Science.gov

Sample records for distributed time-varying delays

  1. Almost periodic solutions for a memristor-based neural networks with leakage, time-varying and distributed delays.

    PubMed

    Jiang, Ping; Zeng, Zhigang; Chen, Jiejie

    2015-08-01

    In this paper, we study the existence and global exponential stability of almost periodic solution for memristor-based neural networks with leakage, time-varying and distributed delays. Using a new Lyapunov function method, we prove that this delayed neural network has a unique almost periodic solution, which is globally exponentially stable. Moreover, the obtained conclusion on the almost periodic solution is applied to prove the existence and stability of periodic solution (or equilibrium point) for this delayed neural network with periodic coefficients (or constant coefficients).

  2. Global exponential stability of impulsive complex-valued neural networks with both asynchronous time-varying and continuously distributed delays.

    PubMed

    Song, Qiankun; Yan, Huan; Zhao, Zhenjiang; Liu, Yurong

    2016-09-01

    This paper investigates the stability problem for a class of impulsive complex-valued neural networks with both asynchronous time-varying and continuously distributed delays. By employing the idea of vector Lyapunov function, M-matrix theory and inequality technique, several sufficient conditions are obtained to ensure the global exponential stability of equilibrium point. When the impulsive effects are not considered, several sufficient conditions are also given to guarantee the existence, uniqueness and global exponential stability of equilibrium point. Two examples are given to illustrate the effectiveness and lower level of conservatism of the proposed criteria in comparison with some existing results.

  3. Design of delay-dependent state estimator for discrete-time recurrent neural networks with interval discrete and infinite-distributed time-varying delays.

    PubMed

    Liao, Chin-Wen; Lu, Chien-Yu

    2011-06-01

    The state estimation problem for discrete-time recurrent neural networks with both interval discrete and infinite-distributed time-varying delays is studied in this paper, where interval discrete time-varying delay is in a given range. The activation functions are assumed to be globally Lipschitz continuous. A delay-dependent condition for the existence of state estimators is proposed based on new bounding techniques. Via solutions to certain linear matrix inequalities, general full-order state estimators are designed that ensure globally asymptotic stability. The significant feature is that no inequality is needed for seeking upper bounds for the inner product between two vectors, which can reduce the conservatism of the criterion by employing the new bounding techniques. Two illustrative examples are given to demonstrate the effectiveness and applicability of the proposed approach.

  4. Delay-dependent fuzzy static output feedback control for discrete-time fuzzy stochastic systems with distributed time-varying delays.

    PubMed

    Xia, ZhiLe; Li, JunMin; Li, JiangRong

    2012-11-01

    This paper is concerned with the delay-dependent H(∞) fuzzy static output feedback control scheme for discrete-time Takagi-Sugeno (T-S) fuzzy stochastic systems with distributed time-varying delays. To begin with, the T-S fuzzy stochastic system is transformed to an equivalent switching fuzzy stochastic system. Then, based on novel matrix decoupling technique, improved free-weighting matrix technique and piecewise Lyapunov-Krasovskii function (PLKF), a new delay-dependent H(∞) fuzzy static output feedback controller design approach is first derived for the switching fuzzy stochastic system. Some drawbacks existing in the previous papers such as matrix equalities constraint, coordinate transformation, the same output matrices, diagonal structure constraint on Lyapunov matrices and BMI problem have been eliminated. Since only a set of LMIs is involved, the controller parameters can be solved directly by the Matlab LMI toolbox. Finally, two examples are provided to illustrate the validity of the proposed method.

  5. Dissipativity analysis of stochastic memristor-based recurrent neural networks with discrete and distributed time-varying delays.

    PubMed

    Radhika, Thirunavukkarasu; Nagamani, Gnaneswaran

    2016-01-01

    In this paper, based on the knowledge of memristor-based recurrent neural networks (MRNNs), the model of the stochastic MRNNs with discrete and distributed delays is established. In real nervous systems and in the implementation of very large-scale integration (VLSI) circuits, noise is unavoidable, which leads to the stochastic model of the MRNNs. In this model, the delay interval is decomposed into two subintervals by using the tuning parameter α such that 0 < α < 1. By constructing proper Lyapunov-Krasovskii functional and employing direct delay decomposition technique, several sufficient conditions are given to guarantee the dissipativity and passivity of the stochastic MRNNs with discrete and distributed delays in the sense of Filippov solutions. Using the stochastic analysis theory and Itô's formula for stochastic differential equations, we establish sufficient conditions for dissipativity criterion. The dissipativity and passivity conditions are presented in terms of linear matrix inequalities, which can be easily solved by using Matlab Tools. Finally, three numerical examples with simulations are presented to demonstrate the effectiveness of the theoretical results.

  6. Distributed Tracking with Consensus on Noisy Time-varying Graphs: Convergence Results and Applications

    DTIC Science & Technology

    2010-12-01

    R. M. Murray, “ Consensus problems in networks of agents with switching topology and time -delays,” IEEE Trans. Autom. Control, vol. 49, no. 9, pp... Distributed Tracking with Consensus on Noisy Time -varying Graphs: Convergence Results and Applications Sudharman K. Jayaweera and Y. Ruan ECE... distributed tracking with consensus on a time -varying graph with noisy communications links and sensing constraints. We develop a framework to handle the

  7. Stability Analysis of Uncertain Switched Delay Systems: A Time-Varying Lyapunov Function Approach

    NASA Astrophysics Data System (ADS)

    Huang, Ganji; Luo, Shixian; Chen, Wu-Hua

    Exponential stability for switched systems with uncertain parameters and time-varying delay is considered in this paper. The parametric uncertainties are assumed to be time-varying and norm-bounded. By introducing a novel piecewise time-varying Lyapunov function and using Razumikhin techniques, some linear matrix inequalities (LMIs) stability criteria are derived to guarantee the exponential stability of the switched delay systems. A numerical example is presented to demonstrate the effectiveness of the proposed method.

  8. Reliable dissipative control of high-speed train with probabilistic time-varying delays

    NASA Astrophysics Data System (ADS)

    Kaviarasan, B.; Sakthivel, R.; Shi, Y.

    2016-12-01

    This paper investigates the reliable dissipative control problem for high-speed trains (HSTs) under probabilistic time-varying sampling with a known upper bound on the sampling intervals. In particular, random variables obeying the Bernoulli distribution are considered to account for the probabilistic time-varying delays. Based on Lyapunov-Krasovskii functional approach which considers full use of the available information about actual sampling pattern, a new set of sufficient condition is established to guarantee that the HST can well track the desired speed and the relative spring displacement between the two neighbouring carriages is asymptotically stable and the corresponding error system is strictly ?-dissipative. The existence condition of the dissipativity-based reliable sampled-data controller is obtained in terms of a set of linear matrix inequalities which are delay-distribution-dependent, i.e. the solvability of the condition depends on not only the variation range of the delay but also the probability distribution of it. Moreover, different control processes for the HST system can be obtained from the proposed design procedure and hence it can reduce the time and cost. Finally, the effectiveness and benefits of the proposed control law is demonstrated through a numerical example by taking the experimental values of Japan Shinkansen HST.

  9. Containment consensus with measurement noises and time-varying communication delays

    NASA Astrophysics Data System (ADS)

    Zhou, Feng; Wang, Zheng-Jie; Fan, Ning-Jun

    2015-02-01

    In this paper, we consider the containment consensus control problem for multi-agent systems with measurement noises and time-varying communication delays under directed networks. By using stochastic analysis tools and algebraic graph theory, we prove that the followers can converge to the convex hull spanned by the leaders in the sense of mean square if the allowed upper bound of the time-varying delays satisfies a certain sufficient condition. Moreover, the time-varying delays are asymmetric for each follower agent, and the time-delay-dependent consensus condition is derived. Finally, numerical simulations are provided to illustrate the effectiveness of the obtained theoretical results. Project supported by the National Natural Science Foundation of China (Grant No. 11102019), the Aeronautical Science Foundation of China (Grant No. 2013ZC72006), and the Research Foundation of Beijing Institute of Technology, China.

  10. Stability of uncertain impulsive complex-variable chaotic systems with time-varying delays.

    PubMed

    Zheng, Song

    2015-09-01

    In this paper, the robust exponential stabilization of uncertain impulsive complex-variable chaotic delayed systems is considered with parameters perturbation and delayed impulses. It is assumed that the considered complex-variable chaotic systems have bounded parametric uncertainties together with the state variables on the impulses related to the time-varying delays. Based on the theories of adaptive control and impulsive control, some less conservative and easily verified stability criteria are established for a class of complex-variable chaotic delayed systems with delayed impulses. Some numerical simulations are given to validate the effectiveness of the proposed criteria of impulsive stabilization for uncertain complex-variable chaotic delayed systems.

  11. An observer for a velocity-sensorless VTOL aircraft with time-varying measurement delay

    NASA Astrophysics Data System (ADS)

    He, Qing; Liu, Jinkun

    2016-02-01

    This paper presents a kind of state observer for a velocity-sensorless vertical take-off and landing (VTOL) aircraft with bounded time-varying delay in its measurement outputs. The proposed observer predicts current state variables based on the delayed outputs, and the estimated state variables can be considered as the actual state variables for feedback control scheme design. Since the delay is time-varying, compared to the constant delay case, different analysis theory must be employed. Under the assumption that the delays are identical for different outputs and bounded input, the asymptotic convergence property of the estimation error based on Lyapunov-Razumikhin theorem is proved. A relative large time delay for the VTOL aircraft in the outputs has been tested in the numerical simulation, and the simulation results show the effectiveness of the proposed observer.

  12. New Stabilization for Dynamical System with Two Additive Time-Varying Delays

    PubMed Central

    Yang, Fan; Chen, Xiaozhou

    2014-01-01

    This paper provides a new delay-dependent stabilization criterion for systems with two additive time-varying delays. The novel functional is constructed, a tighter upper bound of the derivative of the Lyapunov functional is obtained. These results have advantages over some existing ones because the combination of the delay decomposition technique and the reciprocally convex approach. Two examples are provided to demonstrate the less conservatism and effectiveness of the results in this paper. PMID:24701159

  13. Global exponential synchronization of memristor-based recurrent neural networks with time-varying delays.

    PubMed

    Wen, Shiping; Bao, Gang; Zeng, Zhigang; Chen, Yiran; Huang, Tingwen

    2013-12-01

    This paper deals with the problem of global exponential synchronization of a class of memristor-based recurrent neural networks with time-varying delays based on the fuzzy theory and Lyapunov method. First, a memristor-based recurrent neural network is designed. Then, considering the state-dependent properties of the memristor, a new fuzzy model employing parallel distributed compensation (PDC) gives a new way to analyze the complicated memristor-based neural networks with only two subsystems. Comparisons between results in this paper and in the previous ones have been made. They show that the results in this paper improve and generalized the results derived in the previous literature. An example is also given to illustrate the effectiveness of the results.

  14. Improved results for linear discrete-time systems with an interval time-varying input delay

    NASA Astrophysics Data System (ADS)

    Zhang, Jin; Peng, Chen; Zheng, Min

    2016-01-01

    This paper addresses the problem of delay-dependent stability analysis and controller synthesis for a discrete-time system with an interval time-varying input delay. By dividing delay interval into multiple parts and constructing a novel piecewise Lyapunov-Krasovskii functional, an improved delay-partitioning-dependent stability criterion and a stabilisation criterion are obtained in terms of matrix inequalities. Compared with some existing results, since a tighter bounding inequality is employed to deal with the integral items, our results depend on less number of linear matrix inequality scalar decision variables while obtaining same or better allowable upper delay bound. Numerical examples show the effectiveness of the proposed method.

  15. Global exponential stability for switched memristive neural networks with time-varying delays.

    PubMed

    Xin, Youming; Li, Yuxia; Cheng, Zunshui; Huang, Xia

    2016-08-01

    This paper considers the problem of exponential stability for switched memristive neural networks (MNNs) with time-varying delays. Different from most of the existing papers, we model a memristor as a continuous system, and view switched MNNs as switched neural networks with uncertain time-varying parameters. Based on average dwell time technique, mode-dependent average dwell time technique and multiple Lyapunov-Krasovskii functional approach, two conditions are derived to design the switching signal and guarantee the exponential stability of the considered neural networks, which are delay-dependent and formulated by linear matrix inequalities (LMIs). Finally, the effectiveness of the theoretical results is demonstrated by two numerical examples.

  16. Stability analysis of switched stochastic neural networks with time-varying delays.

    PubMed

    Wu, Xiaotai; Tang, Yang; Zhang, Wenbing

    2014-03-01

    This paper is concerned with the global exponential stability of switched stochastic neural networks with time-varying delays. Firstly, the stability of switched stochastic delayed neural networks with stable subsystems is investigated by utilizing the mathematical induction method, the piecewise Lyapunov function and the average dwell time approach. Secondly, by utilizing the extended comparison principle from impulsive systems, the stability of stochastic switched delayed neural networks with both stable and unstable subsystems is analyzed and several easy to verify conditions are derived to ensure the exponential mean square stability of switched delayed neural networks with stochastic disturbances. The effectiveness of the proposed results is illustrated by two simulation examples.

  17. Nonlinear adaptive control for teleoperation systems with symmetrical and unsymmetrical time-varying delay

    NASA Astrophysics Data System (ADS)

    Islam, S.; Liu, P. X.; El Saddik, A.

    2015-12-01

    The stability and trajectory tracking control problem of passive teleoperation systems with the presence of the symmetrical and unsymmetrical time-varying communication delay is addressed in this paper. The proposed teleoperator is designed by coupling local and remote sites by delaying position signals of the master and slave manipulator. The design also comprises local proportional and derivative signals with nonlinear adaptive terms to cope with parametric uncertainty associated with the master and slave dynamics. The Lyapunov-Krasovskii function is employed to establish stability conditions for the closed-loop teleoperators under both symmetrical and unsymmetrical time-varying communication delay. These delay-dependent conditions allow the designer to estimate the control gains a priori in order to achieve asymptotic property of the position, velocity and synchronisation errors of the master and slave systems. Finally, simulation results along with comparative studies are presented to illustrate the effectiveness of the proposed method.

  18. New exponential synchronization criteria for time-varying delayed neural networks with discontinuous activations.

    PubMed

    Cai, Zuowei; Huang, Lihong; Zhang, Lingling

    2015-05-01

    This paper investigates the problem of exponential synchronization of time-varying delayed neural networks with discontinuous neuron activations. Under the extended Filippov differential inclusion framework, by designing discontinuous state-feedback controller and using some analytic techniques, new testable algebraic criteria are obtained to realize two different kinds of global exponential synchronization of the drive-response system. Moreover, we give the estimated rate of exponential synchronization which depends on the delays and system parameters. The obtained results extend some previous works on synchronization of delayed neural networks not only with continuous activations but also with discontinuous activations. Finally, numerical examples are provided to show the correctness of our analysis via computer simulations. Our method and theoretical results have a leading significance in the design of synchronized neural network circuits involving discontinuous factors and time-varying delays.

  19. Stability Analysis of Networked Control Systems With Aperiodic Sampling and Time-Varying Delay.

    PubMed

    Chen, Jie; Meng, Su; Sun, Jian

    2016-12-01

    This paper addresses the stability of networked control systems with aperiodic sampling and time-varying network-induced delay. The sampling intervals are assumed to vary within a known interval. The transmission delay is assumed to belong to a given interval. The closed-loop system is first converted to a discrete-time system with multiple time-varying delays and norm-bounded uncertainties resulting from the variation of the sampling intervals. And then, it is transformed into a delay-free system being form of an interconnection of two subsystems. By utilizing scaled small gain theorem, an asymptotic stability criterion for the closed-loop system is proposed in terms of linear matrix inequality. Finally, numerical examples demonstrate the effectiveness of the proposed method and its advantages over existing methods.

  20. Complete stability of cellular neural networks with unbounded time-varying delays.

    PubMed

    Wang, Lili; Chen, Tianping

    2012-12-01

    In this paper, we are concerned with the delayed cellular neural networks (DCNNs) in the case that the time-varying delays are unbounded. Under some conditions, it shows that the DCNNs can exhibit 3(n) equilibrium points. Then, we track the dynamics of u(t)(t>0) in two cases with respect to different types of subset regions in which u(0) is located. It concludes that every solution trajectory u(t) would converge to one of the equilibrium points despite the time-varying delays, that is, the delayed cellular neural networks are completely stable. The method is novel and the results obtained extend the existing ones. In addition, two illustrative examples are presented to verify the effectiveness of our results.

  1. Improved exponential convergence result for generalized neural networks including interval time-varying delayed signals.

    PubMed

    Rajchakit, G; Saravanakumar, R; Ahn, Choon Ki; Karimi, Hamid Reza

    2017-02-01

    This article examines the exponential stability analysis problem of generalized neural networks (GNNs) including interval time-varying delayed states. A new improved exponential stability criterion is presented by establishing a proper Lyapunov-Krasovskii functional (LKF) and employing new analysis theory. The improved reciprocally convex combination (RCC) and weighted integral inequality (WII) techniques are utilized to obtain new sufficient conditions to ascertain the exponential stability result of such delayed GNNs. The superiority of the obtained results is clearly demonstrated by numerical examples.

  2. Almost automorphic solutions for shunting inhibitory cellular neural networks with time-varying delays.

    PubMed

    Xu, Changjin; Liao, Maoxin

    2015-01-01

    This paper is concerned with the shunting inhibitory cellular neural networks with time-varying delays. Under some suitable conditions, we establish some criteria on the existence and global exponential stability of the almost automorphic solutions of the networks. Numerical simulations are given to support the theoretical findings.

  3. Passivity analysis of uncertain stochastic neural networks with time-varying delays and Markovian jumping parameters.

    PubMed

    Ali, M Syed; Rani, M Esther

    2015-01-01

    This paper investigates the problem of robust passivity of uncertain stochastic neural networks with time-varying delays and Markovian jumping parameters. To reflect most of the dynamical behaviors of the system, both parameter uncertainties and stochastic disturbances are considered; stochastic disturbances are given in the form of a Brownian motion. By utilizing the Lyapunov functional method, the Itô differential rule, and matrix analysis techniques, we establish a sufficient criterion such that, for all admissible parameter uncertainties and stochastic disturbances, the stochastic neural network is robustly passive in the sense of expectation. A delay-dependent stability condition is formulated, in which the restriction of the derivative of the time-varying delay should be less than 1 is removed. The derived criteria are expressed in terms of linear matrix inequalities that can be easily checked by using the standard numerical software. Illustrative examples are presented to demonstrate the effectiveness and usefulness of the proposed results.

  4. Stabilisation for switched linear systems with time-varying delay and input saturation

    NASA Astrophysics Data System (ADS)

    Chen, Yonggang; Fei, Shumin; Zhang, Kanjian

    2014-03-01

    This article investigates the stabilisation problems for continuous-time and discrete-time switched systems with time-varying delay and saturated control input. Based on dwell time switching signals and multiple Lyapunov functional method, stabilisation conditions are well obtained in the context of linear matrix inequalities. To estimate attractive regions as large as possible, the feasibility problems are translated into optimisation problems. In addition, the corresponding results are presented for linear time-delay systems and switched delay-free systems, which improve and supplement some existing ones in the literature. Finally, numerical examples and simulations are given to illustrate the effectiveness and values of the proposed results.

  5. Stability of Nonlinear Systems with Unknown Time-varying Feedback Delay

    NASA Astrophysics Data System (ADS)

    Chunodkar, Apurva A.; Akella, Maruthi R.

    2013-12-01

    This paper considers the problem of stabilizing a class of nonlinear systems with unknown bounded delayed feedback wherein the time-varying delay is 1) piecewise constant 2) continuous with a bounded rate. We also consider application of these results to the stabilization of rigid-body attitude dynamics. In the first case, the time-delay in feedback is modeled specifically as a switch among an arbitrarily large set of unknown constant values with a known strict upper bound. The feedback is a linear function of the delayed states. In the case of linear systems with switched delay feedback, a new sufficiency condition for average dwell time result is presented using a complete type Lyapunov-Krasovskii (L-K) functional approach. Further, the corresponding switched system with nonlinear perturbations is proven to be exponentially stable inside a well characterized region of attraction for an appropriately chosen average dwell time. In the second case, the concept of the complete type L-K functional is extended to a class of nonlinear time-delay systems with unknown time-varying time-delay. This extension ensures stability robustness to time-delay in the control design for all values of time-delay less than the known upper bound. Model-transformation is used in order to partition the nonlinear system into a nominal linear part that is exponentially stable with a bounded perturbation. We obtain sufficient conditions which ensure exponential stability inside a region of attraction estimate. A constructive method to evaluate the sufficient conditions is presented together with comparison with the corresponding constant and piecewise constant delay. Numerical simulations are performed to illustrate the theoretical results of this paper.

  6. Global exponential stability and dissipativity of generalized neural networks with time-varying delay signals.

    PubMed

    Manivannan, R; Samidurai, R; Cao, Jinde; Alsaedi, Ahmed; Alsaadi, Fuad E

    2017-03-01

    This paper investigates the problems of exponential stability and dissipativity of generalized neural networks (GNNs) with time-varying delay signals. By constructing a novel Lyapunov-Krasovskii functionals (LKFs) with triple integral terms that contain more advantages of the state vectors of the neural networks, and the upper bound on the time-varying delay signals are formulated. We employ a new integral inequality technique (IIT), free-matrix-based (FMB) integral inequality approach, and Wirtinger double integral inequality (WDII) technique together with the reciprocally convex combination (RCC) approach to bound the time derivative of the LKFs. An improved exponential stability and strictly (Q,S,R)-γ-dissipative conditions of the addressed systems are represented by the linear matrix inequalities (LMIs). Finally, four interesting numerical examples are developed to verify the usefulness of the proposed method with a practical application to a biological network.

  7. Robust stabilisation of time-varying delay systems with probabilistic uncertainties

    NASA Astrophysics Data System (ADS)

    Jiang, Ning; Xiong, Junlin; Lam, James

    2016-09-01

    For robust stabilisation of time-varying delay systems, only sufficient conditions are available to date. A natural question is as follows: if the existing sufficient conditions are not satisfied, and hence no controllers can be found, what can one do to improve the stability performance of time-varying delay systems? This question is addressed in this paper when there is a probabilistic structure on the parameter uncertainty set. A randomised algorithm is proposed to design a state-feedback controller, which stabilises the system over the uncertainty domain in a probabilistic sense. The capability of the designed controller is quantified by the probability of stability of the resulting closed-loop system. The accuracy of the solution obtained from the randomised algorithm is also analysed. Finally, numerical examples are used to illustrate the effectiveness and advantages of the developed controller design approach.

  8. On global exponential stability of positive neural networks with time-varying delay.

    PubMed

    Hien, Le Van

    2017-03-01

    This paper presents a new result on the existence, uniqueness and global exponential stability of a positive equilibrium of positive neural networks in the presence of bounded time-varying delay. Based on some novel comparison techniques, a testable condition is derived to ensure that all the state trajectories of the system converge exponentially to a unique positive equilibrium. The effectiveness of the obtained results is illustrated by a numerical example.

  9. H∞ state estimation of generalised neural networks with interval time-varying delays

    NASA Astrophysics Data System (ADS)

    Saravanakumar, R.; Syed Ali, M.; Cao, Jinde; Huang, He

    2016-12-01

    This paper focuses on studying the H∞ state estimation of generalised neural networks with interval time-varying delays. The integral terms in the time derivative of the Lyapunov-Krasovskii functional are handled by the Jensen's inequality, reciprocally convex combination approach and a new Wirtinger-based double integral inequality. A delay-dependent criterion is derived under which the estimation error system is globally asymptotically stable with H∞ performance. The proposed conditions are represented by linear matrix inequalities. Optimal H∞ norm bounds are obtained easily by solving convex problems in terms of linear matrix inequalities. The advantage of employing the proposed inequalities is illustrated by numerical examples.

  10. A dynamic feedback control strategy for control loops with time-varying delay

    NASA Astrophysics Data System (ADS)

    Ebrahimi, Behrouz; Tafreshi, Reza; Franchek, Matthew; Grigoriadis, Karolos; Mohammadpour, Javad

    2014-05-01

    Dynamic systems of nth order with time-varying delay in the control loop are examined in this paper. The infinite-dimensional pure delay problem is approximated using a jth-order Padé approximation. Although the approximation provides a well-matched finite-dimensional configuration, it poses a new challenge in terms of unstable internal dynamics for the resulted non-minimum phase system. Such a non-minimum phase characteristic limits the closed-loop system bandwidth and leads to an imperfect tracking performance. To circumvent this problem, the unstable internal dynamics of the system is captured and a new dynamic compensator is proposed to stabilise it in a systematic framework. A dynamic controller is developed, which provides the overall system stability against unmatched perturbation and meets the desired tracking error dynamics. The proposed approach is then applied to fuelling control in gasoline engines addressing the varying transport delay of the oxygen-sensor measurement in the exhaust. The developed methodology is finally validated on a Ford F-150 SI lean-burn engine model with large time-varying delay in the control loop.

  11. Adaptive control for a class of MIMO nonlinear time delay systems against time varying actuator failures.

    PubMed

    Hashemi, Mahnaz; Ghaisari, Jafar; Askari, Javad

    2015-07-01

    This paper investigates an adaptive controller for a class of Multi Input Multi Output (MIMO) nonlinear systems with unknown parameters, bounded time delays and in the presence of unknown time varying actuator failures. The type of considered actuator failure is one in which some inputs may be stuck at some time varying values where the values, times and patterns of the failures are unknown. The proposed approach is constructed based on a backstepping design method. The boundedness of all the closed-loop signals is guaranteed and the tracking errors are proved to converge to a small neighborhood of the origin. The proposed approach is employed for a double inverted pendulums benchmark and a chemical reactor system. The simulation results show the effectiveness of the proposed method.

  12. Non-fragile control for a class of uncertain systems with time-varying delay

    NASA Astrophysics Data System (ADS)

    Yao, Hejun; Yuan, Fushun; Qiao, Yue

    2017-01-01

    The problem of exponential stability non-fragile control for uncertain systems with time-varying delay is considered in this paper. Based on the Lyapunov stability theorem, and by using linear matrix inequality approach, a new approach is obtained to design the state feedback exponential stability non-fragile controller. By introducing a new Lyapunov functional, a sufficient exponential stability condition is given in terms of linear matrix inequality. With the non-fragile controller and the linear matrix inequality Control Toolbox in MATLAB, the simulation results are easier obtained.

  13. Finite-time boundedness and stabilization of uncertain switched neural networks with time-varying delay.

    PubMed

    Wu, Yuanyuan; Cao, Jinde; Alofi, Abdulaziz; Al-Mazrooei, Abdullah; Elaiw, Ahmed

    2015-09-01

    This paper deals with the finite-time boundedness and stabilization problem for a class of switched neural networks with time-varying delay and parametric uncertainties. Based on Lyapunov-like function method and average dwell time technique, some sufficient conditions are derived to guarantee the finite-time boundedness of considered uncertain switched neural networks. Furthermore, the state feedback controller is designed to solve the finite-time stabilization problem. Moreover, the proposed sufficient conditions can be simplified into the form of linear matrix equalities for conveniently using Matlab LMI toolbox. Finally, two numerical examples are given to show the effectiveness of the main results.

  14. Attitude tracking control for spacecraft formation with time-varying delays and switching topology

    NASA Astrophysics Data System (ADS)

    Yang, Hongjiu; You, Xiu; Hua, Changchun

    2016-09-01

    This paper investigates attitude dynamic tracking control for spacecraft formation in the presence of unmeasurable velocity information with time-varying delays and switching topology. Based on an extended state observer, a nonlinear attitude tracking control approach is developed for spacecraft attitude model formulated by Euler-Lagrangian equations. The attitude tracking controller allows for external disturbances and absence of angular velocity information. Both auto-stable region techniques and a Lyapunov function approach are developed to prove ultimately bounded tracking. Simulation results demonstrate effectiveness of the nonlinear control techniques proposed in this paper.

  15. Synchronization Control for Stochastic Neural Networks with Mixed Time-Varying Delays

    PubMed Central

    Zhu, Qing; Song, Aiguo; Fei, Shumin; Yang, Yuequan; Cao, Zhiqiang

    2014-01-01

    Synchronization control of stochastic neural networks with time-varying discrete and continuous delays has been investigated. A novel control scheme is proposed using the Lyapunov functional method and linear matrix inequality (LMI) approach. Sufficient conditions have been derived to ensure the global asymptotical mean-square stability for the error system, and thus the drive system synchronizes with the response system. Also, the control gain matrix can be obtained. With these effective methods, synchronization can be achieved. Simulation results are presented to show the effectiveness of the theoretical results. PMID:25110747

  16. Mixed outer synchronization of coupled complex networks with time-varying coupling delay.

    PubMed

    Wang, Jun-Wei; Ma, Qinghua; Zeng, Li; Abd-Elouahab, Mohammed Salah

    2011-03-01

    In this paper, the problem of outer synchronization between two complex networks with the same topological structure and time-varying coupling delay is investigated. In particular, we introduce a new type of outer synchronization behavior, i.e., mixed outer synchronization (MOS), in which different state variables of the corresponding nodes can evolve into complete synchronization, antisynchronization, and even amplitude death simultaneously for an appropriate choice of the scaling matrix. A novel nonfragile linear state feedback controller is designed to realize the MOS between two networks and proved analytically by using Lyapunov-Krasovskii stability theory. Finally, numerical simulations are provided to demonstrate the feasibility and efficacy of our proposed control approach.

  17. New Results on Passivity Analysis of Stochastic Neural Networks with Time-Varying Delay and Leakage Delay

    PubMed Central

    Li, YaJun; Huang, Zhaowen

    2015-01-01

    The passivity problem for a class of stochastic neural networks systems (SNNs) with varying delay and leakage delay has been further studied in this paper. By constructing a more effective Lyapunov functional, employing the free-weighting matrix approach, and combining with integral inequality technic and stochastic analysis theory, the delay-dependent conditions have been proposed such that SNNs are asymptotically stable with guaranteed performance. The time-varying delay is divided into several subintervals and two adjustable parameters are introduced; more information about time delay is utilised and less conservative results have been obtained. Examples are provided to illustrate the less conservatism of the proposed method and simulations are given to show the impact of leakage delay on stability of SNNs. PMID:26366165

  18. H∞ control problem for Hopfield neural networks with interval time-varying delay

    NASA Astrophysics Data System (ADS)

    Emharuethai, Chanikan

    2016-02-01

    In this paper, we consider H∞ control problem for a class Hopfield neural networks with interval time-varying delay. The time delay is a continuous function belonging to a given interval, but not necessariry differentiable. The stabilizing controllers to be designed must satisfy some exponential stability constraints on the closed-loop poles. Based on the construction of improved Lyapunov-Krasovskii functionals combined with Newton-Leibniz formula. H∞ controller is designed via memoryless state feedback control and new sufficient conditions for the existence of the H∞ state-feedback for the system are given in terms of linear matrix inequalities (LMIs). Numerical examples are given to illustrate the effectiveness of the obtained result.

  19. Decentralized adaptive fuzzy output feedback control of nonlinear interconnected systems with time-varying delay

    NASA Astrophysics Data System (ADS)

    Wang, Qin; Chen, Zuwen; Song, Aiguo

    2017-01-01

    A robust adaptive output-feedback control scheme based on K-filters is proposed for a class of nonlinear interconnected time-varying delay systems with immeasurable states. It is difficult to design the controller due to the existence of the immeasurable states and the time-delay couplings among interconnected subsystems. This difficulty is overcome by use of the fuzzy system, the K-filters and the appropriate Lyapunov-Krasovskii functional. Based on Lyapunov theory, the closed-loop control system is proved to be semi-global uniformly ultimately bounded (SGUUB), and the output tracking error converges to a neighborhood of zero. Simulation results demonstrate the effectiveness of the approach.

  20. Bilateral shared autonomous systems with passive and nonpassive input forces under time varying delay.

    PubMed

    Islam, Shafiqul; Liu, Peter X; El Saddik, Abdulmotaleb; Dias, J; Seneviratne, Lakmal

    2015-01-01

    In this paper, we address stability and tracking control problem of bilateral shared autonomous systems in the presence of passive and nonpassive input interaction forces. The design comprises delayed position and position-velocity signals with the known and unknown structures of the master and slave manipulator dynamics. Using novel Lyapunov-Krasovskii functional, stability and tracking conditions of the coupled master-slave shared autonomous systems are developed under symmetrical and unsymmetrical time varying data transmission delays. This condition allows the designer to estimate the control design parameters to ensure position, velocity and synchronizing errors of the master and slave manipulators. Finally, evaluation results are presented to demonstrate the validity of the proposed design for real-time teleoperation applications.

  1. Multiple μ-stability of neural networks with unbounded time-varying delays.

    PubMed

    Wang, Lili; Chen, Tianping

    2014-05-01

    In this paper, we are concerned with a class of recurrent neural networks with unbounded time-varying delays. Based on the geometrical configuration of activation functions, the phase space R(n) can be divided into several Φη-type subsets. Accordingly, a new set of regions Ωη are proposed, and rigorous mathematical analysis is provided to derive the existence of equilibrium point and its local μ-stability in each Ωη. It concludes that the n-dimensional neural networks can exhibit at least 3(n) equilibrium points and 2(n) of them are μ-stable. Furthermore, due to the compatible property, a set of new conditions are presented to address the dynamics in the remaining 3(n)-2(n) subset regions. As direct applications of these results, we can get some criteria on the multiple exponential stability, multiple power stability, multiple log-stability, multiple log-log-stability and so on. In addition, the approach and results can also be extended to the neural networks with K-level nonlinear activation functions and unbounded time-varying delays, in which there can store (2K+1)(n) equilibrium points, (K+1)(n) of them are locally μ-stable. Numerical examples are given to illustrate the effectiveness of our results.

  2. A delay-range-partition approach to analyse stability of linear systems with time-varying delays

    NASA Astrophysics Data System (ADS)

    Xue, Y.; Zhang, X.; Han, Y. Y.; Shi, M.

    2016-12-01

    In this paper, the stability analysis of linear systems with an interval time-varying delay is investigated. First, augmented Lyapunov-Krasovskii functionals are constructed, which include more information of the delay's range and the delay's derivative. Second, two improved integral inequalities, which are less conservative than Jensen's integral inequalities, and delay-range-partition approach are utilised to estimate the upper bounds of the derivatives of the augmented Lyapunov-Krasovskii functionals. Then, less conservative stability criteria are proposed no matter whether the lower bound of delay is zero or not. Finally, to illustrate the effectiveness of the stability criteria proposed in this paper, two numerical examples are given and their results are compared with the existing results.

  3. Exponential synchronization of discontinuous neural networks with time-varying mixed delays via state feedback and impulsive control.

    PubMed

    Yang, Xinsong; Cao, Jinde; Ho, Daniel W C

    2015-04-01

    This paper investigates drive-response synchronization for a class of neural networks with time-varying discrete and distributed delays (mixed delays) as well as discontinuous activations. Strict mathematical proof shows the global existence of Filippov solutions to neural networks with discontinuous activation functions and the mixed delays. State feedback controller and impulsive controller are designed respectively to guarantee global exponential synchronization of the neural networks. By using Lyapunov function and new analysis techniques, several new synchronization criteria are obtained. Moreover, lower bound on the convergence rate is explicitly estimated when state feedback controller is utilized. Results of this paper are new and some existing ones are extended and improved. Finally, numerical simulations are given to verify the effectiveness of the theoretical results.

  4. Containment Control for First-Order Multi-Agent Systems with Time-Varying Delays and Uncertain Topologies

    NASA Astrophysics Data System (ADS)

    Wang, Fu-Yong; Yang, Hong-Yong; Zhang, Shu-Ning; Han, Fu-Jun

    2016-08-01

    Containment control of first-order multi-agent systems with uncertain topologies and communication time-delays is studied. Suppose system topologies are dynamically changed, a containment control algorithm with time-varying delays is presented. The stability of the control algorithm is studied under the assumption that communication topologies are jointly-connected, and constraint condition of distributed containment control for delayed multi-agent systems is derived with the aid of Lyapunov-Krasovskii function. Simulation results are provided to prove the correctness and effectiveness of the conclusion. Supported by the National Natural Science Foundation of China under Grant Nos. 61273152, 61304052, 51407088, the Science Foundation of Education Office of Shandong Province of China under Grant Nos. ZR2011FM07, BS2015DX018

  5. Delay-dependent finite-time boundedness of a class of Markovian switching neural networks with time-varying delays.

    PubMed

    Zhong, Qishui; Cheng, Jun; Zhao, Yuqing

    2015-07-01

    In this paper, a novel method is developed for delay-dependent finite-time boundedness of a class of Markovian switching neural networks with time-varying delays. New sufficient condition for stochastic boundness of Markovian jumping neural networks is presented and proved by an newly augmented stochastic Lyapunov-Krasovskii functional and novel activation function conditions, the state trajectory remains in a bounded region of the state space over a given finite-time interval. Finally, a numerical example is given to illustrate the efficiency and less conservative of the proposed method.

  6. New passivity criteria for memristive uncertain neural networks with leakage and time-varying delays.

    PubMed

    Xiao, Jianying; Zhong, Shouming; Li, Yongtao

    2015-11-01

    In this paper, the problem of passivity analysis is studied for memristor-based uncertain neural networks with leakage and time-varying delays. By combining differential inclusions with set-valued maps, the system of memristive neural networks is changed into the conventional one. By adding a triple quadratic integral and relaxing the requirement for the positive definiteness of some matrices, a proper Lyapunov-Krasovskii functional is constructed. Based on the establishment of the novel Lyapunov-Krasovskii functional, the new passivity criteria are derived by mainly applying Wirtinger-based double integral inequality, S-procedure and so on. Moreover, the conservatism of passivity conditions can be reduced. Finally, four numerical examples are given to show the effectiveness and less conservatism of the proposed criteria.

  7. μ-Stability of Nonlinear Positive Systems With Unbounded Time-Varying Delays.

    PubMed

    Chen, Tianping; Liu, Xiwei

    2016-03-11

    The stability of the zero solution plays an important role in the investigation of positive systems. In this brief, we discuss the μ-stability of positive nonlinear systems with unbounded time-varying delays. The system is modeled by the continuous-time ordinary differential equation. Under some assumptions on the nonlinear functions, such as homogeneous, cooperative, and nondecreasing, we propose a novel transform, by which the nonlinear system reduces to a new system. Thus, we analyze its dynamics, which can simplify the nonlinear homogenous functions with respect to the arbitrary dilation map to those with respect to the standard dilation map. We finally get some new criteria for the global μ-stability taking the degree into consideration. A numerical example is given to demonstrate the validity of obtained results.

  8. Robust Reliable Control for Neutral-Type Nonlinear Systems with Time-Varying Delays

    NASA Astrophysics Data System (ADS)

    Mathiyalagan, K.; Sakthivel, R.; Park, Ju. H.

    2014-10-01

    The problem of robust reliable stabilization against actuator failures for a class of uncertain nonlinear neutral systems with time-varying delays is considered. Based on a new Lyapunov-Krasovskii functional, by employing linear matrix inequality technique and free weighting matrix approach, we derived a set of sufficient conditions for the existence of a reliable controller. The derived controller is applied for the robust stabilization of the nonlinear neutral system in the presence of known actuator failure matrix and uncertainties. Further, the results are extended to study the stabilization of neutral systems with unknown actuator failure matrix. The failure of actuators are considered by variables, which are varying in a given interval. The developed theoretical results are established in the form of linear matrix inequalities, which can be easily solved via standard numerical software. Finally, two numerical examples are presented to demonstrate the validity and less conservatism of the obtained results.

  9. Robust Stability of Scaled-Four-Channel Teleoperation with Internet Time-Varying Delays

    PubMed Central

    Delgado, Emma; Barreiro, Antonio; Falcón, Pablo; Díaz-Cacho, Miguel

    2016-01-01

    We describe the application of a generic stability framework for a teleoperation system under time-varying delay conditions, as addressed in a previous work, to a scaled-four-channel (γ-4C) control scheme. Described is how varying delays are dealt with by means of dynamic encapsulation, giving rise to mu-test conditions for robust stability and offering an appealing frequency technique to deal with the stability robustness of the architecture. We discuss ideal transparency problems and we adapt classical solutions so that controllers are proper, without single or double differentiators, and thus avoid the negative effects of noise. The control scheme was fine-tuned and tested for complete stability to zero of the whole state, while seeking a practical solution to the trade-off between stability and transparency in the Internet-based teleoperation. These ideas were tested on an Internet-based application with two Omni devices at remote laboratory locations via simulations and real remote experiments that achieved robust stability, while performing well in terms of position synchronization and force transparency. PMID:27128914

  10. Event-Triggered Generalized Dissipativity Filtering for Neural Networks With Time-Varying Delays.

    PubMed

    Wang, Jia; Zhang, Xian-Ming; Han, Qing-Long

    2016-01-01

    This paper is concerned with event-triggered generalized dissipativity filtering for a neural network (NN) with a time-varying delay. The signal transmission from the NN to its filter is completed through a communication channel. It is assumed that the network measurement of the NN is sampled periodically. An event-triggered communication scheme is introduced to design a suitable filter such that precious communication resources can be saved significantly while certain filtering performance can be ensured. On the one hand, the event-triggered communication scheme is devised to select only those sampled signals violating a certain threshold to be transmitted, which directly leads to saving of precious communication resources. On the other hand, the filtering error system is modeled as a time-delay system closely dependent on the parameters of the event-triggered scheme. Based on this model, a suitable filter is designed such that certain filtering performance can be ensured, provided that a set of linear matrix inequalities are satisfied. Furthermore, since a generalized dissipativity performance index is introduced, several kinds of event-triggered filtering issues, such as H∞ filtering, passive filtering, mixed H∞ and passive filtering, (Q,S,R) -dissipative filtering, and L2 - L∞ filtering, are solved in a unified framework. Finally, two examples are given to illustrate the effectiveness of the proposed method.

  11. Dynamic programming based time-delay estimation technique for analysis of time-varying time-delay

    SciTech Connect

    Gupta, Deepak K.; McKee, George R.; Fonck, Raymond J.

    2010-01-15

    A new time-delay estimation (TDE) technique based on dynamic programming is developed to measure the time-varying time-delay between two signals. The dynamic programming based TDE technique provides a frequency response five to ten times better than previously known TDE techniques, namely, those based on time-lag cross-correlation or wavelet analysis. Effects of frequency spectrum, signal-to-noise ratio, and amplitude of time-delay on response of the TDE technique (represented as transfer function) are studied using simulated data signals. The transfer function for the technique decreases with increase in noise in signal; however it is independent of signal spectrum shape. The dynamic programming based TDE technique is applied to the beam emission spectroscopy diagnostic data to measure poloidal velocity fluctuations, which led to the observation of theoretically predicted zonal flows in high-temperature tokamak plasmas.

  12. Robust asymptotic stability of fuzzy Markovian jumping genetic regulatory networks with time-varying delays by delay decomposition approach

    NASA Astrophysics Data System (ADS)

    Balasubramaniam, P.; Sathy, R.

    2011-02-01

    In this paper, the robust asymptotic stability problem is considered for a class of fuzzy Markovian jumping genetic regulatory networks with uncertain parameters and switching probabilities by delay decomposition approach. The purpose of the addressed stability analysis problem is to establish an easy-to-verify condition under which the dynamics of the true concentrations of the messenger ribonucleic acid (mRNA) and protein is asymptotically stable irrespective of the norm-bounded modeling errors. A new Lyapunov-Krasovskii functional (LKF) is constructed by nonuniformly dividing the delay interval into multiple subinterval, and choosing proper functionals with different weighting matrices corresponding to different subintervals in the LKFs. Employing these new LKFs for the time-varying delays, a new delay-dependent stability criterion is established with Markovian jumping parameters by T-S fuzzy model. Note that the obtained results are formulated in terms of linear matrix inequality (LMI) that can efficiently solved by the LMI toolbox in Matlab. Numerical examples are exploited to illustrate the effectiveness of the proposed design procedures.

  13. Stability and Synchronization for Discrete-Time Complex-Valued Neural Networks with Time-Varying Delays

    PubMed Central

    Zhang, Hao; Wang, Xing-yuan; Lin, Xiao-hui; Liu, Chong-xin

    2014-01-01

    In this paper, the synchronization problem for a class of discrete-time complex-valued neural networks with time-varying delays is investigated. Compared with the previous work, the time delay and parameters are assumed to be time-varying. By separating the real part and imaginary part, the discrete-time model of complex-valued neural networks is derived. Moreover, by using the complex-valued Lyapunov-Krasovskii functional method and linear matrix inequality as tools, sufficient conditions of the synchronization stability are obtained. In numerical simulation, examples are presented to show the effectiveness of our method. PMID:24714386

  14. Stability Analysis of Discrete-Time Neural Networks With Time-Varying Delay via an Extended Reciprocally Convex Matrix Inequality.

    PubMed

    Zhang, Chuan-Ke; He, Yong; Jiang, Lin; Wang, Qing-Guo; Wu, Min

    2017-02-17

    This paper is concerned with the stability analysis of discrete-time neural networks with a time-varying delay. Assessment of the effect of time delays on system stability requires suitable delay-dependent stability criteria. This paper aims to develop new stability criteria for reduction of conservatism without much increase of computational burden. An extended reciprocally convex matrix inequality is developed to replace the popular reciprocally convex combination lemma (RCCL). It has potential to reduce the conservatism of the RCCL-based criteria without introducing any extra decision variable due to its advantage of reduced estimation gap using the same decision variables. Moreover, a delay-product-type term is introduced for the first time into the Lyapunov function candidate such that a delay-variation-dependent stability criterion with the bounds of delay change rate is established. Finally, the advantages of the proposed criteria are demonstrated through two numerical examples.

  15. Synchronization and State Estimation of a Class of Hierarchical Hybrid Neural Networks With Time-Varying Delays.

    PubMed

    Zhang, Lixian; Zhu, Yanzheng; Zheng, Wei Xing

    2016-02-01

    This paper addresses the problems of synchronization and state estimation for a class of discrete-time hierarchical hybrid neural networks (NNs) with time-varying delays. The hierarchical hybrid feature consists of a higher level nondeterministic switching and a lower level stochastic switching. The latter is used to describe the NNs subject to Markovian modes transitions, whereas the former is of the average dwell-time switching regularity to model the supervisory orchestrating mechanism among these Markov jump NNs. The considered time delays are not only time-varying but also dependent on the mode of NNs on the lower layer in the hierarchical structure. Despite quantization and random data missing, the synchronized controllers and state estimators are designed such that the resulting error system is exponentially stable with an expected decay rate and has a prescribed H∞ disturbance attenuation level. Two numerical examples are provided to show the validity and potential of the developed results.

  16. On antiperiodic solutions for Cohen-Grossberg shunting inhibitory neural networks with time-varying delays and impulses.

    PubMed

    Xu, Changjin; Zhang, Qiming

    2014-10-01

    In this letter, a class of Cohen-Grossberg shunting inhibitory neural networks with time-varying delays and impulses is investigated. Sufficient conditions for the existence and exponential stability of antiperiodic solutions of such a class of neural networks are established. Our results are new and complementary to previously known results. An example is given to illustrate the feasibility and effectiveness of our main results.

  17. DDI-based finite-time stability analysis for nonlinear switched systems with time-varying delays

    NASA Astrophysics Data System (ADS)

    Xue, Wenping; Li, Kangji; Liu, Guohai

    2016-09-01

    This paper investigates the finite-time stability (FTS) analysis problem for switched systems with both nonlinear perturbation and time-varying delays. For the system to be finite-time stable, a sufficient condition is proposed based on some delay differential inequalities (DDIs), rather than the Lyapunov-like functions which are commonly used in the FTS analysis of switched systems. Compared with the Lyapunov-like function method, the FTS conditions based on the DDI method are easier for checking and do not require FTS of each subsystem. Two examples are given to illustrate the effectiveness of the developed theory.

  18. Synchronization analysis of delayed complex networks with time-varying couplings

    NASA Astrophysics Data System (ADS)

    Li, Ping; Yi, Zhang

    2008-06-01

    In this paper, a new method is presented to analyze the linear stability of the synchronized state in arbitrarily coupled complex dynamical systems with time delays. The coupling configurations are not restricted to the symmetric and irreducible connections or the non-negative off-diagonal links. The stability criteria are obtained by using Lyapunov-Krasovskii functional method and subspace projection method. These criteria reveal the relationship between coupling matrices and stability of the dynamical networks.

  19. An Improved Integral Inequality to Stability Analysis of Genetic Regulatory Networks With Interval Time-Varying Delays.

    PubMed

    Zhang, Xian; Wu, Ligang; Cui, Shaochun

    2015-01-01

    This paper focuses on stability analysis for a class of genetic regulatory networks with interval time-varying delays. An improved integral inequality concerning on double-integral items is first established. Then, we use the improved integral inequality to deal with the resultant double-integral items in the derivative of the involved Lyapunov-Krasovskii functional. As a result, a delay-range-dependent and delay-rate-dependent asymptotical stability criterion is established for genetic regulatory networks with differential time-varying delays. Furthermore, it is theoretically proven that the stability criterion proposed here is less conservative than the corresponding one in [Neurocomputing, 2012, 93: 19-26]. Based on the obtained result, another stability criterion is given under the case that the information of the derivatives of delays is unknown. Finally, the effectiveness of the approach proposed in this paper is illustrated by a pair of numerical examples which give the comparisons of stability criteria proposed in this paper and some literature.

  20. Non-predictor control of a class of feedforward nonlinear systems with unknown time-varying delays

    NASA Astrophysics Data System (ADS)

    Koo, Min-Sung; Choi, Ho-Lim

    2016-08-01

    This paper generalises the several recent results on the control of feedforward time-delay nonlinear systems. First, in view of system formulation, there are unknown time-varying delays in both states and main control input. Also, the considered nonlinear system has extended feedforward nonlinearities. Second, in view of control solution, our proposed controller is a non-predictor feedback controller whereas smith-predictor type controllers are used in the several existing results. Moreover, our controller does not need any information on the unknown delays except their upper bounds. Thus, our result has certain merits in both system formulation and control solution perspective. The analysis and example are given for clear illustration.

  1. Delay Analysis of Max-Weight Queue Algorithm for Time-Varying Wireless Ad hoc Networks—Control Theoretical Approach

    NASA Astrophysics Data System (ADS)

    Chen, Junting; Lau, Vincent K. N.

    2013-01-01

    Max weighted queue (MWQ) control policy is a widely used cross-layer control policy that achieves queue stability and a reasonable delay performance. In most of the existing literature, it is assumed that optimal MWQ policy can be obtained instantaneously at every time slot. However, this assumption may be unrealistic in time varying wireless systems, especially when there is no closed-form MWQ solution and iterative algorithms have to be applied to obtain the optimal solution. This paper investigates the convergence behavior and the queue delay performance of the conventional MWQ iterations in which the channel state information (CSI) and queue state information (QSI) are changing in a similar timescale as the algorithm iterations. Our results are established by studying the stochastic stability of an equivalent virtual stochastic dynamic system (VSDS), and an extended Foster-Lyapunov criteria is applied for the stability analysis. We derive a closed form delay bound of the wireless network in terms of the CSI fading rate and the sensitivity of MWQ policy over CSI and QSI. Based on the equivalent VSDS, we propose a novel MWQ iterative algorithm with compensation to improve the tracking performance. We demonstrate that under some mild conditions, the proposed modified MWQ algorithm converges to the optimal MWQ control despite the time-varying CSI and QSI.

  2. Matrix measure method for global exponential stability of complex-valued recurrent neural networks with time-varying delays.

    PubMed

    Gong, Weiqiang; Liang, Jinling; Cao, Jinde

    2015-10-01

    In this paper, based on the matrix measure method and the Halanay inequality, global exponential stability problem is investigated for the complex-valued recurrent neural networks with time-varying delays. Without constructing any Lyapunov functions, several sufficient criteria are obtained to ascertain the global exponential stability of the addressed complex-valued neural networks under different activation functions. Here, the activation functions are no longer assumed to be derivative which is always demanded in relating references. In addition, the obtained results are easy to be verified and implemented in practice. Finally, two examples are given to illustrate the effectiveness of the obtained results.

  3. Exponential Stabilization of Memristor-based Chaotic Neural Networks with Time-Varying Delays via Intermittent Control.

    PubMed

    Zhang, Guodong; Shen, Yi

    2015-07-01

    This paper is concerned with the global exponential stabilization of memristor-based chaotic neural networks with both time-varying delays and general activation functions. Here, we adopt nonsmooth analysis and control theory to handle memristor-based chaotic neural networks with discontinuous right-hand side. In particular, several new sufficient conditions ensuring exponential stabilization of memristor-based chaotic neural networks are obtained via periodically intermittent control. In addition, the proposed results here are easy to verify and they also extend the earlier publications. Finally, numerical simulations illustrate the effectiveness of the obtained results.

  4. Further results for global exponential stability of stochastic memristor-based neural networks with time-varying delays

    NASA Astrophysics Data System (ADS)

    Zhong, Kai; Zhu, Song; Yang, Qiqi

    2016-11-01

    In recent years, the stability problems of memristor-based neural networks have been studied extensively. This paper not only takes the unavoidable noise into consideration but also investigates the global exponential stability of stochastic memristor-based neural networks with time-varying delays. The obtained criteria are essentially new and complement previously known ones, which can be easily validated with the parameters of system itself. In addition, the study of the nonlinear dynamics for the addressed neural networks may be helpful in qualitative analysis for general stochastic systems. Finally, two numerical examples are provided to substantiate our results.

  5. Time varying feedbacks and coevolution of alluvial channel morphology, flow distribution and vegetation.

    NASA Astrophysics Data System (ADS)

    Rodriguez, Jose F.; Bayat, Esmaeel; Vahidi, Elham; de Almeida, Gustavo; Gorrick, Sam

    2016-04-01

    Alluvial channel dynamics is the result of the coevolution of channel morphology, flow distribution and vegetation. Even though these processes interact on a variety of time and spatial scales, local detailed analysis can provide valuable insights on mechanisms and feedbacks that can affect the long-term evolution of the system. The three-dimensional, time varying flow distribution can be considered the main driving force, but is affected by the channel geometry as a result of stream curvature, stream width changes and in-stream topographic steering. In-stream vegetation also affects flow distribution in a similar way, either reinforcing or attenuating geometric forcing. But as these systems are the result of coevolution, flow patterns in turn affect sediment transport fluxes, erosion and deposition which eventually modify some aspects of the topography, sediment size distribution and vegetative cover. This contribution presents different studies in which a variety of situations are covered, where the interplay and feedbacks between flow mechanisms are different. We analyse the effects of curvature, width changes and bedform and vegetation steering on sediment transport and sorting and the resulting changes in flow patterns. We study how three-dimensional flow patterns are stage dependent and how that impacts sediment transport and vegetation distribution. We also analyse self-maintenance feedbacks of flow-related features under different time-varying flow conditions. We present cases of straight and meandering reaches, reaches with pools and riffles, and reaches with riparian vegetation within a common framework. We cover both gravel-bed and sand-bed streams.

  6. Time Varying Apparent Volume of Distribution and Drug Half-Lives Following Intravenous Bolus Injections

    PubMed Central

    Wesolowski, Carl A.; Wesolowski, Michal J.; Babyn, Paul S.

    2016-01-01

    We present a model that generalizes the apparent volume of distribution and half-life as functions of time following intravenous bolus injection. This generalized model defines a time varying apparent volume of drug distribution. The half-lives of drug remaining in the body vary in time and become longer as time elapses, eventually converging to the terminal half-life. Two example fit models were substituted into the general model: biexponential models from the least relative concentration error, and gamma variate models using adaptive regularization for least relative error of clearance. Using adult population parameters from 41 studies of the renal glomerular filtration marker 169Yb-DTPA, simulations of extracellular fluid volumes of 5, 10, 15 and 20 litres and plasma clearances of 40 and 100 ml/min were obtained. Of these models, the adaptively obtained gamma variate models had longer times to 95% of terminal volume and longer half-lives. PMID:27403663

  7. Position and force tracking in nonlinear teleoperation systems with sandwich linearity in actuators and time-varying delay

    NASA Astrophysics Data System (ADS)

    Ganjefar, Soheil; Rezaei, Sara; Hashemzadeh, Farzad

    2017-03-01

    In this paper, a new bounded force feedback control law is proposed to guarantee position and force tracking in nonlinear teleoperation systems in the presence of passive and nonpassive input interaction forces, time varying delay in their communication channels and sandwich linearity in their actuators. The proposed control is a nonlinear-proportional plus nonlinear damping (nP+nD) controller with the addition of a nonlinear function of the environment force on the slave side and nonlinear function of the human force and force error on the master side, the transparency of the proposed scheme will be improved. The controller prevents the inputs from reaching their usual actuator bounds. Using a novel Lyapunov-Krasovskii functional, the asymptotic stability and tracking performance of the teleoperation system are established under some conditions on the controller parameters, actuator saturation characteristics and maximum allowable time delays.

  8. Multistability of neural networks with discontinuous non-monotonic piecewise linear activation functions and time-varying delays.

    PubMed

    Nie, Xiaobing; Zheng, Wei Xing

    2015-05-01

    This paper is concerned with the problem of coexistence and dynamical behaviors of multiple equilibrium points for neural networks with discontinuous non-monotonic piecewise linear activation functions and time-varying delays. The fixed point theorem and other analytical tools are used to develop certain sufficient conditions that ensure that the n-dimensional discontinuous neural networks with time-varying delays can have at least 5(n) equilibrium points, 3(n) of which are locally stable and the others are unstable. The importance of the derived results is that it reveals that the discontinuous neural networks can have greater storage capacity than the continuous ones. Moreover, different from the existing results on multistability of neural networks with discontinuous activation functions, the 3(n) locally stable equilibrium points obtained in this paper are located in not only saturated regions, but also unsaturated regions, due to the non-monotonic structure of discontinuous activation functions. A numerical simulation study is conducted to illustrate and support the derived theoretical results.

  9. State Estimation for Static Neural Networks With Time-Varying Delays Based on an Improved Reciprocally Convex Inequality.

    PubMed

    Zhang, Xian-Ming; Han, Qing-Long

    2017-02-16

    This brief is concerned with the problem of neural state estimation for static neural networks with time-varying delays. Notice that a Luenberger estimator can produce an estimation error irrespective of the neuron state trajectory. This brief provides a method for designing such an estimator for static neural networks with time-varying delays. First, in-depth analysis on a well-used reciprocally convex approach is made, leading to an improved reciprocally convex inequality. Second, the improved reciprocally convex inequality and some integral inequalities are employed to provide a tight upper bound on the time-derivative of some Lyapunov-Krasovskii functional. As a result, a novel bounded real lemma (BRL) for the resultant error system is derived. Third, the BRL is applied to present a method for designing suitable Luenberger estimators in terms of solutions of linear matrix inequalities with two tuning parameters. Finally, it is shown through a numerical example that the proposed method can derive less conservative results than some existing ones.

  10. Existence and stability of pseudo almost periodic solutions for shunting inhibitory cellular neural networks with neutral type delays and time-varying leakage delays.

    PubMed

    Xu, Changjin; Zhang, Qiming; Wu, Yusen

    2014-01-01

    In this paper, shunting inhibitory cellular neural networks(SICNNs) with neutral type delays and time-varying leakage delays are investigated. By applying Lyapunov functional method and differential inequality techniques, a set of sufficient conditions are obtained for the existence and exponential stability of pseudo almost periodic solutions of the model. An example is given to support the theoretical findings. Our results improve and generalize those of the previous studies.

  11. Input-output method to fault detection for discrete-time fuzzy networked systems with time-varying delay and multiple packet losses

    NASA Astrophysics Data System (ADS)

    Wang, Shenquan; Feng, Jian; Jiang, Yulian

    2016-05-01

    The fault detection (FD) problem for discrete-time fuzzy networked systems with time-varying delay and multiple packet losses is investigated in this paper. The communication links between the plant and the FD filter (FDF) are assumed to be imperfect, and the missing probability is governed by an individual random variable satisfying a certain probabilistic distribution over the interval [0 1]. The discrete-time delayed fuzzy networked system is first transformed into the form of interconnect ion of two subsystems by applying an input-output method and a two-term approximation approach, which are employed to approximate the time-varying delay. Our attention is focused on the design of fuzzy FDF (FFDF) such that, for all data missing conditions, the overall FD dynamics are input-output stable in mean square and preserves a guaranteed performance. Sufficient conditions are first established via H∞ performance analysis for the existence of the desired FFDF; meanwhile, the corresponding solvability conditions for the desired FFDF gains are characterised in terms of the feasibility of a convex optimisation problem. Moreover, we show that the obtained criteria based on the input-output approach can also be established by applying the direct Lyapunov method to the original time-delay systems. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed approaches.

  12. Neural networks-based adaptive control for nonlinear time-varying delays systems with unknown control direction.

    PubMed

    Wen, Yuntong; Ren, Xuemei

    2011-10-01

    This paper investigates a neural network (NN) state observer-based adaptive control for a class of time-varying delays nonlinear systems with unknown control direction. An adaptive neural memoryless observer, in which the knowledge of time-delay is not used, is designed to estimate the system states. Furthermore, by applying the property of the function tanh(2)(ϑ/ε)/ϑ (the function can be defined at ϑ = 0) and introducing a novel type appropriate Lyapunov-Krasovskii functional, an adaptive output feedback controller is constructed via backstepping method which can efficiently avoid the problem of controller singularity and compensate for the time-delay. It is highly proven that the closed-loop systems controller designed by the NN-basis function property, new kind parameter adaptive law and Nussbaum function in detecting the control direction is able to guarantee the semi-global uniform ultimate boundedness of all signals and the tracking error can converge to a small neighborhood of zero. The characteristic of the proposed approach is that it relaxes any restrictive assumptions of Lipschitz condition for the unknown nonlinear continuous functions. And the proposed scheme is suitable for the systems with mismatching conditions and unmeasurable states. Finally, two simulation examples are given to illustrate the effectiveness and applicability of the proposed approach.

  13. Nonlinear Reduced-Order Analysis with Time-Varying Spatial Loading Distributions

    NASA Technical Reports Server (NTRS)

    Prezekop, Adam

    2008-01-01

    Oscillating shocks acting in combination with high-intensity acoustic loadings present a challenge to the design of resilient hypersonic flight vehicle structures. This paper addresses some features of this loading condition and certain aspects of a nonlinear reduced-order analysis with emphasis on system identification leading to formation of a robust modal basis. The nonlinear dynamic response of a composite structure subject to the simultaneous action of locally strong oscillating pressure gradients and high-intensity acoustic loadings is considered. The reduced-order analysis used in this work has been previously demonstrated to be both computationally efficient and accurate for time-invariant spatial loading distributions, provided that an appropriate modal basis is used. The challenge of the present study is to identify a suitable basis for loadings with time-varying spatial distributions. Using a proper orthogonal decomposition and modal expansion, it is shown that such a basis can be developed. The basis is made more robust by incrementally expanding it to account for changes in the location, frequency and span of the oscillating pressure gradient.

  14. Consensus with guaranteed convergence rate of high-order integrator agents in the presence of time-varying delays

    NASA Astrophysics Data System (ADS)

    Savino, H. J.; Souza, F. O.; Pimenta, L. C. A.

    2016-07-01

    This paper aims to study the consensus problem in directed networks of agents with high-order integrator dynamics and fixed topology. It is considered the existence of non-uniform time-varying delays in the agents control laws for each interaction between agents and their neighbours. Based on Lyapunov-Krasovskii stability theory and algebraic graph theory, sufficient conditions, in terms of linear matrix inequalities, are given to verify if consensus is achieved with guaranteed exponential convergence rate. The efficiency of the proposed method is verified by numerical simulations. The simulations reveal that the conditions established in this work outperformed the similar existing ones in all numerical tests accomplished in this paper.

  15. Existence and global exponential stability of periodic solution of memristor-based BAM neural networks with time-varying delays.

    PubMed

    Li, Hongfei; Jiang, Haijun; Hu, Cheng

    2016-03-01

    In this paper, we investigate a class of memristor-based BAM neural networks with time-varying delays. Under the framework of Filippov solutions, boundedness and ultimate boundedness of solutions of memristor-based BAM neural networks are guaranteed by Chain rule and inequalities technique. Moreover, a new method involving Yoshizawa-like theorem is favorably employed to acquire the existence of periodic solution. By applying the theory of set-valued maps and functional differential inclusions, an available Lyapunov functional and some new testable algebraic criteria are derived for ensuring the uniqueness and global exponential stability of periodic solution of memristor-based BAM neural networks. The obtained results expand and complement some previous work on memristor-based BAM neural networks. Finally, a numerical example is provided to show the applicability and effectiveness of our theoretical results.

  16. Well-posedness and exponential stability for a plate equation with time-varying delay and past history

    NASA Astrophysics Data System (ADS)

    Feng, Baowei

    2017-02-01

    This paper is concerned with a class of plate equation with past history and time-varying delay in the internal feedback u_{tt}+α Δ ^2 u-int limits ^t_{-∞}g(t-s)Δ ^2 u(s)ds+μ _1u_t+μ _2u_t(t-τ (t))+f(u)=h(x), defined in a bounded domain of {R}^n (n≥1) with some suitable initial data and boundary conditions. For arbitrary real numbers μ _1 and μ _2, we proved the global well-posedness of the problem. Results on stability of energy are also proved under some restrictions on μ _1, μ _2 and h(x)=0.

  17. On the periodic dynamics of a class of time-varying delayed neural networks via differential inclusions.

    PubMed

    Cai, Zuowei; Huang, Lihong; Guo, Zhenyuan; Chen, Xiaoyan

    2012-09-01

    This paper investigates the periodic dynamics of a general class of time-varying delayed neural networks with discontinuous right-hand sides. By employing the topological degree theory in set-valued analysis, differential inclusions theory and Lyapunov-like approach, we perform a thorough analysis of the existence, uniqueness and global exponential stability of the periodic solution for the neural networks. Especially, some sufficient conditions are derived to guarantee the existence, uniqueness and global exponential stability of the equilibrium point for the autonomous systems corresponding to the non-autonomous neural networks. Furthermore, the global convergence of the output and the convergence in finite time of the state are also discussed. Without assuming the boundedness or monotonicity of the discontinuous neuron activation functions, the obtained results improve and extend previous works on discontinuous or continuous neural network dynamical systems. Finally, two numerical examples are provided to show the applicability and effectiveness of our main results.

  18. Recurrent-Neural-Network-Based Multivariable Adaptive Control for a Class of Nonlinear Dynamic Systems With Time-Varying Delay.

    PubMed

    Hwang, Chih-Lyang; Jan, Chau

    2016-02-01

    At the beginning, an approximate nonlinear autoregressive moving average (NARMA) model is employed to represent a class of multivariable nonlinear dynamic systems with time-varying delay. It is known that the disadvantages of robust control for the NARMA model are as follows: 1) suitable control parameters for larger time delay are more sensitive to achieving desirable performance; 2) it only deals with bounded uncertainty; and 3) the nominal NARMA model must be learned in advance. Due to the dynamic feature of the NARMA model, a recurrent neural network (RNN) is online applied to learn it. However, the system performance becomes deteriorated due to the poor learning of the larger variation of system vector functions. In this situation, a simple network is employed to compensate the upper bound of the residue caused by the linear parameterization of the approximation error of RNN. An e -modification learning law with a projection for weight matrix is applied to guarantee its boundedness without persistent excitation. Under suitable conditions, the semiglobally ultimately bounded tracking with the boundedness of estimated weight matrix is obtained by the proposed RNN-based multivariable adaptive control. Finally, simulations are presented to verify the effectiveness and robustness of the proposed control.

  19. Distributed Consensus Optimization in Multiagent Networks With Time-Varying Directed Topologies and Quantized Communication.

    PubMed

    Li, Huaqing; Huang, Chicheng; Chen, Guo; Liao, Xiaofeng; Huang, Tingwen

    2017-03-31

    This paper considers solving a class of optimization problems which are modeled as the sum of all agents' convex cost functions and each agent is only accessible to its individual function. Communication between agents in multiagent networks is assumed to be limited: each agent can only interact information with its neighbors by using time-varying communication channels with limited capacities. A technique which overcomes the limitation is to implement a quantization process to the interacted information. The quantized information is first encoded as a binary sequence at the side of each agent before sending. After the binary sequence is received by the neighboring agent, corresponding decoding scheme is utilized to resume the original information with a certain degree of error which is caused by the quantization process. With the availability of each agent's encoding states (associated with its out-channels) and decoding states (associated with its in-channels), we devise a set of distributed optimization algorithms that generate two iterative sequences, one of which converges to the optimal solution and the other of which reaches to the optimal value. We prove that if the parameters satisfy some mild conditions, the quantization errors are bounded and the consensus optimization can be achieved. How to minimize the number of quantization level of each connected communication channel in fixed networks is also explored thoroughly. It is found that, by properly choosing system parameters, one bit information exchange suffices to ensure consensus optimization. Finally, we present two numerical simulation experiments to illustrate the efficacy of the algorithms as well as to validate the theoretical findings.

  20. Adaptive Control of Semi-Autonomous Teleoperation System With Asymmetric Time-Varying Delays and Input Uncertainties.

    PubMed

    Zhai, Di-Hua; Xia, Yuanqing

    2016-06-07

    This paper addresses the adaptive task-space bilateral teleoperation for heterogeneous master and slave robots to guarantee stability and tracking performance, where a novel semi-autonomous teleoperation framework is developed to ensure the safety and enhance the efficiency of the robot in remote site. The basic idea is to stabilize the tracking error in task space while enhancing the efficiency of complex teleoperation by using redundant slave robot with subtask control. To unify the study of the asymmetric time-varying delays, passive/nonpassive exogenous forces, dynamic parameter uncertainties and dead-zone input in the same framework, a novel switching technique-based adaptive control scheme is investigated, where a special switched error filter is developed. By replacing the derivatives of position errors with their filtered outputs in the coordinate torque design, and employing the multiple Lyapunov-Krasovskii functionals method, the complete closed-loop master (slave) system is proven to be state-independent input-to-output stable. It is shown that both the position tracking errors in task space and the adaptive parameter estimation errors remain bounded for any bounded exogenous forces. Moreover, by using the redundancy of the slave robot, the proposed teleoperation framework can autonomously achieve additional subtasks in the remote environment. Finally, the obtained results are demonstrated by the simulation.

  1. Analysis of global O(t(-α)) stability and global asymptotical periodicity for a class of fractional-order complex-valued neural networks with time varying delays.

    PubMed

    Rakkiyappan, R; Sivaranjani, R; Velmurugan, G; Cao, Jinde

    2016-05-01

    In this paper, the problem of the global O(t(-α)) stability and global asymptotic periodicity for a class of fractional-order complex-valued neural networks (FCVNNs) with time varying delays is investigated. By constructing suitable Lyapunov functionals and a Leibniz rule for fractional differentiation, some new sufficient conditions are established to ensure that the addressed FCVNNs are globally O(t(-α)) stable. Moreover, some sufficient conditions for the global asymptotic periodicity of the addressed FCVNNs with time varying delays are derived, showing that all solutions converge to the same periodic function. Finally, numerical examples are given to demonstrate the effectiveness and usefulness of our theoretical results.

  2. M-matrix based robust stability and stabilization for uncertain discrete-time switched TS fuzzy systems with time-varying delays.

    PubMed

    Jaballi, Ahmed; Sakly, Anis; Hajjaji, Ahmed El

    2016-07-01

    This paper provides novel sufficient conditions on robust asymptotic stability and stabilization for a class of uncertain discrete-time switched fuzzy with time-varying delays. The attention is focused on developing new algebraic criteria to break with classical criteria in terms of Linear Matrix Inequalities (LMIs). Firstly, based on the M-matrix proprieties and through l1,∞ induced norms notion, new delay-dependent sufficient conditions are derived to ensure the asymptotic stability and stabilization for a class of uncertain discrete-time switched fuzzy systems with time-varying delay. Secondly, these results are extended for a class of uncertain discrete-time switched fuzzy systems with time delays, modeled by difference equations. Finally, two numerical examples and practical example (a robot arm) are provided to demonstrate the advantage and the effectiveness of our results.

  3. The time-varying electron energy distribution function in the plume of a Hall thruster

    NASA Astrophysics Data System (ADS)

    Dannenmayer, K.; Mazouffre, S.; Kudrna, P.; Tichý, M.

    2014-12-01

    Time-resolved Langmuir probe measurements have been performed in the plume of the 1.5 kW class PPS®1350-ML Hall thruster. The time-dependent electron energy distribution function (EEDF) has been inferred from the probe current-voltage characteristic curves obtained after active stabilization of the discharge. The distribution function changes in the course of time at the breathing oscillation frequency (13.8 kHz). The EEDF is Maxwellian with a depleted tail above the xenon ionization energy whatever the location and the time. The electron density and temperature computed from the EEDF also oscillate at the breathing mode frequency. Experimental outcomes indicate the existence of a low-frequency plasma wave that propagates axially. The wave front speed (2700 m s-1) was found to be compatible with the ion acoustic speed (2300 m s-1).

  4. Modeling hyporheic exchange and in-stream transport with time-varying transit time distributions

    NASA Astrophysics Data System (ADS)

    Ball, A.; Harman, C. J.; Ward, A. S.

    2014-12-01

    Transit time distributions (TTD) are used to understand in-stream transport and exchange with the hyporheic zone by quantifying the probability of water (and of dissolved material) taking time T to traverse the stream reach control volume. However, many studies using this method assume a TTD that is time-invariant, despite the time-variability of the streamflow. Others assume that storage is 'randomly sampled' or 'well-mixed' with a fixed volume or fixed exchange rate. Here we present a formulation for a time-variable TTD that relaxes both the time-invariant and 'randomly sampled' assumptions and only requires a few parameters. The framework is applied to transient storage, representing some combination of in-stream and hyporheic storage, along a stream reach. This approach does not assume that hyporheic and dead-zone storage is fixed or temporally-invariant, and allows for these stores to be sampled in more physically representative ways determined by the system itself. Instead of using probability distributions of age, probability distributions of storage (ranked by age) called Ω functions are used to describe how the off-stream storage is sampled in the outflow. Here the Ω function approach is used to describe hyporheic exchange during diurnal fluctuations in streamflow in a gaining reach of the H.J. Andrews Experimental Forest. The breakthrough curves of salt slugs injected four hours apart over a 28-hour period show a systematic variation in transit time distribution. This new approach allows us to relate these salt slug TTDs to a corresponding time-variation in the Ω function, which can then be related to changes in in-stream storage and hyporheic zone mobilization under varying flow conditions. Thus, we can gain insights into how channel storage and hyporheic exchange are changing through time without having to specify difficult to measure or unmeasurable quantities of our system, such as total storage.

  5. Finite-Time Stability Analysis of Reaction-Diffusion Genetic Regulatory Networks with Time-Varying Delays.

    PubMed

    Fan, Xiaofei; Zhang, Xian; Wu, Ligang; Shi, Michael

    2016-04-11

    This paper is concerned with the finite-time stability problem of the delayed genetic regulatory networks (GRNs) with reaction-diffusion terms under Dirichlet boundary conditions. By constructing a Lyapunov-Krasovskii functional including quad- slope integrations, we establish delay-dependent finite-time stabil- ity criteria by employing the Wirtinger-type integral inequality, Gronwall inequality, convex technique, and reciprocally convex technique. In addition, the obtained criteria are also reaction- diffusion-dependent. Finally, a numerical example is provided to illustrate the effectiveness of the theoretical results.

  6. Event-based state estimation for a class of complex networks with time-varying delays: A comparison principle approach

    NASA Astrophysics Data System (ADS)

    Zhang, Wenbing; Wang, Zidong; Liu, Yurong; Ding, Derui; Alsaadi, Fuad E.

    2017-01-01

    The paper is concerned with the state estimation problem for a class of time-delayed complex networks with event-triggering communication protocol. A novel event generator function, which is dependent not only on the measurement output but also on a predefined positive constant, is proposed with hope to reduce the communication burden. A new concept of exponentially ultimate boundedness is provided to quantify the estimation performance. By means of the comparison principle, some sufficient conditions are obtained to guarantee that the estimation error is exponentially ultimately bounded, and then the estimator gains are obtained in terms of the solution of certain matrix inequalities. Furthermore, a rigorous proof is proposed to show that the designed triggering condition is free of the Zeno behavior. Finally, a numerical example is given to illustrate the effectiveness of the proposed event-based estimator.

  7. Neural-adaptive control of single-master-multiple-slaves teleoperation for coordinated multiple mobile manipulators with time-varying communication delays and input uncertainties.

    PubMed

    Li, Zhijun; Su, Chun-Yi

    2013-09-01

    In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies.

  8. Existence and global exponential stability of almost periodic solution for cellular neural networks with variable coefficients and time-varying delays.

    PubMed

    Jiang, Haijun; Zhang, Long; Teng, Zhidong

    2005-11-01

    In this paper, we study cellular neural networks with almost periodic variable coefficients and time-varying delays. By using the existence theorem of almost periodic solution for general functional differential equations, introducing many real parameters and applying the Lyapunov functional method and the technique of Young inequality, we obtain some sufficient conditions to ensure the existence, uniqueness, and global exponential stability of almost periodic solution. The results obtained in this paper are new, useful, and extend and improve the existing ones in previous literature.

  9. State Estimation for Discrete-Time Dynamical Networks With Time-Varying Delays and Stochastic Disturbances Under the Round-Robin Protocol.

    PubMed

    Zou, Lei; Wang, Zidong; Gao, Huijun; Liu, Xiaohui

    2016-02-19

    This paper is concerned with the state estimation problem for a class of nonlinear dynamical networks with time-varying delays subject to the round-robin protocol. The communication between the state estimator and the nodes of the dynamical networks is implemented through a shared constrained network, in which only one node is allowed to send data at each time instant. The round-robin protocol is utilized to orchestrate the transmission order of nodes. By using a switch-based approach, the dynamics of the estimation error is modeled by a periodic parameter-switching system with time-varying delays. The purpose of the problem addressed is to design an estimator, such that the estimation error is exponentially ultimately bounded with a certain asymptotic upper bound in mean square subject to the process noise and exogenous disturbance. Furthermore, such a bound is subsequently minimized by the designed estimator parameters. A novel Lyapunov-like functional is employed to deal with the dynamics analysis issue of the estimation error. Sufficient conditions are established to guarantee the ultimate boundedness of the estimation error in mean square by applying the stochastic analysis approach. Then, the desired estimator gains are characterized by solving a convex problem. Finally, a numerical example is given to illustrate the effectiveness of the estimator design scheme.

  10. Stochastic sampled-data control for synchronization of complex dynamical networks with control packet loss and additive time-varying delays.

    PubMed

    Rakkiyappan, R; Sakthivel, N; Cao, Jinde

    2015-06-01

    This study examines the exponential synchronization of complex dynamical networks with control packet loss and additive time-varying delays. Additionally, sampled-data controller with time-varying sampling period is considered and is assumed to switch between m different values in a random way with given probability. Then, a novel Lyapunov-Krasovskii functional (LKF) with triple integral terms is constructed and by using Jensen's inequality and reciprocally convex approach, sufficient conditions under which the dynamical network is exponentially mean-square stable are derived. When applying Jensen's inequality to partition double integral terms in the derivation of linear matrix inequality (LMI) conditions, a new kind of linear combination of positive functions weighted by the inverses of squared convex parameters appears. In order to handle such a combination, an effective method is introduced by extending the lower bound lemma. To design the sampled-data controller, the synchronization error system is represented as a switched system. Based on the derived LMI conditions and average dwell-time method, sufficient conditions for the synchronization of switched error system are derived in terms of LMIs. Finally, numerical example is employed to show the effectiveness of the proposed methods.

  11. Multistability of memristive Cohen-Grossberg neural networks with non-monotonic piecewise linear activation functions and time-varying delays.

    PubMed

    Nie, Xiaobing; Zheng, Wei Xing; Cao, Jinde

    2015-11-01

    The problem of coexistence and dynamical behaviors of multiple equilibrium points is addressed for a class of memristive Cohen-Grossberg neural networks with non-monotonic piecewise linear activation functions and time-varying delays. By virtue of the fixed point theorem, nonsmooth analysis theory and other analytical tools, some sufficient conditions are established to guarantee that such n-dimensional memristive Cohen-Grossberg neural networks can have 5(n) equilibrium points, among which 3(n) equilibrium points are locally exponentially stable. It is shown that greater storage capacity can be achieved by neural networks with the non-monotonic activation functions introduced herein than the ones with Mexican-hat-type activation function. In addition, unlike most existing multistability results of neural networks with monotonic activation functions, those obtained 3(n) locally stable equilibrium points are located both in saturated regions and unsaturated regions. The theoretical findings are verified by an illustrative example with computer simulations.

  12. Coexistence and local μ-stability of multiple equilibrium points for memristive neural networks with nonmonotonic piecewise linear activation functions and unbounded time-varying delays.

    PubMed

    Nie, Xiaobing; Zheng, Wei Xing; Cao, Jinde

    2016-12-01

    In this paper, the coexistence and dynamical behaviors of multiple equilibrium points are discussed for a class of memristive neural networks (MNNs) with unbounded time-varying delays and nonmonotonic piecewise linear activation functions. By means of the fixed point theorem, nonsmooth analysis theory and rigorous mathematical analysis, it is proven that under some conditions, such n-neuron MNNs can have 5(n) equilibrium points located in ℜ(n), and 3(n) of them are locally μ-stable. As a direct application, some criteria are also obtained on the multiple exponential stability, multiple power stability, multiple log-stability and multiple log-log-stability. All these results reveal that the addressed neural networks with activation functions introduced in this paper can generate greater storage capacity than the ones with Mexican-hat-type activation function. Numerical simulations are presented to substantiate the theoretical results.

  13. Global O(t(-α)) stability and global asymptotical periodicity for a non-autonomous fractional-order neural networks with time-varying delays.

    PubMed

    Chen, Boshan; Chen, Jiejie

    2016-01-01

    The present paper studies global O(t(-α)) stability and global asymptotical periodicity for a non-autonomous fractional-order neural networks with time-varying delays (FDNN). Firstly, some sufficient conditions are established to ensure that a non-autonomous FDNN is global O(t(-α)) stable based on a new Lyapunov function method and Leibniz rule for fractional differentiation. Next it is shown that the periodic or autonomous FDNN cannot generate exactly nonconstant periodic solution under any circumstances. Finally, we show that all solutions converge to a same periodic function for a periodic FDNN by using a fractional-order differential inequality technique. Our issues, methods and results are all new.

  14. Adaptive fuzzy decentralized control for large-scale nonlinear systems with time-varying delays and unknown high-frequency gain sign.

    PubMed

    Tong, Shaocheng; Liu, Changliang; Li, Yongming; Zhang, Huaguang

    2011-04-01

    In this paper, an adaptive fuzzy decentralized robust output feedback control approach is proposed for a class of large-scale strict-feedback nonlinear systems without the measurements of the states. The nonlinear systems in this paper are assumed to possess unstructured uncertainties, time-varying delays, and unknown high-frequency gain sign. Fuzzy logic systems are used to approximate the unstructured uncertainties, K-filters are designed to estimate the unmeasured states, and a special Nussbaum gain function is introduced to solve the problem of unknown high-frequency gain sign. Combining the backstepping technique with adaptive fuzzy control theory, an adaptive fuzzy decentralized robust output feedback control scheme is developed. In order to obtain the stability of the closed-loop system, a new lemma is given and proved. Based on this lemma and Lyapunov-Krasovskii functions, it is proved that all the signals in the closed-loop system are uniformly ultimately bounded and that the tracking errors can converge to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated from simulation results.

  15. Distributed finite-time consensus tracking for nonlinear multi-agent systems with a time-varying reference state

    NASA Astrophysics Data System (ADS)

    Wen, Guoguang; Yu, Yongguang; Peng, Zhaoxia; Rahmani, Ahmed

    2016-06-01

    This paper investigates the consensus tracking problem for nonlinear multi-agent systems with a time-varying reference state. The consensus reference is taken as a virtual leader, whose output is only its position information that is available to only a subset of a group of followers. The dynamics of each follower consists of two terms: nonlinear inherent dynamics and a simple communication protocol relying only on the position of its neighbours. In this paper, the consensus tracking problem is respectively considered under fixed and switching communication topologies. Some corresponding sufficient conditions are obtained to guarantee the states of followers can converge to the state of the virtual leader in finite time. Rigorous proofs are given by using graph theory, matrix theory, and Lyapunov theory. Simulations are presented to illustrate the theoretical analysis.

  16. Theoretical Delay Time Distributions

    NASA Astrophysics Data System (ADS)

    Nelemans, Gijs; Toonen, Silvia; Bours, Madelon

    2013-01-01

    We briefly discuss the method of population synthesis to calculate theoretical delay time distributions of Type Ia supernova progenitors. We also compare the results of different research groups and conclude that, although one of the main differences in the results for single degenerate progenitors is the retention efficiency with which accreted hydrogen is added to the white dwarf core, this alone cannot explain all the differences.

  17. Time Varying Feature Data

    NASA Astrophysics Data System (ADS)

    Echterhoff, J.; Simonis, I.; Atkinson, R.

    2012-04-01

    The infrastructure to gather, store and access information about our environment is improving and growing rapidly. The increasing amount of information allows us to get a better understanding of the current state of our environment, historical processes and to simulate and predict the future state of the environment. Finer grained spatial and temporal data and more reliable communications make it easier to model dynamic states and ephemeral features. The exchange of information within and across geospatial domains is facilitated through the use of harmonized information models. The Observations & Measurements (O&M) developed through OGC and standardised by ISO is an example of such a cross-domain information model. It is used in many domains, including meteorology, hydrology as well as the emergency management. O&M enables harmonized representation of common metadata that belong to the act of determining the state of a feature property, whether by sensors, simulations or humans. In addition to the resulting feature property value, information such as the result quality but especially the time that the result applies to the feature property can be represented. Temporal metadata is critical to modelling past and future states of a feature. The features, and the semantics of each property, are defined in domain specific Application Schema using the General Feature Model (GFM) from ISO 19109 and usually encoded following ISO 19136. However, at the moment these standards provide only limited support for the representation and handling of time varying feature data. Features like rivers, wildfires or gas plumes have a defined state - for example geographic extent - at any given point in time. To keep track of changes, a more complex model for example using time-series coverages is required. Furthermore, the representation and management of feature property value changes via the service interfaces defined by OGC and ISO - namely: WFS and WCS - would be rather complex

  18. Existence and uniqueness of pseudo almost-periodic solutions of recurrent neural networks with time-varying coefficients and mixed delays.

    PubMed

    Ammar, Boudour; Chérif, Farouk; Alimi, Adel M

    2012-01-01

    This paper is concerned with the existence and uniqueness of pseudo almost-periodic solutions to recurrent delayed neural networks. Several conditions guaranteeing the existence and uniqueness of such solutions are obtained in a suitable convex domain. Furthermore, several methods are applied to establish sufficient criteria for the globally exponential stability of this system. The approaches are based on constructing suitable Lyapunov functionals and the well-known Banach contraction mapping principle. Moreover, the attractivity and exponential stability of the pseudo almost-periodic solution are also considered for the system. A numerical example is given to illustrate the effectiveness of our results.

  19. Ultrasonic generator and detector using an optical mask having a grating for launching a plurality of spatially distributed, time varying strain pulses in a sample

    DOEpatents

    Maris, Humphrey J.

    2003-01-01

    A method and a system are disclosed for determining at least one characteristic of a sample that contains a substrate and at least one film disposed on or over a surface of the substrate. The method includes a first step of placing a mask over a free surface of the at least one film, where the mask has a top surface and a bottom surface that is placed adjacent to the free surface of the film. The bottom surface of the mask has formed therein or thereon a plurality of features for forming at least one grating. A next step directs optical pump pulses through the mask to the free surface of the film, where individual ones of the pump pulses are followed by at least one optical probe pulse. The pump pulses are spatially distributed by the grating for launching a plurality of spatially distributed, time varying strain pulses within the film, which cause a detectable change in optical constants of the film. A next step detects a reflected or a transmitted portion of the probe pulses, which are also spatially distributed by the grating. A next step measures a change in at least one characteristic of at least one of reflected or transmitted probe pulses due to the change in optical constants, and a further step determines the at least one characteristic of the sample from the measured change in the at least one characteristic of the probe pulses. An optical mask is also disclosed herein, and forms a part of these teachings.

  20. Ultrasonic generator and detector using an optical mask having a grating for launching a plurality of spatially distributed, time varying strain pulses in a sample

    DOEpatents

    Maris, Humphrey J.

    2002-01-01

    A method and a system are disclosed for determining at least one characteristic of a sample that contains a substrate and at least one film disposed on or over a surface of the substrate. The method includes a first step of placing a mask over a free surface of the at least one film, where the mask has a top surface and a bottom surface that is placed adjacent to the free surface of the film. The bottom surface of the mask has formed therein or thereon a plurality of features for forming at least one grating. A next step directs optical pump pulses through the mask to the free surface of the film, where individual ones of the pump pulses are followed by at least one optical probe pulse. The pump pulses are spatially distributed by the grating for launching a plurality of spatially distributed, time varying strain pulses within the film, which cause a detectable change in optical constants of the film. A next step detects a reflected or a transmitted portion of the probe pulses, which are also spatially distributed by the grating. A next step measures a change in at least one characteristic of at least one of reflected or transmitted probe pulses due to the change in optical constants, and a further step determines the at least one characteristic of the sample from the measured change in the at least one characteristic of the probe pulses. An optical mask is also disclosed herein, and forms a part of these teachings.

  1. Event-based distributed set-membership filtering for a class of time-varying non-linear systems over sensor networks with saturation effects

    NASA Astrophysics Data System (ADS)

    Wei, Guoliang; Liu, Shuai; Wang, Licheng; Wang, Yongxiong

    2016-07-01

    In this paper, based on the event-triggered mechanism, the problem of distributed set-membership filtering is concerned for a class of time-varying non-linear systems over sensor networks subject to saturation effects. Different from the traditional periodic sample-data approach, the filter is updated only when the predefined event is satisfied, which the event is defined according to the measurement output. For each node, the proposed novel event-triggered mechanism can reduce the unnecessary information transmission between sensors and filters. The purpose of the addressed problem is to design a series of distributed set-membership filters, for all the admissible unknown but bounded noises, non-linearities and sensor saturation, such that the set of all possible states can be determined. The desired filter parameters are obtained by solving a recursive linear matrix inequality that can be computed recursively using the available MATLAB toolbox. Finally, a simulation example is exploited to show the effectiveness of the proposed design approach in this paper.

  2. Can distributed delays perfectly stabilize dynamical networks?

    NASA Astrophysics Data System (ADS)

    Omi, Takahiro; Shinomoto, Shigeru

    2008-04-01

    Signal transmission delays tend to destabilize dynamical networks leading to oscillation, but their dispersion contributes oppositely toward stabilization. We analyze an integrodifferential equation that describes the collective dynamics of a neural network with distributed signal delays. With the Γ distributed delays less dispersed than exponential distribution, the system exhibits reentrant phenomena, in which the stability is once lost but then recovered as the mean delay is increased. With delays dispersed more highly than exponential, the system never destabilizes.

  3. Exponential stability and robust H∞ control of a class of discrete-time switched non-linear systems with time-varying delays via T-S fuzzy model

    NASA Astrophysics Data System (ADS)

    Mao, Yanbing; Zhang, Hongbin

    2014-05-01

    This paper deals with stability and robust H∞ control of discrete-time switched non-linear systems with time-varying delays. The T-S fuzzy models are utilised to represent each sub-non-linear system. Thus, with two level functions, namely, crisp switching functions and local fuzzy weighting functions, we introduce a discrete-time switched fuzzy systems, which inherently contain the features of the switched hybrid systems and T-S fuzzy systems. Piecewise fuzzy weighting-dependent Lyapunov-Krasovskii functionals (PFLKFs) and average dwell-time approach are utilised in this paper for the exponentially stability analysis and controller design, and with free fuzzy weighting matrix scheme, switching control laws are obtained such that H∞ performance is satisfied. The conditions of stability and the control laws are given in the form of linear matrix inequalities (LMIs) that are numerically feasible. The state decay estimate is explicitly given. A numerical example and the control of delayed single link robot arm with uncertain part are given to demonstrate the efficiency of the proposed method.

  4. Distributed Load Shedding over Directed Communication Networks with Time Delays

    SciTech Connect

    Yang, Tao; Wu, Di

    2016-07-25

    When generation is insufficient to support all loads under emergencies, effective and efficient load shedding needs to be deployed in order to maintain the supply-demand balance. This paper presents a distributed load shedding algorithm, which makes efficient decision based on the discovered global information. In the global information discovery process, each load only communicates with its neighboring load via directed communication links possibly with arbitrarily large but bounded time varying communication delays. We propose a novel distributed information discovery algorithm based on ratio consensus. Simulation results are used to validate the proposed method.

  5. Control and Identification of Time Varying Systems.

    DTIC Science & Technology

    1986-10-03

    distributed delay systems described by 0 0 i(t) = d o(O)x ( +O) + fJd P(c)u (t +’t) (5) where a(-) and P() are matrix valued functions of bounded ... variation and the integrals are of the Stieltjes type. This includes multiple point delayed systems akin to the system (1) as special cases. Some results

  6. Transit time distributions and StorAge Selection functions in a sloping soil lysimeter with time-varying flow paths: Direct observation of internal and external transport variability

    NASA Astrophysics Data System (ADS)

    Kim, Minseok; Pangle, Luke A.; Cardoso, Charléne; Lora, Marco; Volkmann, Till H. M.; Wang, Yadi; Harman, Ciaran J.; Troch, Peter A.

    2016-09-01

    Transit times through hydrologic systems vary in time, but the nature of that variability is not well understood. Transit times variability was investigated in a 1 m3 sloping lysimeter, representing a simplified model of a hillslope receiving periodic rainfall events for 28 days. Tracer tests were conducted using an experimental protocol that allows time-variable transit time distributions (TTDs) to be calculated from data. Observed TTDs varied with the storage state of the system, and the history of inflows and outflows. We propose that the observed time variability of the TTDs can be decomposed into two parts: "internal" variability associated with changes in the arrangement of, and partitioning between, flow pathways; and "external" variability driven by fluctuations in the flow rate along all flow pathways. These concepts can be defined quantitatively in terms of rank StorAge Selection (rSAS) functions, which is a theory describing lumped transport dynamics. Internal variability is associated with temporal variability in the rSAS function, while external is not. The rSAS function variability was characterized by an "inverse storage effect," whereby younger water is released in greater proportion under wetter conditions than drier. We hypothesize that this effect is caused by the rapid mobilization of water in the unsaturated zone by the rising water table. Common approximations used to model transport dynamics that neglect internal variability were unable to reproduce the observed breakthrough curves accurately. This suggests that internal variability can play an important role in hydrologic transport dynamics, with implications for field data interpretation and modeling.

  7. Fractal analysis of time varying data

    DOEpatents

    Vo-Dinh, Tuan; Sadana, Ajit

    2002-01-01

    Characteristics of time varying data, such as an electrical signal, are analyzed by converting the data from a temporal domain into a spatial domain pattern. Fractal analysis is performed on the spatial domain pattern, thereby producing a fractal dimension D.sub.F. The fractal dimension indicates the regularity of the time varying data.

  8. TIME-VARYING DYNAMICAL STAR FORMATION RATE

    SciTech Connect

    Lee, Eve J.; Chang, Philip; Murray, Norman

    2015-02-10

    We present numerical evidence of dynamic star formation in which the accreted stellar mass grows superlinearly with time, roughly as t {sup 2}. We perform simulations of star formation in self-gravitating hydrodynamic and magnetohydrodynamic turbulence that is continuously driven. By turning the self-gravity of the gas in the simulations on or off, we demonstrate that self-gravity is the dominant physical effect setting the mass accretion rate at early times before feedback effects take over, contrary to theories of turbulence-regulated star formation. We find that gravitational collapse steepens the density profile around stars, generating the power-law tail on what is otherwise a lognormal density probability distribution function. Furthermore, we find turbulent velocity profiles to flatten inside collapsing regions, altering the size-line width relation. This local flattening reflects enhancements of turbulent velocity on small scales, as verified by changes to the velocity power spectra. Our results indicate that gas self-gravity dynamically alters both density and velocity structures in clouds, giving rise to a time-varying star formation rate. We find that a substantial fraction of the gas that forms stars arrives via low-density flows, as opposed to accreting through high-density filaments.

  9. Nonstationary Feller process with time-varying coefficients

    NASA Astrophysics Data System (ADS)

    Masoliver, Jaume

    2016-01-01

    We study the nonstationary Feller process with time varying coefficients. We obtain the exact probability distribution exemplified by its characteristic function and cumulants. In some particular cases we exactly invert the distribution and achieve the probability density function. We show that for sufficiently long times this density approaches a Γ distribution with time-varying shape and scale parameters. Not far from the origin the process obeys a power law with an exponent dependent of time, thereby concluding that accessibility to the origin is not static but dynamic. We finally discuss some possible applications of the process.

  10. Nonstationary Feller process with time-varying coefficients.

    PubMed

    Masoliver, Jaume

    2016-01-01

    We study the nonstationary Feller process with time varying coefficients. We obtain the exact probability distribution exemplified by its characteristic function and cumulants. In some particular cases we exactly invert the distribution and achieve the probability density function. We show that for sufficiently long times this density approaches a Γ distribution with time-varying shape and scale parameters. Not far from the origin the process obeys a power law with an exponent dependent of time, thereby concluding that accessibility to the origin is not static but dynamic. We finally discuss some possible applications of the process.

  11. Mean square delay dependent-probability-distribution stability analysis of neutral type stochastic neural networks.

    PubMed

    Muralisankar, S; Manivannan, A; Balasubramaniam, P

    2015-09-01

    The aim of this manuscript is to investigate the mean square delay dependent-probability-distribution stability analysis of neutral type stochastic neural networks with time-delays. The time-delays are assumed to be interval time-varying and randomly occurring. Based on the new Lyapunov-Krasovskii functional and stochastic analysis approach, a novel sufficient condition is obtained in the form of linear matrix inequality such that the delayed stochastic neural networks are globally robustly asymptotically stable in the mean-square sense for all admissible uncertainties. Finally, the derived theoretical results are validated through numerical examples in which maximum allowable upper bounds are calculated for different lower bounds of time-delay.

  12. Convergence of Asymptotic Systems of Non-autonomous Neural Network Models with Infinite Distributed Delays

    NASA Astrophysics Data System (ADS)

    Oliveira, José J.

    2017-02-01

    In this paper, we investigate the global convergence of solutions of non-autonomous Hopfield neural network models with discrete time-varying delays, infinite distributed delays, and possible unbounded coefficient functions. Instead of using Lyapunov functionals, we explore intrinsic features between the non-autonomous systems and their asymptotic systems to ensure the boundedness and global convergence of the solutions of the studied models. Our results are new and complement known results in the literature. The theoretical analysis is illustrated with some examples and numerical simulations.

  13. Distributed Time Delay Goodwin's Models of the Business Cycle

    NASA Astrophysics Data System (ADS)

    Antonova, A. O.; Reznik, S. N.; Todorov, M. D.

    2011-11-01

    We consider continuously distributed time delay Goodwin's model of the business cycle. We show that the delay induced sawtooth oscillations, similar to those detected by R. H. Strotz, J. C. McAnulty, J. B. Naines, Econometrica, 21, 390-411 (1953) for Goodwin's model with fixed investment time lag, exist only for very narrow delay distribution when the variance of the delay distribution much less than the average delay.

  14. Learning Time-Varying Coverage Functions

    PubMed Central

    Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

    2015-01-01

    Coverage functions are an important class of discrete functions that capture the law of diminishing returns arising naturally from applications in social network analysis, machine learning, and algorithmic game theory. In this paper, we propose a new problem of learning time-varying coverage functions, and develop a novel parametrization of these functions using random features. Based on the connection between time-varying coverage functions and counting processes, we also propose an efficient parameter learning algorithm based on likelihood maximization, and provide a sample complexity analysis. We applied our algorithm to the influence function estimation problem in information diffusion in social networks, and show that with few assumptions about the diffusion processes, our algorithm is able to estimate influence significantly more accurately than existing approaches on both synthetic and real world data. PMID:25960624

  15. Synchronization in time-varying networks

    NASA Astrophysics Data System (ADS)

    Kohar, Vivek; Ji, Peng; Choudhary, Anshul; Sinha, Sudeshna; Kurths, Jüergen

    2014-08-01

    We study the stability of the synchronized state in time-varying complex networks using the concept of basin stability, which is a nonlocal and nonlinear measure of stability that can be easily applied to high-dimensional systems [P. J. Menck, J. Heitzig, N. Marwan, and J. Kurths, Nature Phys. 9, 89 (2013), 10.1038/nphys2516]. The time-varying character is included by stochastically rewiring each link with the average frequency f. We find that the time taken to reach synchronization is lowered and the stability range of the synchronized state increases considerably in dynamic networks. Further we uncover that small-world networks are much more sensitive to link changes than random ones, with the time-varying character of the network having a significant effect at much lower rewiring frequencies. At very high rewiring frequencies, random networks perform better than small-world networks and the synchronized state is stable over a much wider window of coupling strengths. Lastly we show that the stability range of the synchronized state may be quite different for small and large perturbations, and so the linear stability analysis and the basin stability criterion provide complementary indicators of stability.

  16. Synchronization in time-varying networks.

    PubMed

    Kohar, Vivek; Ji, Peng; Choudhary, Anshul; Sinha, Sudeshna; Kurths, Jüergen

    2014-08-01

    We study the stability of the synchronized state in time-varying complex networks using the concept of basin stability, which is a nonlocal and nonlinear measure of stability that can be easily applied to high-dimensional systems [P. J. Menck, J. Heitzig, N. Marwan, and J. Kurths, Nature Phys. 9, 89 (2013)]. The time-varying character is included by stochastically rewiring each link with the average frequency f. We find that the time taken to reach synchronization is lowered and the stability range of the synchronized state increases considerably in dynamic networks. Further we uncover that small-world networks are much more sensitive to link changes than random ones, with the time-varying character of the network having a significant effect at much lower rewiring frequencies. At very high rewiring frequencies, random networks perform better than small-world networks and the synchronized state is stable over a much wider window of coupling strengths. Lastly we show that the stability range of the synchronized state may be quite different for small and large perturbations, and so the linear stability analysis and the basin stability criterion provide complementary indicators of stability.

  17. A time-varying magnetic flux concentrator

    NASA Astrophysics Data System (ADS)

    Kibret, B.; Premaratne, M.; Lewis, P. M.; Thomson, R.; Fitzgerald, P. B.

    2016-08-01

    It is known that diverse technological applications require the use of focused magnetic fields. This has driven the quest for controlling the magnetic field. Recently, the principles in transformation optics and metamaterials have allowed the realization of practical static magnetic flux concentrators. Extending such progress, here, we propose a time-varying magnetic flux concentrator cylindrical shell that uses electric conductors and ferromagnetic materials to guide magnetic flux to its center. Its performance is discussed based on finite-element simulation results. Our proposed design has potential applications in magnetic sensors, medical devices, wireless power transfer, and near-field wireless communications.

  18. Stability analysis of linear fractional differential system with distributed delays

    NASA Astrophysics Data System (ADS)

    Veselinova, Magdalena; Kiskinov, Hristo; Zahariev, Andrey

    2015-11-01

    In the present work we study the Cauchy problem for linear incommensurate fractional differential system with distributed delays. For the autonomous case with distributed delays with derivatives in Riemann-Liouville or Caputo sense, we establish sufficient conditions under which the zero solution is globally asymptotic stable. The established conditions coincide with the conditions which guaranty the same result in the particular case of system with constant delays and for the case of system without delays in the commensurate case too.

  19. Distributed Nonlocal Feedback Delays May Destabilize Fronts in Neural Fields, Distributed Transmission Delays Do Not

    PubMed Central

    2013-01-01

    The spread of activity in neural populations is a well-known phenomenon. To understand the propagation speed and the stability of stationary fronts in neural populations, the present work considers a neural field model that involves intracortical and cortico-cortical synaptic interactions. This includes distributions of axonal transmission speeds and nonlocal feedback delays as well as general classes of synaptic interactions. The work proves the spectral stability of standing and traveling fronts subject to general transmission speeds for large classes of spatial interactions and derives conditions for the front instabilities subjected to nonlocal feedback delays. Moreover, it turns out that the uniqueness of the stationary traveling fronts guarantees its exponential stability for vanishing feedback delay. Numerical simulations complement the analytical findings. PMID:23899051

  20. Time varying, multivariate volume data reduction

    SciTech Connect

    Ahrens, James P; Fout, Nathaniel; Ma, Kwan - Liu

    2010-01-01

    Large-scale supercomputing is revolutionizing the way science is conducted. A growing challenge, however, is understanding the massive quantities of data produced by large-scale simulations. The data, typically time-varying, multivariate, and volumetric, can occupy from hundreds of gigabytes to several terabytes of storage space. Transferring and processing volume data of such sizes is prohibitively expensive and resource intensive. Although it may not be possible to entirely alleviate these problems, data compression should be considered as part of a viable solution, especially when the primary means of data analysis is volume rendering. In this paper we present our study of multivariate compression, which exploits correlations among related variables, for volume rendering. Two configurations for multidimensional compression based on vector quantization are examined. We emphasize quality reconstruction and interactive rendering, which leads us to a solution using graphics hardware to perform on-the-fly decompression during rendering. In this paper we present a solution which addresses the need for data reduction in large supercomputing environments where data resulting from simulations occupies tremendous amounts of storage. Our solution employs a lossy encoding scheme to acrueve data reduction with several options in terms of rate-distortion behavior. We focus on encoding of multiple variables together, with optional compression in space and time. The compressed volumes can be rendered directly with commodity graphics cards at interactive frame rates and rendering quality similar to that of static volume renderers. Compression results using a multivariate time-varying data set indicate that encoding multiple variables results in acceptable performance in the case of spatial and temporal encoding as compared to independent compression of variables. The relative performance of spatial vs. temporal compression is data dependent, although temporal compression has the

  1. Efficient Encoding and Rendering of Time-Varying Volume Data

    NASA Technical Reports Server (NTRS)

    Ma, Kwan-Liu; Smith, Diann; Shih, Ming-Yun; Shen, Han-Wei

    1998-01-01

    Visualization of time-varying volumetric data sets, which may be obtained from numerical simulations or sensing instruments, provides scientists insights into the detailed dynamics of the phenomenon under study. This paper describes a coherent solution based on quantization, coupled with octree and difference encoding for visualizing time-varying volumetric data. Quantization is used to attain voxel-level compression and may have a significant influence on the performance of the subsequent encoding and visualization steps. Octree encoding is used for spatial domain compression, and difference encoding for temporal domain compression. In essence, neighboring voxels may be fused into macro voxels if they have similar values, and subtrees at consecutive time steps may be merged if they are identical. The software rendering process is tailored according to the tree structures and the volume visualization process. With the tree representation, selective rendering may be performed very efficiently. Additionally, the I/O costs are reduced. With these combined savings, a higher level of user interactivity is achieved. We have studied a variety of time-varying volume datasets, performed encoding based on data statistics, and optimized the rendering calculations wherever possible. Preliminary tests on workstations have shown in many cases tremendous reduction by as high as 90% in both storage space and inter-frame delay.

  2. Audibility of time-varying signals in time-varying backgrounds: Model and data

    NASA Astrophysics Data System (ADS)

    Moore, Brian C. J.; Glasberg, Brian R.

    2004-05-01

    We have described a model for calculating the partial loudness of a steady signal in the presence of a steady background sound [Moore et al., J. Audio Eng. Soc. 45, 224-240 (1997)]. We have also described a model for calculating the loudness of time-varying signals [B. R. Glasberg and B. C. J. Moore, J. Audio Eng. Soc. 50, 331-342 (2002)]. These two models have been combined to allow calculation of the partial loudness of a time-varying signal in the presence of a time-varying background. To evaluate the model, psychometric functions for the detection of a variety of time-varying signals (e.g., telephone ring tones) have been measured in a variety of background sounds sampled from everyday listening situations, using a two-alternative forced-choice task. The different signals and backgrounds were interleaved, to create stimulus uncertainty, as would occur in everyday life. The data are used to relate the detectability index, d', to the calculated partial loudness. In this way, the model can be used to predict the detectability of any signal, based on its calculated partial loudness. [Work supported by MRC (UK) and by Nokia.

  3. Compensation of distributed delays in integrated communication and control systems

    NASA Technical Reports Server (NTRS)

    Ray, Asok; Luck, Rogelio

    1991-01-01

    The concept, analysis, implementation, and verification of a method for compensating delays that are distributed between the sensors, controller, and actuators within a control loop are discussed. With the objective of mitigating the detrimental effects of these network induced delays, a predictor-controller algorithm was formulated and analyzed. Robustness of the delay compensation algorithm was investigated relative to parametric uncertainties in plant modeling. The delay compensator was experimentally verified on an IEEE 802.4 network testbed for velocity control of a DC servomotor.

  4. Parallel Rendering of Large Time-Varying Volume Data

    NASA Technical Reports Server (NTRS)

    Garbutt, Alexander E.

    2005-01-01

    Interactive visualization of large time-varying 3D volume datasets has been and still is a great challenge to the modem computational world. It stretches the limits of the memory capacity, the disk space, the network bandwidth and the CPU speed of a conventional computer. In this SURF project, we propose to develop a parallel volume rendering program on SGI's Prism, a cluster computer equipped with state-of-the-art graphic hardware. The proposed program combines both parallel computing and hardware rendering in order to achieve an interactive rendering rate. We use 3D texture mapping and a hardware shader to implement 3D volume rendering on each workstation. We use SGI's VisServer to enable remote rendering using Prism's graphic hardware. And last, we will integrate this new program with ParVox, a parallel distributed visualization system developed at JPL. At the end of the project, we Will demonstrate remote interactive visualization using this new hardware volume renderer on JPL's Prism System using a time-varying dataset from selected JPL applications.

  5. Holographic cinematography of time-varying reflecting and time-varying phase objects using a Nd:YAG laser

    NASA Technical Reports Server (NTRS)

    Decker, A. J.

    1982-01-01

    The use of a Nd:YAG laser to record holographic motion pictures of time-varying reflecting objects and time-varying phase objects is discussed. Sample frames from both types of holographic motion pictures are presented. The holographic system discussed is intended for three-dimensional flow visualization of the time-varying flows that occur in jet-engine components.

  6. Flexible Demand Management under Time-Varying Prices

    NASA Astrophysics Data System (ADS)

    Liang, Yong

    In this dissertation, the problem of flexible demand management under time-varying prices is studied. This generic problem has many applications, which usually have multiple periods in which decisions on satisfying demand need to be made, and prices in these periods are time-varying. Examples of such applications include multi-period procurement problem, operating room scheduling, and user-end demand scheduling in the Smart Grid, where the last application is used as the main motivating story throughout the dissertation. The current grid is experiencing an upgrade with lots of new designs. What is of particular interest is the idea of passing time-varying prices that reflect electricity market conditions to end users as incentives for load shifting. One key component, consequently, is the demand management system at the user-end. The objective of the system is to find the optimal trade-off between cost saving and discomfort increment resulted from load shifting. In this dissertation, we approach this problem from the following aspects: (1) construct a generic model, solve for Pareto optimal solutions, and analyze the robust solution that optimizes the worst-case payoffs, (2) extend to a distribution-free model for multiple types of demand (appliances), for which an approximate dynamic programming (ADP) approach is developed, and (3) design other efficient algorithms for practical purposes of the flexible demand management system. We first construct a novel multi-objective flexible demand management model, in which there are a finite number of periods with time-varying prices, and demand arrives in each period. In each period, the decision maker chooses to either satisfy or defer outstanding demand to minimize costs and discomfort over a certain number of periods. We consider both the deterministic model, models with stochastic demand or prices, and when only partial information about the stochastic demand or prices is known. We first analyze the stochastic

  7. Time Delay Systems with Distribution Dependent Dynamics

    DTIC Science & Technology

    2006-05-10

    sensitivity function for general nonlinear ordinary differential equations (ODEs) in a Banach space. Here we only show the construction of the abstract...shear: A nonlinear stick-slip formulation. CRSC-TR06-07, February, 2006; Differential Equations and Nonlinear Mechanics. Banks, H.T. and H.K. Nguyen (to...dependent dynamical system (in this case a 6 complicated system of partial differential equations ) for which the distribution PL must be estimated in some

  8. Propagation of phase modulation signals in time-varying plasma

    NASA Astrophysics Data System (ADS)

    Yang, Min; Li, Xiaoping; Wang, Di; Liu, Yanming; He, Pan

    2016-05-01

    The effects of time-varying plasma to the propagation of phase modulation signals are investigated in this paper. Through theoretical analysis, the mechanism of the interaction between the time-varying plasma and the phase modulation signal is given. A time-varying plasma generator which could produce arbitrary time-varying plasma is built by adjusting the discharge power. A comparison of results from experiment and simulation prove that the time-varying plasma could cause the special rotation of QPSK (Quadrature Phase Shift Keying) constellation, and the mechanism of constellation point's rotation is analyzed. Additionally, the experimental results of the QPSK signals' EVM (Error Vector Magnitude) after time-varying and time-invariant plasma with different ωp/ω are given. This research could be used to improve the TT&C (Tracking Telemeter and Command) system of re-entry vehicles.

  9. Poverty index with time-varying consumption and income distributions

    NASA Astrophysics Data System (ADS)

    Chattopadhyay, Amit K.; Kumar, T. Krishna; Mallick, Sushanta K.

    2017-03-01

    Starting from a stochastic agent-based model to represent market exchange in a developing economy, we study time variations of the probability density function of income with simultaneous variation of the consumption deprivation (CD), where CD represents the shortfall in consumption from the saturation level of an essential commodity, cereal. Together, these two models combine income-expenditure-based market dynamics with time variations in consumption due to income. In this new unified theoretical structure, exchange of trade in assets is only allowed when the income exceeds consumption-deprivation while CD itself is endogenously obtained from a separate kinetic model. Our results reveal that the nature of time variation of the CD function leads to a downward trend in the threshold level of consumption of basic necessities, suggesting a possible dietary transition in terms of lower saturation level of food-grain consumption, possibly through an improvement in the level of living. The new poverty index, defined as CD, is amenable to approximate probabilistic prediction within a short time horizon. A major achievement of this work is the intrinsic independence of the poverty index from an exogenous poverty line, making it more objective for policy formulation as opposed to existing poverty indices in the literature.

  10. Visualizing Time-Varying Distribution Data in EOS Application

    NASA Technical Reports Server (NTRS)

    Shen, Han-Wei

    2004-01-01

    In this research, we have developed several novel visualization methods for spatial probability density function data. Our focus has been on 2D spatial datasets, where each pixel is a random variable, and has multiple samples which are the results of experiments on that random variable. We developed novel clustering algorithms as a means to reduce the information contained in these datasets; and investigated different ways of interpreting and clustering the data.

  11. Impacts of Time Delays on Distributed Algorithms for Economic Dispatch

    SciTech Connect

    Yang, Tao; Wu, Di; Sun, Yannan; Lian, Jianming

    2015-07-26

    Economic dispatch problem (EDP) is an important problem in power systems. It can be formulated as an optimization problem with the objective to minimize the total generation cost subject to the power balance constraint and generator capacity limits. Recently, several consensus-based algorithms have been proposed to solve EDP in a distributed manner. However, impacts of communication time delays on these distributed algorithms are not fully understood, especially for the case where the communication network is directed, i.e., the information exchange is unidirectional. This paper investigates communication time delay effects on a distributed algorithm for directed communication networks. The algorithm has been tested by applying time delays to different types of information exchange. Several case studies are carried out to evaluate the effectiveness and performance of the algorithm in the presence of time delays in communication networks. It is found that time delay effects have negative effects on the convergence rate, and can even result in an incorrect converge value or fail the algorithm to converge.

  12. Dynamic Factor Analysis Models with Time-Varying Parameters

    ERIC Educational Resources Information Center

    Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian

    2011-01-01

    Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor…

  13. Stable Inversion for Nonlinear Nonminimum-Phase Time Varying Systems

    NASA Technical Reports Server (NTRS)

    Devasia, S.; Paden, B.

    1998-01-01

    In this paper, we extend stable inversion to nonlinear time-varying systems and study computational issues; the technique is applicable to minimum-phase as well as nonminimum-phase systems. The inversion technique is new, even in the linear time-varying case, and relies on partitioning (the dichotomic split of) the linearized system dynamics into time-varying, stable, and unstable, submanifolds. This dichotomic split is used to build time-varying filters which are, in turn, the basis of a contraction used to find a bounded inverse input-state trajectory. Finding the inverse input-state trajectory allows the development or exact-output tracking controllers. The method is local to the time-varying trajectory and requires that the internal dynamics vary slowly; however, the method represents a significant advance relative to presently available tracking controllers. Present techniques are restricted to time-invariant nonlinear systems and, in the general case, track only asymptotically.

  14. Time varying voltage combustion control and diagnostics sensor

    DOEpatents

    Chorpening, Benjamin T.; Thornton, Jimmy D.; Huckaby, E. David; Fincham, William

    2011-04-19

    A time-varying voltage is applied to an electrode, or a pair of electrodes, of a sensor installed in a fuel nozzle disposed adjacent the combustion zone of a continuous combustion system, such as of the gas turbine engine type. The time-varying voltage induces a time-varying current in the flame which is measured and used to determine flame capacitance using AC electrical circuit analysis. Flame capacitance is used to accurately determine the position of the flame from the sensor and the fuel/air ratio. The fuel and/or air flow rate (s) is/are then adjusted to provide reduced flame instability problems such as flashback, combustion dynamics and lean blowout, as well as reduced emissions. The time-varying voltage may be an alternating voltage and the time-varying current may be an alternating current.

  15. Dynamics of strongly coupled spatially distributed logistic equations with delay

    NASA Astrophysics Data System (ADS)

    Kashchenko, I. S.; Kashchenko, S. A.

    2015-04-01

    The dynamics of a system of two logistic delay equations with spatially distributed coupling is studied. The coupling coefficient is assumed to be sufficiently large. Special nonlinear systems of parabolic equations are constructed such that the behavior of their solutions is determined in the first approximation by the dynamical properties of the original system.

  16. Randomly Distributed Delayed Communication and Coherent Swarm Patterns

    DTIC Science & Technology

    2012-05-01

    and Luis Mier-y- Teran -Romero and Ira B. Schwartz Abstract— Previously we showed how delay communication between globally coupled self-propelled agents...brandon.lindley.ctr@nrl.navy.mil L. Mier-y- Teran -Romero is an NIH post doctoral fellow at the Naval Research Laboratory. luis.miery@nrl.navy.mil I. B. Schwartz...S. Shinomoto, “Can distributed delays perfectly stabilize dynamical networks?,” Phys. Rev. E, vol. 77, APR 2008. [31] L. Mier-y Teran -Romero, E

  17. Etiology of phenotype switching strategy in time varying stochastic environment

    NASA Astrophysics Data System (ADS)

    Horvath, Denis; Brutovsky, Branislav

    2016-11-01

    In the paper, we present the two-state discrete-time Markovian model to study the impact of the two alternative switching strategies on the fitness of the population evolving in time varying environment. The first strategy, referred as the 'responsive switching', enables the cell to make transition into the state conferring to it higher fitness in the instant environment. If the alternative strategy, termed 'random switching' is applied, the cell undergoes transition into the new state not regarding the instant environment. Each strategy comes with the respective cost for its physical realization. Within the framework of evolutionary model, mutations occur as random events which change parameters of the probabilistic models corresponding to the respective switching strategies. Most of the general trends of population averages can be easily understood at the intuitive level, with a few exceptions related to the cases when too low mutation noise hampers population to follow rapid environmental changes. On the other hand, the more detailed study of the parameter distributions reveals much more complex structure than expected. The simulation results may help to understand, at the conceptual level, relation between the population heterogeneity and its environment that could find important implications in various areas, such as cancer therapy or development of risk diversifying strategies.

  18. Analysis and Design of Time-Varying Filter Banks

    NASA Astrophysics Data System (ADS)

    Sodagar, Iraj

    Analysis-synthesis filter banks have been studied extensively and a wide range of theoretical problems have been subsequently addressed. However, almost all the research activity has been concentrated on time-invariant filter banks whose components are fixed and do not change in time. The objective of this thesis is to develop analysis and design techniques for time-varying FIR analysis-synthesis filter banks that are perfect reconstructing (PR). In such systems, the analysis and/or synthesis filters, the down-up sampling rates, or even the number of bands can change in time. The underlying idea is that by adapting the basis functions of the filter bank transform to the signal properties, one can represent the relevant information of the signal more efficiently. For analysis purposes, we derive the time-varying impulse response of the filter bank in terms of the analysis and synthesis filter coefficients. We are able to represent this impulse response in terms of the product of the analysis and synthesis matrix transforms. Our approach to the PR time-varying filter bank design is to change the analysis -synthesis filter bank among a set of time-invariant filter banks. The analysis filter banks are switched instantaneously. To eliminate the distortion during switching, a new time-varying synthesis section is designed for each transition. Three design techniques are developed for the time-varying filter bank design. The first technique uses the least squares synthesis filters. This method improves the reconstruction quality significantly, but does not usually achieve the perfect reconstruction. Using the second technique, one can design PR time-varying systems by redesigning the analysis filters. The drawback is that this method requires numerical optimizations. The third technique introduces a new structure for exactly reconstructing time-varying filter banks. This structure consists of the conventional filter bank followed by a time-varying post filter. The post

  19. Estimation of Time-Varying Pilot Model Parameters

    NASA Technical Reports Server (NTRS)

    Zaal, Peter M. T.; Sweet, Barbara T.

    2011-01-01

    Human control behavior is rarely completely stationary over time due to fatigue or loss of attention. In addition, there are many control tasks for which human operators need to adapt their control strategy to vehicle dynamics that vary in time. In previous studies on the identification of time-varying pilot control behavior wavelets were used to estimate the time-varying frequency response functions. However, the estimation of time-varying pilot model parameters was not considered. Estimating these parameters can be a valuable tool for the quantification of different aspects of human time-varying manual control. This paper presents two methods for the estimation of time-varying pilot model parameters, a two-step method using wavelets and a windowed maximum likelihood estimation method. The methods are evaluated using simulations of a closed-loop control task with time-varying pilot equalization and vehicle dynamics. Simulations are performed with and without remnant. Both methods give accurate results when no pilot remnant is present. The wavelet transform is very sensitive to measurement noise, resulting in inaccurate parameter estimates when considerable pilot remnant is present. Maximum likelihood estimation is less sensitive to pilot remnant, but cannot detect fast changes in pilot control behavior.

  20. Neuronal model with distributed delay: analysis and simulation study for gamma distribution memory kernel.

    PubMed

    Karmeshu; Gupta, Varun; Kadambari, K V

    2011-06-01

    A single neuronal model incorporating distributed delay (memory)is proposed. The stochastic model has been formulated as a Stochastic Integro-Differential Equation (SIDE) which results in the underlying process being non-Markovian. A detailed analysis of the model when the distributed delay kernel has exponential form (weak delay) has been carried out. The selection of exponential kernel has enabled the transformation of the non-Markovian model to a Markovian model in an extended state space. For the study of First Passage Time (FPT) with exponential delay kernel, the model has been transformed to a system of coupled Stochastic Differential Equations (SDEs) in two-dimensional state space. Simulation studies of the SDEs provide insight into the effect of weak delay kernel on the Inter-Spike Interval(ISI) distribution. A measure based on Jensen-Shannon divergence is proposed which can be used to make a choice between two competing models viz. distributed delay model vis-á-vis LIF model. An interesting feature of the model is that the behavior of (CV(t))((ISI)) (Coefficient of Variation) of the ISI distribution with respect to memory kernel time constant parameter η reveals that neuron can switch from a bursting state to non-bursting state as the noise intensity parameter changes. The membrane potential exhibits decaying auto-correlation structure with or without damped oscillatory behavior depending on the choice of parameters. This behavior is in agreement with empirically observed pattern of spike count in a fixed time window. The power spectral density derived from the auto-correlation function is found to exhibit single and double peaks. The model is also examined for the case of strong delay with memory kernel having the form of Gamma distribution. In contrast to fast decay of damped oscillations of the ISI distribution for the model with weak delay kernel, the decay of damped oscillations is found to be slower for the model with strong delay kernel.

  1. Global asymptotic stability of Hopfield neural network involving distributed delays.

    PubMed

    Zhao, Hongyong

    2004-01-01

    In the paper, we study dynamical behaviors of Hopfield neural networks system with distributed delays. Some new criteria ensuring the existence and uniqueness, and the global asymptotic stability (GAS) of equilibrium point are derived. In the results, we do not assume that the signal propagation functions satisfy the Lipschitz condition and do not require them to be bounded, differentiable or strictly increasing. Moreover, the symmetry of the connection matrix is not also necessary. Thus, we improve some previous works of other researchers. These conditions are presented in terms of system parameters and have importance leading significance in designs and applications of the GAS for Hopfield neural networks system with distributed delays. Two examples are also worked out to demonstrate the advantages of our results.

  2. Stabilization of linear distributed control systems with unbounded delay

    NASA Astrophysics Data System (ADS)

    Henríquez, Hernán R.; Hernández M., Eduardo

    2005-07-01

    In this paper we study the asymptotic stabilization of linear distributed parameter control systems with unbounded delay. Assuming that the semigroup of operators associated with the uncontrolled and nondelayed equation is compact and that the phase space is a uniform fading memory space, we characterize those systems that can be stabilized using a feedback control. As consequence we conclude that every system of this type is stabilizable with an appropriated finite dimensional control.

  3. Model Selection for Cox Models with Time-Varying Coefficients

    PubMed Central

    Yan, Jun; Huang, Jian

    2011-01-01

    Summary Cox models with time-varying coefficients offer great flexibility in capturing the temporal dynamics of covariate effects on right censored failure times. Since not all covariate coefficients are time-varying, model selection for such models presents an additional challenge, which is to distinguish covariates with time-varying coefficient from those with time-independent coefficient. We propose an adaptive group lasso method that not only selects important variables but also selects between time-independent and time-varying specifications of their presence in the model. Each covariate effect is partitioned into a time-independent part and a time-varying part, the latter of which is characterized by a group of coefficients of basis splines without intercept. Model selection and estimation are carried out through a fast, iterative group shooting algorithm. Our approach is shown to have good properties in a simulation study that mimics realistic situations with up to 20 variables. A real example illustrates the utility of the method. PMID:22506825

  4. Dynamic Factor Analysis Models With Time-Varying Parameters.

    PubMed

    Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian

    2011-04-11

    Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor model with vector autoregressive relations and time-varying cross-regression parameters at the factor level. Using techniques drawn from the state-space literature, the model was fitted to a set of daily affect data (over 71 days) from 10 participants who had been diagnosed with Parkinson's disease. Our empirical results lend partial support and some potential refinement to the Dynamic Model of Activation with regard to how the time dependencies between positive and negative affects change over time. A simulation study is conducted to examine the performance of the proposed techniques when (a) changes in the time-varying parameters are represented using the true model of change, (b) supposedly time-invariant parameters are represented as time-varying, and

  5. Design of Distributed Engine Control Systems with Uncertain Delay

    PubMed Central

    Li, Yanxi; Sun, Xu

    2016-01-01

    Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) is dependent on the network performance. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS). Typical turboshaft engine-distributed controllers are designed based on the NCCS framework with a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method. PMID:27669005

  6. Design of Distributed Engine Control Systems with Uncertain Delay.

    PubMed

    Liu, Xiaofeng; Li, Yanxi; Sun, Xu

    Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) is dependent on the network performance. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS). Typical turboshaft engine-distributed controllers are designed based on the NCCS framework with a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method.

  7. Visualization of Time-Varying Strain Green Tensors

    NASA Astrophysics Data System (ADS)

    Callaghan, S. A.; Maechling, P.

    2006-12-01

    Geophysical tensor data calculated by earthquake wave propagation simulation codes is used to investigate stresses and strains near the earth's surface. To assist scientists with the interpretation of tensor data sets, we have developed distributed processing and visualization techniques for visualizing time-varying, volumetric tensor data. We have applied our techniques to strain Green tensor data calculated for the SCEC/CME CyberShake project in order to explore basin effects in Southern California. One step in the CyberShake project workflow is to generate strain Green tensors for a volume to allow physics-based seismic hazard analysis. These volumes are typically 400 x 400 x 40 km with grid points every 200 m, with 1800 timesteps, yielding multiple terabytes of tensor data in many small files. To graphically display the six-component tensors, we use ellipsoids with the major axes aligned with the three eigenvectors, scaled according to the normalized eigenvalues, and colored based on the magnitude of the eigenvalues. This allows for visualization of the tensor magnitudes, which span a range of over 105, while keeping the ellipsoids a constant size. This software was implemented using the Mesa implementation of OpenGL using the C language. In order to allow interactive visualization of the data, rendering is performed on a parallel computational cluster and real- time images are sent to the user via network sockets. To enable meaningful investigation of the data, a scale for the ellipsoid colors is included. Additionally, a georeferenced surface image is added to provide a point of reference for the user and allow analysis of tensor behavior with other georeferenced data, enabling validation of the CyberShake software and examination of varying ground motions due to basin effects.

  8. Time varying networks and the weakness of strong ties

    NASA Astrophysics Data System (ADS)

    Karsai, Márton; Perra, Nicola; Vespignani, Alessandro

    2014-02-01

    In most social and information systems the activity of agents generates rapidly evolving time-varying networks. The temporal variation in networks' connectivity patterns and the ongoing dynamic processes are usually coupled in ways that still challenge our mathematical or computational modelling. Here we analyse a mobile call dataset and find a simple statistical law that characterize the temporal evolution of users' egocentric networks. We encode this observation in a reinforcement process defining a time-varying network model that exhibits the emergence of strong and weak ties. We study the effect of time-varying and heterogeneous interactions on the classic rumour spreading model in both synthetic, and real-world networks. We observe that strong ties severely inhibit information diffusion by confining the spreading process among agents with recurrent communication patterns. This provides the counterintuitive evidence that strong ties may have a negative role in the spreading of information across networks.

  9. Reduction of chemical reaction networks through delay distributions

    NASA Astrophysics Data System (ADS)

    Barrio, Manuel; Leier, André; Marquez-Lago, Tatiana T.

    2013-03-01

    Accurate modelling and simulation of dynamic cellular events require two main ingredients: an adequate description of key chemical reactions and simulation of such chemical events in reasonable time spans. Quite logically, posing the right model is a crucial step for any endeavour in Computational Biology. However, more often than not, it is the associated computational costs which actually limit our capabilities of representing complex cellular behaviour. In this paper, we propose a methodology aimed at representing chains of chemical reactions by much simpler, reduced models. The abridgement is achieved by generation of model-specific delay distribution functions, consecutively fed to a delay stochastic simulation algorithm. We show how such delay distributions can be analytically described whenever the system is solely composed of consecutive first-order reactions, with or without additional "backward" bypass reactions, yielding an exact reduction. For models including other types of monomolecular reactions (constitutive synthesis, degradation, or "forward" bypass reactions), we discuss why one must adopt a numerical approach for its accurate stochastic representation, and propose two alternatives for this. In these cases, the accuracy depends on the respective numerical sample size. Our model reduction methodology yields significantly lower computational costs while retaining accuracy. Quite naturally, computational costs increase alongside network size and separation of time scales. Thus, we expect our model reduction methodologies to significantly decrease computational costs in these instances. We anticipate the use of delays in model reduction will greatly alleviate some of the current restrictions in simulating large sets of chemical reactions, largely applicable in pharmaceutical and biological research.

  10. Time-varying Reeb Graphs: A Topological Framework Supporting the Analysis of Continuous Time-varying Data

    SciTech Connect

    Mascarenhas, Ajith Arthur

    2006-01-01

    I present time-varying Reeb graphs as a topological framework to support the analysis of continuous time-varying data. Such data is captured in many studies, including computational fluid dynamics, oceanography, medical imaging, and climate modeling, by measuring physical processes over time, or by modeling and simulating them on a computer. Analysis tools are applied to these data sets by scientists and engineers who seek to understand the underlying physical processes. A popular tool for analyzing scientific datasets is level sets, which are the points in space with a fixed data value s. Displaying level sets allows the user to study their geometry, their topological features such as connected components, handles, and voids, and to study the evolution of these features for varying s. For static data, the Reeb graph encodes the evolution of topological features and compactly represents topological information of all level sets. The Reeb graph essentially contracts each level set component to a point. It can be computed efficiently, and it has several uses: as a succinct summary of the data, as an interface to select meaningful level sets, as a data structure to accelerate level set extraction, and as a guide to remove noise. I extend these uses of Reeb graphs to time-varying data. I characterize the changes to Reeb graphs over time, and develop an algorithm that can maintain a Reeb graph data structure by tracking these changes over time. I store this sequence of Reeb graphs compactly, and call it a time-varying Reeb graph. I augment the time-varying Reeb graph with information that records the topology of level sets of all level values at all times, that maintains the correspondence of level set components over time, and that accelerates the extraction of level sets for a chosen level value and time. Scientific data sampled in space-time must be extended everywhere in this domain using an interpolant. A poor choice of interpolant can create degeneracies that are

  11. Adaptive stabilization of discrete-time systems using linear periodically time varying controllers

    NASA Technical Reports Server (NTRS)

    Ortega, Romeo; Albertos, Pedro; Lozano, Rogelio

    1988-01-01

    A direct adaptive scheme based on the use of linear time-varying periodic controllers is proposed which estimates online the periodic coefficients of the controller. It is shown that adaptive stabilization is attained for all possibly nonstably invertible plants of known order but unknown delay. Although no appeal is made to persistency of excitation arguments, a provision is needed to avoid the singularity of an estimated matrix, this property being required only for the analysis and not the control calculations.

  12. Decoupling in linear time-varying multivariable systems

    NASA Technical Reports Server (NTRS)

    Sankaran, V.

    1973-01-01

    The necessary and sufficient conditions for the decoupling of an m-input, m-output, linear time varying dynamical system by state variable feedback is described. The class of feedback matrices which decouple the system are illustrated. Systems which do not satisfy these results are described and systems with disturbances are considered. Some examples are illustrated to clarify the results.

  13. Cosmology with a time-varying speed of light

    NASA Astrophysics Data System (ADS)

    Albrecht, Andreas

    1999-07-01

    Cosmic inflation is the only known mechanism with the potential to explain the very special initial conditions which are required at the early stages of the evolution of our universe. This article outlines my work with Joao Magueijo which attempts to construct an alternative mechanism based on a time-varying speed of light.

  14. Time varying market efficiency of the GCC stock markets

    NASA Astrophysics Data System (ADS)

    Charfeddine, Lanouar; Khediri, Karim Ben

    2016-02-01

    This paper investigates the time-varying levels of weak-form market efficiency for the GCC stock markets over the period spanning from May 2005 to September 2013. We use two empirical approaches: (1) the generalized autoregressive conditional heteroscedasticity in mean (GARCH-M) model with state space time varying parameter (Kalman filter), and (2) a rolling technique sample test of the fractional long memory parameter d. As long memory estimation methods, we use the detrended fluctuation analysis (DFA) technique, the modified R/S statistic, the exact local whittle (ELW) and the feasible Exact Local Whittle (FELW) methods. Moreover, we use the Bai and Perron (1998, 2003) multiple structural breaks technique to test and date the time varying behavior of stock market efficiency. Empirical results show that GCC markets have different degrees of time-varying efficiency, and also have experiencing periods of efficiency improvement. Results also show evidence of structural breaks in all GCC markets. Moreover, we observe that the recent financial shocks such as Arab spring and subprime crises have a significant impact on the time path evolution of market efficiency.

  15. Time-Varying Affective Response for Humanoid Robots

    NASA Astrophysics Data System (ADS)

    Moshkina, Lilia; Arkin, Ronald C.; Lee, Jamee K.; Jung, Hyunryong

    This paper describes the design of a complex time-varying affective architecture. It is an expansion of the TAME architecture (traits, attitudes, moods, and emotions) as applied to humanoid robotics. It particular it is intended to promote effective human-robot interaction by conveying the robot’s affective state to the user in an easy-to-interpret manner.

  16. Applicability of delay tolerant networking to distributed satellite systems

    NASA Astrophysics Data System (ADS)

    Freimann, A.; Tzschichholz, T.; Schmidt, M.; Kleinschrodt, A.; Schilling, K.

    2016-12-01

    Currently, a trend towards distributed small satellite missions is emerging using cooperating satellites to achieve joint mission objectives, e.g. for earth observation. Communication is a key feature when cooperation between satellites is desired. Typically those satellite networks are affected by slow data rates, high packet loss and intermittent connectivity. To address these challenges the store-and-forward approach of the delay tolerant networking (DTN) concept is investigated in this article. Network simulations of typical scenarios were carried out and evaluated to derive statements about the applicability of the DTN approach to networks in low earth orbits.

  17. Stabilising compensators for linear time-varying differential systems

    NASA Astrophysics Data System (ADS)

    Oberst, Ulrich

    2016-04-01

    In this paper, we describe a constructive test to decide whether a given linear time-varying (LTV) differential system admits a stabilising compensator for the control tasks of tracking, disturbance rejection or model matching and construct and parametrise all of them if at least one exists. In analogy to the linear time-invariant (LTI) case, the ring of stable rational functions, noncommutative in the LTV situation, and the Kučera-Youla parametrisation play prominent parts in the theory. We transfer Blumthaler's thesis from the LTI to the LTV case and sharpen, complete and simplify the corresponding results in the book 'Linear Time-Varying Systems' by Bourlès and Marinescu.

  18. Path Flow Estimation Using Time Varying Coefficient State Space Model

    NASA Astrophysics Data System (ADS)

    Jou, Yow-Jen; Lan, Chien-Lun

    2009-08-01

    The dynamic path flow information is very crucial in the field of transportation operation and management, i.e., dynamic traffic assignment, scheduling plan, and signal timing. Time-dependent path information, which is important in many aspects, is nearly impossible to be obtained. Consequently, researchers have been seeking estimation methods for deriving valuable path flow information from less expensive traffic data, primarily link traffic counts of surveillance systems. This investigation considers a path flow estimation problem involving the time varying coefficient state space model, Gibbs sampler, and Kalman filter. Numerical examples with part of a real network of the Taipei Mass Rapid Transit with real O-D matrices is demonstrated to address the accuracy of proposed model. Results of this study show that this time-varying coefficient state space model is very effective in the estimation of path flow compared to time-invariant model.

  19. Morphable Word Clouds for Time-Varying Text Data Visualization.

    PubMed

    Chi, Ming-Te; Lin, Shih-Syun; Chen, Shiang-Yi; Lin, Chao-Hung; Lee, Tong-Yee

    2015-12-01

    A word cloud is a visual representation of a collection of text documents that uses various font sizes, colors, and spaces to arrange and depict significant words. The majority of previous studies on time-varying word clouds focuses on layout optimization and temporal trend visualization. However, they do not fully consider the spatial shapes and temporal motions of word clouds, which are important factors for attracting people's attention and are also important cues for human visual systems in capturing information from time-varying text data. This paper presents a novel method that uses rigid body dynamics to arrange multi-temporal word-tags in a specific shape sequence under various constraints. Each word-tag is regarded as a rigid body in dynamics. With the aid of geometric, aesthetic, and temporal coherence constraints, the proposed method can generate a temporally morphable word cloud that not only arranges word-tags in their corresponding shapes but also smoothly transforms the shapes of word clouds over time, thus yielding a pleasing time-varying visualization. Using the proposed frame-by-frame and morphable word clouds, people can observe the overall story of a time-varying text data from the shape transition, and people can also observe the details from the word clouds in frames. Experimental results on various data demonstrate the feasibility and flexibility of the proposed method in morphable word cloud generation. In addition, an application that uses the proposed word clouds in a simulated exhibition demonstrates the usefulness of the proposed method.

  20. Generating survival times to simulate Cox proportional hazards models with time-varying covariates.

    PubMed

    Austin, Peter C

    2012-12-20

    Simulations and Monte Carlo methods serve an important role in modern statistical research. They allow for an examination of the performance of statistical procedures in settings in which analytic and mathematical derivations may not be feasible. A key element in any statistical simulation is the existence of an appropriate data-generating process: one must be able to simulate data from a specified statistical model. We describe data-generating processes for the Cox proportional hazards model with time-varying covariates when event times follow an exponential, Weibull, or Gompertz distribution. We consider three types of time-varying covariates: first, a dichotomous time-varying covariate that can change at most once from untreated to treated (e.g., organ transplant); second, a continuous time-varying covariate such as cumulative exposure at a constant dose to radiation or to a pharmaceutical agent used for a chronic condition; third, a dichotomous time-varying covariate with a subject being able to move repeatedly between treatment states (e.g., current compliance or use of a medication). In each setting, we derive closed-form expressions that allow one to simulate survival times so that survival times are related to a vector of fixed or time-invariant covariates and to a single time-varying covariate. We illustrate the utility of our closed-form expressions for simulating event times by using Monte Carlo simulations to estimate the statistical power to detect as statistically significant the effect of different types of binary time-varying covariates. This is compared with the statistical power to detect as statistically significant a binary time-invariant covariate.

  1. The impact of command signal power distribution, processing delays, and speed scaling on neurally-controlled devices

    NASA Astrophysics Data System (ADS)

    Marathe, A. R.; Taylor, D. M.

    2015-08-01

    Objective. Decoding algorithms for brain-machine interfacing (BMI) are typically only optimized to reduce the magnitude of decoding errors. Our goal was to systematically quantify how four characteristics of BMI command signals impact closed-loop performance: (1) error magnitude, (2) distribution of different frequency components in the decoding errors, (3) processing delays, and (4) command gain. Approach. To systematically evaluate these different command features and their interactions, we used a closed-loop BMI simulator where human subjects used their own wrist movements to command the motion of a cursor to targets on a computer screen. Random noise with three different power distributions and four different relative magnitudes was added to the ongoing cursor motion in real time to simulate imperfect decoding. These error characteristics were tested with four different visual feedback delays and two velocity gains. Main results. Participants had significantly more trouble correcting for errors with a larger proportion of low-frequency, slow-time-varying components than they did with jittery, higher-frequency errors, even when the error magnitudes were equivalent. When errors were present, a movement delay often increased the time needed to complete the movement by an order of magnitude more than the delay itself. Scaling down the overall speed of the velocity command can actually speed up target acquisition time when low-frequency errors and delays are present. Significance. This study is the first to systematically evaluate how the combination of these four key command signal features (including the relatively-unexplored error power distribution) and their interactions impact closed-loop performance independent of any specific decoding method. The equations we derive relating closed-loop movement performance to these command characteristics can provide guidance on how best to balance these different factors when designing BMI systems. The equations reported

  2. Time-varying boundaries for diffusion models of decision making and response time

    PubMed Central

    Zhang, Shunan; Lee, Michael D.; Vandekerckhove, Joachim; Maris, Gunter; Wagenmakers, Eric-Jan

    2014-01-01

    Diffusion models are widely-used and successful accounts of the time course of two-choice decision making. Most diffusion models assume constant boundaries, which are the threshold levels of evidence that must be sampled from a stimulus to reach a decision. We summarize theoretical results from statistics that relate distributions of decisions and response times to diffusion models with time-varying boundaries. We then develop a computational method for finding time-varying boundaries from empirical data, and apply our new method to two problems. The first problem involves finding the time-varying boundaries that make diffusion models equivalent to the alternative sequential sampling class of accumulator models. The second problem involves finding the time-varying boundaries, at the individual level, that best fit empirical data for perceptual stimuli that provide equal evidence for both decision alternatives. We discuss the theoretical and modeling implications of using time-varying boundaries in diffusion models, as well as the limitations and potential of our approach to their inference. PMID:25538642

  3. The effect of distributed time-delays on the synchronization of neuronal networks

    NASA Astrophysics Data System (ADS)

    Kachhvah, Ajay Deep

    2017-01-01

    Here we investigate the synchronization of networks of FitzHugh-Nagumo neurons coupled in scale-free, small-world and random topologies, in the presence of distributed time delays in the coupling of neurons. We explore how the synchronization transition is affected when the time delays in the interactions between pairs of interacting neurons are non-uniform. We find that the presence of distributed time-delays does not change the behavior of the synchronization transition significantly, vis-a-vis networks with constant time-delay, where the value of the constant time-delay is the mean of the distributed delays. We also notice that a normal distribution of delays gives rise to a transition at marginally lower coupling strengths, vis-a-vis uniformly distributed delays. These trends hold across classes of networks and for varying standard deviations of the delay distribution, indicating the generality of these results. So we conclude that distributed delays, which may be typically expected in real-world situations, do not have a notable effect on synchronization. This allows results obtained with constant delays to remain relevant even in the case of randomly distributed delays.

  4. Synthesis fidelity and time-varying spectral change in vowels

    NASA Astrophysics Data System (ADS)

    Assmann, Peter F.; Katz, William F.

    2005-02-01

    Recent studies have shown that synthesized versions of American English vowels are less accurately identified when the natural time-varying spectral changes are eliminated by holding the formant frequencies constant over the duration of the vowel. A limitation of these experiments has been that vowels produced by formant synthesis are generally less accurately identified than the natural vowels after which they are modeled. To overcome this limitation, a high-quality speech analysis-synthesis system (STRAIGHT) was used to synthesize versions of 12 American English vowels spoken by adults and children. Vowels synthesized with STRAIGHT were identified as accurately as the natural versions, in contrast with previous results from our laboratory showing identification rates 9%-12% lower for the same vowels synthesized using the cascade formant model. Consistent with earlier studies, identification accuracy was not reduced when the fundamental frequency was held constant across the vowel. However, elimination of time-varying changes in the spectral envelope using STRAIGHT led to a greater reduction in accuracy (23%) than was previously found with cascade formant synthesis (11%). A statistical pattern recognition model, applied to acoustic measurements of the natural and synthesized vowels, predicted both the higher identification accuracy for vowels synthesized using STRAIGHT compared to formant synthesis, and the greater effects of holding the formant frequencies constant over time with STRAIGHT synthesis. Taken together, the experiment and modeling results suggest that formant estimation errors and incorrect rendering of spectral and temporal cues by cascade formant synthesis contribute to lower identification accuracy and underestimation of the role of time-varying spectral change in vowels. .

  5. Visual exploration of complex time-varying graphs.

    PubMed

    Kumar, Gautam; Garland, Michael

    2006-01-01

    Many graph drawing and visualization algorithms, such as force-directed layout and line-dot rendering, work very well on relatively small and sparse graphs. However, they often produce extremely tangled results and exhibit impractical running times for highly non-planar graphs with large edge density. And very few graph layout algorithms support dynamic time-varying graphs; applying them independently to each frame produces distracting temporally incoherent visualizations. We have developed a new visualization technique based on a novel approach to hierarchically structuring dense graphs via stratification. Using this structure, we formulate a hierarchical force-directed layout algorithm that is both efficient and produces quality graph layouts. The stratification of the graph also allows us to present views of the data that abstract away many small details of its structure. Rather than displaying all edges and nodes at once, resulting in a convoluted rendering, we present an interactive tool that filters edges and nodes using the graph hierarchy and allows users to drill down into the graph for details. Our layout algorithm also accommodates time-varying graphs in a natural way, producing a temporally coherent animation that can be used to analyze and extract trends from dynamic graph data. For example, we demonstrate the use of our method to explore financial correlation data for the U.S. stock market in the period from 1990 to 2005. The user can easily analyze the time-varying correlation graph of the market, uncovering information such as market sector trends, representative stocks for portfolio construction, and the interrelationship of stocks over time.

  6. Recursive time-varying filter banks for subband image coding

    NASA Technical Reports Server (NTRS)

    Smith, Mark J. T.; Chung, Wilson C.

    1992-01-01

    Filter banks and wavelet decompositions that employ recursive filters have been considered previously and are recognized for their efficiency in partitioning the frequency spectrum. This paper presents an analysis of a new infinite impulse response (IIR) filter bank in which these computationally efficient filters may be changed adaptively in response to the input. The filter bank is presented and discussed in the context of finite-support signals with the intended application in subband image coding. In the absence of quantization errors, exact reconstruction can be achieved and by the proper choice of an adaptation scheme, it is shown that IIR time-varying filter banks can yield improvement over conventional ones.

  7. Downdating a time-varying square root information filter

    NASA Technical Reports Server (NTRS)

    Muellerschoen, Ronald J.

    1990-01-01

    A new method to efficiently downdate an estimate and covariance generated by a discrete time Square Root Information Filter (SRIF) is presented. The method combines the QR factor downdating algorithm of Gill and the decentralized SRIF algorithm of Bierman. Efficient removal of either measurements or a priori information is possible without loss of numerical integrity. Moreover, the method includes features for detecting potential numerical degradation. Performance on a 300 parameter system with 5800 data points shows that the method can be used in real time and hence is a promising tool for interactive data analysis. Additionally, updating a time-varying SRIF filter with either additional measurements or a priori information proceeds analogously.

  8. Optimal transport in time-varying small-world networks

    NASA Astrophysics Data System (ADS)

    Chen, Qu; Qian, Jiang-Hai; Zhu, Liang; Han, Ding-Ding

    2016-03-01

    The time-order of interactions, which is regulated by some intrinsic activity, surely plays a crucial role regarding the transport efficiency of transportation systems. Here we study the optimal transport structure by measure of the length of time-respecting paths. Our network is built from a two-dimensional regular lattice, and long-range connections are allocated with probability Pi j˜rij -α , where ri j is the Manhattan distance. By assigning each shortcut an activity rate subjected to its geometric distance τi j˜rij -C , long-range links become active intermittently, leading to the time-varying dynamics. We show that for 0 time-varying transportation networks. Empirical studies on British Airways and Austrian Airlines provide consistent evidence with our conclusion.

  9. Integrated Sachs-Wolfe effect in time varying vacuum model

    SciTech Connect

    Wang, Y. T.; Gui, Y. X.; Xu, L. X.; Lu, J. B.

    2010-04-15

    The integrated Sachs-Wolfe (ISW) effect is an important implication for dark energy. In this paper, we have calculated the power spectrum of the ISW effect in the time varying vacuum cosmological model, where the model parameter {beta}=4.407 is obtained by the observational constraint of the growth rate. It is found that the source of the ISW effect is not only affected by the different evolutions of the Hubble function H(a) and the dimensionless matter density {Omega}{sub m}(a), but also by the different growth function D{sub +}(a), all of which are changed due to the presence of a matter production term in the time varying vacuum model. However, the difference of the ISW effect in the {Lambda}(t)CDM model and the {Lambda}CDM model is lessened to a certain extent because of the integration from the time of last scattering to the present. It is implied that the observations of the galaxies with high redshift are required to distinguish the two models.

  10. Interactive isosurface ray tracing of time-varying tetrahedral volumes.

    PubMed

    Wald, Ingo; Friedrich, Heiko; Knoll, Aaron; Hansen, Charles D

    2007-01-01

    We describe a system for interactively rendering isosurfaces of tetrahedral finite-element scalar fields using coherent ray tracing techniques on the CPU. By employing state-of-the art methods in polygonal ray tracing, namely aggressive packet/frustum traversal of a bounding volume hierarchy, we can accomodate large and time-varying unstructured data. In conjunction with this efficiency structure, we introduce a novel technique for intersecting ray packets with tetrahedral primitives. Ray tracing is flexible, allowing for dynamic changes in isovalue and time step, visualization of multiple isosurfaces, shadows, and depth-peeling transparency effects. The resulting system offers the intuitive simplicity of isosurfacing, guaranteed-correct visual results, and ultimately a scalable, dynamic and consistently interactive solution for visualizing unstructured volumes.

  11. Epidemic spreading in time-varying community networks

    SciTech Connect

    Ren, Guangming E-mail: ren-guang-ming@163.com; Wang, Xingyuan E-mail: ren-guang-ming@163.com

    2014-06-15

    The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold q{sub c}. The epidemic will survive when q > q{sub c} and die when q < q{sub c}. These results can help understanding the impacts of human travel on the epidemic spreading in complex networks with community structure.

  12. A Symmetric Time-Varying Cluster Rate of Descent Model

    NASA Technical Reports Server (NTRS)

    Ray, Eric S.

    2015-01-01

    A model of the time-varying rate of descent of the Orion vehicle was developed based on the observed correlation between canopy projected area and drag coefficient. This initial version of the model assumes cluster symmetry and only varies the vertical component of velocity. The cluster fly-out angle is modeled as a series of sine waves based on flight test data. The projected area of each canopy is synchronized with the primary fly-out angle mode. The sudden loss of projected area during canopy collisions is modeled at minimum fly-out angles, leading to brief increases in rate of descent. The cluster geometry is converted to drag coefficient using empirically derived constants. A more complete model is under development, which computes the aerodynamic response of each canopy to its local incidence angle.

  13. Circular motion analysis of time-varying bioimpedance.

    PubMed

    Sanchez, B; Louarroudi, E; Rutkove, S B; Pintelon, R

    2015-11-01

    This paper presents a step forward towards the analysis of a linear periodically time-varying (PTV) bioimpedance ZPTV(jw, t), which is an important subclass of a linear time-varying (LTV) bioimpedance. Similarly to the Fourier coefficients of a periodic signal, a PTV impedance can be decomposed into frequency dependent impedance phasors, [Formula: see text], that are rotating with an angular speed of wr = 2πr/TZ. The vector length of these impedance phasors corresponds to the amplitude of the rth-order harmonic impedance |Zr( jw)| and the initial phase is given by Φr(w, t0) = [Symbol: see text]Zr( jw) + 2πrt0/TZ, with t0∈[0, T] being a time instant within the measurement time T. The impedance period TZ stands for the cycle length of the bio-system under investigation; for example, the elapsed time between two consecutive R-waves in the electrocardiogram or the breathing periodicity in case of the heart or lungs, respectively. First, it is demonstrated that the harmonic impedance phasor [Formula: see text], at a particular measured frequency k, can be represented by a rotating phasor, leading to the so-called circular motion analysis technique. Next, the two dimensional (2D) representation of the harmonic impedance phasors is then extended to a three-dimensional (3D) coordinate system by taking into account the frequency dependence. Finally, we introduce a new visualizing tool to summarize the frequency response behavior of ZPTV( jw, t) into a single 3D plot using the local Frenet-Serret frame. This novel 3D impedance representation is then compared with the 3D Nyquist representation of a PTV impedance. The concepts are illustrated through real measurements conducted on a PTV RC-circuit.

  14. Estimation of the blood Doppler frequency shift by a time-varying parametric approach.

    PubMed

    Girault, J M; Kouamé, D; Ouahabi, A; Patat, F

    2000-03-01

    Doppler ultrasound is widely used in medical applications to extract the blood Doppler flow velocity in the arteries via spectral analysis. The spectral analysis of non-stationary signals and particularly Doppler signals requires adequate tools that should present both good time and frequency resolutions. It is well-known that the most commonly used time-windowed Fourier transform, which provides a time-frequency representation, is limited by the intrinsic trade-off between time and frequency resolutions. Parametric methods have then been introduced as an alternative to overcome this resolution problem. However, the performance of those methods deteriorates when high non-stationarities are present in the Doppler signal. For the purpose of accurately estimating the Doppler frequency shift, even when the temporal flow velocity is rapid (high non-stationarity), we propose to combine the use of the time-varying autoregressive (AR) method and the (dominant) pole frequency. This proposed method performs well in the context where non-stationarities are very high. A comparative evaluation has been made between classical (FFT based) and AR (both block and recursive) algorithms. Among recursive algorithms we test an adaptive recursive method as well as a time-varying recursive method. Finally, the superiority of the time-varying parametric approach in terms of frequency tracking and delay in the frequency estimate is illustrated for both simulated and in vivo Doppler signals.

  15. Complexity Variability Assessment of Nonlinear Time-Varying Cardiovascular Control.

    PubMed

    Valenza, Gaetano; Citi, Luca; Garcia, Ronald G; Taylor, Jessica Noggle; Toschi, Nicola; Barbieri, Riccardo

    2017-02-20

    The application of complex systems theory to physiology and medicine has provided meaningful information about the nonlinear aspects underlying the dynamics of a wide range of biological processes and their disease-related aberrations. However, no studies have investigated whether meaningful information can be extracted by quantifying second-order moments of time-varying cardiovascular complexity. To this extent, we introduce a novel mathematical framework termed complexity variability, in which the variance of instantaneous Lyapunov spectra estimated over time serves as a reference quantifier. We apply the proposed methodology to four exemplary studies involving disorders which stem from cardiology, neurology and psychiatry: Congestive Heart Failure (CHF), Major Depression Disorder (MDD), Parkinson's Disease (PD), and Post-Traumatic Stress Disorder (PTSD) patients with insomnia under a yoga training regime. We show that complexity assessments derived from simple time-averaging are not able to discern pathology-related changes in autonomic control, and we demonstrate that between-group differences in measures of complexity variability are consistent across pathologies. Pathological states such as CHF, MDD, and PD are associated with an increased complexity variability when compared to healthy controls, whereas wellbeing derived from yoga in PTSD is associated with lower time-variance of complexity.

  16. Study of selected phenotype switching strategies in time varying environment

    NASA Astrophysics Data System (ADS)

    Horvath, Denis; Brutovsky, Branislav

    2016-03-01

    Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback-Leibler functional distances and the Hamming distance.

  17. Complexity Variability Assessment of Nonlinear Time-Varying Cardiovascular Control

    PubMed Central

    Valenza, Gaetano; Citi, Luca; Garcia, Ronald G.; Taylor, Jessica Noggle; Toschi, Nicola; Barbieri, Riccardo

    2017-01-01

    The application of complex systems theory to physiology and medicine has provided meaningful information about the nonlinear aspects underlying the dynamics of a wide range of biological processes and their disease-related aberrations. However, no studies have investigated whether meaningful information can be extracted by quantifying second-order moments of time-varying cardiovascular complexity. To this extent, we introduce a novel mathematical framework termed complexity variability, in which the variance of instantaneous Lyapunov spectra estimated over time serves as a reference quantifier. We apply the proposed methodology to four exemplary studies involving disorders which stem from cardiology, neurology and psychiatry: Congestive Heart Failure (CHF), Major Depression Disorder (MDD), Parkinson’s Disease (PD), and Post-Traumatic Stress Disorder (PTSD) patients with insomnia under a yoga training regime. We show that complexity assessments derived from simple time-averaging are not able to discern pathology-related changes in autonomic control, and we demonstrate that between-group differences in measures of complexity variability are consistent across pathologies. Pathological states such as CHF, MDD, and PD are associated with an increased complexity variability when compared to healthy controls, whereas wellbeing derived from yoga in PTSD is associated with lower time-variance of complexity. PMID:28218249

  18. Automated model formulation for time-varying flexible structures

    NASA Technical Reports Server (NTRS)

    Glass, B. J.; Hanagud, S.

    1989-01-01

    Presented here is an identification technique that uses the sensor information to choose a new model out of a finite set of discrete model space, in order to follow the observed changes to the given time varying flexible structure. Boundary condition sets or other information on model variations are used to organize the set of possible models laterally into a search tree with levels of abstraction used to order the models vertically within branches. An object-oriented programming approach is used to represent the model set in the search tree. A modified A (asterisk) best first search algorithm finds the model where the model response best matches the current observations. Several extensions to this methodology are discussed. Methods of possible integration of rules with the current search algorithm are considered to give weight to interpreted trends that may be found in a series of observations. This capability might lead, for instance, to identifying a model that incorporates a progressive damage rather than with incorrect paramenters such as added mass. Another new direction is to consider the use of noisy time domain sensor feedback rather than frequency domain information in the search algorithm to improve the real-time capability of the developed procedure.

  19. Opinion formation with time-varying bounded confidence.

    PubMed

    Zhang, YunHong; Liu, QiPeng; Zhang, SiYing

    2017-01-01

    When individuals in social groups communicate with one another and are under the influence of neighbors' opinions, they typically revise their own opinions to adapt to such peer opinions. The individual threshold of bounded confidence will thus be affected by both a change in individual confidence and by neighbor influence. Individuals thus update their own opinions with new bounded confidence, while their updated opinions also influence their neighbors' opinions. Based on this reasoned factual assumption, we propose an opinion dynamics model with time-varying bounded confidence. A directed network is formed by the rule of the individual bounded confidence threshold. The threshold of individual bounded confidence involves both confidence variation and the in/out degree of the individual node. When the confidence variation is greater, an individual's confidence in persisting in his own opinion in interactions is weaker, and the individual is more likely to adopt neighbors' opinions. In networks, the in/out degree is determined by individual neighbors. Our main research involves the process of opinion evolution and the basic laws of opinion cluster formation. Group opinions converge exponentially to consensus with stable neighbors. An individual opinion evolution is determined by the average neighbor opinion effect strength. We also explore the conditions involved in forming a stable neighbor relationship and the influence of the confidence variation in the convergence of the threshold of bounded confidence. The results show that the influence on opinion evolution is greater with increased confidence variation.

  20. Opinion formation with time-varying bounded confidence

    PubMed Central

    Liu, QiPeng; Zhang, SiYing

    2017-01-01

    When individuals in social groups communicate with one another and are under the influence of neighbors’ opinions, they typically revise their own opinions to adapt to such peer opinions. The individual threshold of bounded confidence will thus be affected by both a change in individual confidence and by neighbor influence. Individuals thus update their own opinions with new bounded confidence, while their updated opinions also influence their neighbors’ opinions. Based on this reasoned factual assumption, we propose an opinion dynamics model with time-varying bounded confidence. A directed network is formed by the rule of the individual bounded confidence threshold. The threshold of individual bounded confidence involves both confidence variation and the in/out degree of the individual node. When the confidence variation is greater, an individual’s confidence in persisting in his own opinion in interactions is weaker, and the individual is more likely to adopt neighbors’ opinions. In networks, the in/out degree is determined by individual neighbors. Our main research involves the process of opinion evolution and the basic laws of opinion cluster formation. Group opinions converge exponentially to consensus with stable neighbors. An individual opinion evolution is determined by the average neighbor opinion effect strength. We also explore the conditions involved in forming a stable neighbor relationship and the influence of the confidence variation in the convergence of the threshold of bounded confidence. The results show that the influence on opinion evolution is greater with increased confidence variation. PMID:28264038

  1. Innovation diffusion on time-varying activity driven networks

    NASA Astrophysics Data System (ADS)

    Rizzo, Alessandro; Porfiri, Maurizio

    2016-01-01

    Since its introduction in the 1960s, the theory of innovation diffusion has contributed to the advancement of several research fields, such as marketing management and consumer behavior. The 1969 seminal paper by Bass [F.M. Bass, Manag. Sci. 15, 215 (1969)] introduced a model of product growth for consumer durables, which has been extensively used to predict innovation diffusion across a range of applications. Here, we propose a novel approach to study innovation diffusion, where interactions among individuals are mediated by the dynamics of a time-varying network. Our approach is based on the Bass' model, and overcomes key limitations of previous studies, which assumed timescale separation between the individual dynamics and the evolution of the connectivity patterns. Thus, we do not hypothesize homogeneous mixing among individuals or the existence of a fixed interaction network. We formulate our approach in the framework of activity driven networks to enable the analysis of the concurrent evolution of the interaction and individual dynamics. Numerical simulations offer a systematic analysis of the model behavior and highlight the role of individual activity on market penetration when targeted advertisement campaigns are designed, or a competition between two different products takes place.

  2. Video painting with space-time-varying style parameters.

    PubMed

    Kagaya, Mizuki; Brendel, William; Deng, Qingqing; Kesterson, Todd; Todorovic, Sinisa; Neill, Patrick J; Zhang, Eugene

    2011-01-01

    Artists use different means of stylization to control the focus on different objects in the scene. This allows them to portray complex meaning and achieve certain artistic effects. Most prior work on painterly rendering of videos, however, uses only a single painting style, with fixed global parameters, irrespective of objects and their layout in the images. This often leads to inadequate artistic control. Moreover, brush stroke orientation is typically assumed to follow an everywhere continuous directional field. In this paper, we propose a video painting system that accounts for the spatial support of objects in the images or videos, and uses this information to specify style parameters and stroke orientation for painterly rendering. Since objects occupy distinct image locations and move relatively smoothly from one video frame to another, our object-based painterly rendering approach is characterized by style parameters that coherently vary in space and time. Space-time-varying style parameters enable more artistic freedom, such as emphasis/de-emphasis, increase or decrease of contrast, exaggeration or abstraction of different objects in the scene in a temporally coherent fashion.

  3. Complexity Variability Assessment of Nonlinear Time-Varying Cardiovascular Control

    NASA Astrophysics Data System (ADS)

    Valenza, Gaetano; Citi, Luca; Garcia, Ronald G.; Taylor, Jessica Noggle; Toschi, Nicola; Barbieri, Riccardo

    2017-02-01

    The application of complex systems theory to physiology and medicine has provided meaningful information about the nonlinear aspects underlying the dynamics of a wide range of biological processes and their disease-related aberrations. However, no studies have investigated whether meaningful information can be extracted by quantifying second-order moments of time-varying cardiovascular complexity. To this extent, we introduce a novel mathematical framework termed complexity variability, in which the variance of instantaneous Lyapunov spectra estimated over time serves as a reference quantifier. We apply the proposed methodology to four exemplary studies involving disorders which stem from cardiology, neurology and psychiatry: Congestive Heart Failure (CHF), Major Depression Disorder (MDD), Parkinson’s Disease (PD), and Post-Traumatic Stress Disorder (PTSD) patients with insomnia under a yoga training regime. We show that complexity assessments derived from simple time-averaging are not able to discern pathology-related changes in autonomic control, and we demonstrate that between-group differences in measures of complexity variability are consistent across pathologies. Pathological states such as CHF, MDD, and PD are associated with an increased complexity variability when compared to healthy controls, whereas wellbeing derived from yoga in PTSD is associated with lower time-variance of complexity.

  4. Modeling of Time Varying Slag Flow in Coal Gasifiers

    SciTech Connect

    Pilli, Siva Prasad; Johnson, Kenneth I.; Williford, Ralph E.; Sundaram, S. K.; Korolev, Vladimir N.; Crum, Jarrod V.

    2008-08-30

    There is considerable interest within government agencies and the energy industries across the globe to further advance the clean and economical conversion of coal into liquid fuels to reduce our dependency on imported oil. To date, advances in these areas have been largely based on experimental work. Although there are some detailed systems level performance models, little work has been done on numerical modeling of the component level processes. If accurate models are developed, then significant R&D time might be saved, new insights into the process might be gained, and some good predictions of process or performance can be made. One such area is the characterization of slag deposition and flow on the gasifier walls. Understanding slag rheology and slag-refractory interactions is critical to design and operation of gasifiers with extended refractory lifetimes and also to better control of operating parameters so that the overall gasifier performance with extended service life can be optimized. In the present work, the literature on slag flow modeling was reviewed and a model similar to Seggiani’s was developed to simulate the time varying slag accumulation and flow on the walls of a Prenflo coal gasifier. This model was further extended and modified to simulate a refractory wall gasifier including heat transfer through the refractory wall with flowing slag in contact with the refractory. The model was used to simulate temperature dependent slag flow using rheology data from our experimental slag testing program. These modeling results as well as experimental validation are presented.

  5. Spatiotemporal Distributions of Migratory Birds: Patchy Models with Delay

    NASA Astrophysics Data System (ADS)

    Gourley, Stephen A.; Liu, Rongsong; Wu, Jianhong

    2010-01-01

    We derive and analyze a mathematical model for the spatiotemporal distribution of a migratory bird species. The birds have specific sites for breeding and winter feeding, and usually several stopover sites along the migration route, and therefore a patch model is the natural choice. However, we also model the journeys of the birds along the flyways, and this is achieved using a continuous space model of reaction-advection type. In this way proper account is taken of flight times and in-flight mortalities which may vary from sector to sector, and this information is featured in the ordinary differential equations for the populations on the patches through the values of the time delays and the model coefficients. The seasonality of the phenomenon is accommodated by having periodic migration and birth rates. The central result of the paper is a very general theorem on the threshold dynamics, obtained using recent results on discrete monotone dynamical systems, for birth functions which are subhomogeneous. For such functions, depending on the spectral radius of a certain operator, either there is a globally attracting periodic solution, or the bird population becomes extinct. Evaluation of the spectral radius is difficult, so we also present, for the particular case of just one stopover site on the migration route, a verifiable sufficient condition for extinction or survival in the form of an attractive periodic solution. This threshold is illustrated numerically using data from the U.S. Geological Survey on the bar-headed goose and its migration to India from its main breeding sites around Lake Qinghai and Mongolia.

  6. Stability and bifurcation analysis for the Kaldor-Kalecki model with a discrete delay and a distributed delay

    NASA Astrophysics Data System (ADS)

    Yu, Jinchen; Peng, Mingshu

    2016-10-01

    In this paper, a Kaldor-Kalecki model of business cycle with both discrete and distributed delays is considered. With the corresponding characteristic equation analyzed, the local stability of the positive equilibrium is investigated. It is found that there exist Hopf bifurcations when the discrete time delay passes a sequence of critical values. By applying the method of multiple scales, the explicit formulae which determine the direction of Hopf bifurcation and the stability of bifurcating periodic solutions are derived. Finally, numerical simulations are carried out to illustrate our main results.

  7. Stochastic processes with distributed delays: chemical Langevin equation and linear-noise approximation.

    PubMed

    Brett, Tobias; Galla, Tobias

    2013-06-21

    We develop a systematic approach to the linear-noise approximation for stochastic reaction systems with distributed delays. Unlike most existing work our formalism does not rely on a master equation; instead it is based upon a dynamical generating functional describing the probability measure over all possible paths of the dynamics. We derive general expressions for the chemical Langevin equation for a broad class of non-Markovian systems with distributed delay. Exemplars of a model of gene regulation with delayed autoinhibition and a model of epidemic spread with delayed recovery provide evidence of the applicability of our results.

  8. Time-varying priority queuing models for human dynamics

    NASA Astrophysics Data System (ADS)

    Jo, Hang-Hyun; Pan, Raj Kumar; Kaski, Kimmo

    2012-06-01

    Queuing models provide insight into the temporal inhomogeneity of human dynamics, characterized by the broad distribution of waiting times of individuals performing tasks. We theoretically study the queuing model of an agent trying to execute a task of interest, the priority of which may vary with time due to the agent's “state of mind.” However, its execution is disrupted by other tasks of random priorities. By considering the priority of the task of interest either decreasing or increasing algebraically in time, we analytically obtain and numerically confirm the bimodal and unimodal waiting time distributions with power-law decaying tails, respectively. These results are also compared to the updating time distribution of papers in arXiv.org and the processing time distribution of papers in Physical Review journals. Our analysis helps to understand human task execution in a more realistic scenario.

  9. ICASE/LaRC Symposium on Visualizing Time-Varying Data

    NASA Technical Reports Server (NTRS)

    Banks, D. C. (Editor); Crockett, T. W. (Editor); Stacy, K. (Editor)

    1996-01-01

    Time-varying datasets present difficult problems for both analysis and visualization. For example, the data may be terabytes in size, distributed across mass storage systems at several sites, with time scales ranging from femtoseconds to eons. In response to these challenges, ICASE and NASA Langley Research Center, in cooperation with ACM SIGGRAPH, organized the first symposium on visualizing time-varying data. The purpose was to bring the producers of time-varying data together with visualization specialists to assess open issues in the field, present new solutions, and encourage collaborative problem-solving. These proceedings contain the peer-reviewed papers which were presented at the symposium. They cover a broad range of topics, from methods for modeling and compressing data to systems for visualizing CFD simulations and World Wide Web traffic. Because the subject matter is inherently dynamic, a paper proceedings cannot adequately convey all aspects of the work. The accompanying video proceedings provide additional context for several of the papers.

  10. Multi-carrier Communications over Time-varying Acoustic Channels

    NASA Astrophysics Data System (ADS)

    Aval, Yashar M.

    Acoustic communication is an enabling technology for many autonomous undersea systems, such as those used for ocean monitoring, offshore oil and gas industry, aquaculture, or port security. There are three main challenges in achieving reliable high-rate underwater communication: the bandwidth of acoustic channels is extremely limited, the propagation delays are long, and the Doppler distortions are more pronounced than those found in wireless radio channels. In this dissertation we focus on assessing the fundamental limitations of acoustic communication, and designing efficient signal processing methods that cam overcome these limitations. We address the fundamental question of acoustic channel capacity (achievable rate) for single-input-multi-output (SIMO) acoustic channels using a per-path Rician fading model, and focusing on two scenarios: narrowband channels where the channel statistics can be approximated as frequency- independent, and wideband channels where the nominal path loss is frequency-dependent. In each scenario, we compare several candidate power allocation techniques, and show that assigning uniform power across all frequencies for the first scenario, and assigning uniform power across a selected frequency-band for the second scenario, are the best practical choices in most cases, because the long propagation delay renders the feedback information outdated for power allocation based on the estimated channel response. We quantify our results using the channel information extracted form the 2010 Mobile Acoustic Communications Experiment (MACE'10). Next, we focus on achieving reliable high-rate communication over underwater acoustic channels. Specifically, we investigate orthogonal frequency division multiplexing (OFDM) as the state-of-the-art technique for dealing with frequency-selective multipath channels, and propose a class of methods that compensate for the time-variation of the underwater acoustic channel. These methods are based on multiple

  11. Statistical-Mechanical Analysis of LMS Algorithm for Time-Varying Unknown System

    NASA Astrophysics Data System (ADS)

    Ishibushi, Norihiro; Kajikawa, Yoshinobu; Miyoshi, Seiji

    2017-02-01

    We analyze the behaviors of the least-mean-square algorithm for a time-varying unknown system using a statistical-mechanical method. Cross-correlations between the elements of a primary path and those of an adaptive filter and autocorrelations of the elements of the adaptive filter are treated as macroscopic variables. We obtain simultaneous differential equations that describe the dynamical behaviors of the macroscopic variables under conditions in which the tapped delay line is sufficiently long. We analytically show the existence of an optimal step size. This result is supporting evidence of Widrow et al.'s pioneering work that clarified the trade-off between the noise misadjustment and the lag misadjustment. Furthermore, we obtain the exact solution of the optimal step size in the case of a white reference signal. The derived theory includes the behaviors for a time-constant unknown system as a special case.

  12. Theory of electromagnetic cyclotron wave growth in a time-varying magnetoplasma

    NASA Technical Reports Server (NTRS)

    Gail, William B.

    1990-01-01

    The effect of a time-dependent perturbation in the magnetoplasma on the wave and particle populations is investigated using the Kennel-Petchek (1966) approach. Perturbations in the cold plasma density, energetic particle distribution, and resonance condition are calculated on the basis of the ideal MHD assumption given an arbitrary compressional magnetic field perturbation. An equation is derived describing the time-dependent growth rate for parallel propagating electromagnetic cyclotron waves in a time-varying magnetoplasma with perturbations superimposed on an equilibrium configuration.

  13. Integrated planning problem in supply chains with time-varying delivery

    NASA Astrophysics Data System (ADS)

    Wang, Hai-ying; Liu, Da-cheng; Ding, Hua; Guo, Fu

    2011-10-01

    We consider a serial supply chain consisting of a raw material supplier, a manufacturer, a distribution centre and a retailer in the presence of time-varying delivery between manufacturer facility and the retailer warehouse. Delivery time functions are developed based on practical data analysis and the cost models for both linear and non-linear delivery time functions are derived. Analytic solution for system with linear delivery times is derived and a search algorithm for system with non-linear delivery times is established. Finally, sensitivity analysis is made to help decision makers achieve a lower total cost in practice.

  14. An observer-based compensator for distributed delays in integrated control systems

    NASA Technical Reports Server (NTRS)

    Luck, Rogelio; Ray, Asok

    1989-01-01

    This paper presents an algorithm for compensation of delays that are distributed within a control loop. The observer-based algorithm is especially suitable for compensating network-induced delays that are likely to occur in integrated control systems of the future generation aircraft. The robustness of the algorithm relative to uncertainties in the plant model have been examined.

  15. Hubble expansion and structure formation in time varying vacuum models

    SciTech Connect

    Basilakos, Spyros; Plionis, Manolis; Sola, Joan

    2009-10-15

    {lambda}{proportional_to}H model) in which clusters form at significantly earlier times (z{>=}4) with respect to all other models (z{approx}2). Finally, we derived the theoretically predicted dark matter halo mass function and the corresponding distribution of cluster-size halos for all the models studied. Their expected redshift distribution indicates that it will be difficult to distinguish the closely resembling models (constant vacuum, quantum field, and power law vacuum), using realistic future x-ray surveys of cluster abundances. However, cluster surveys based on the Sunayev-Zeldovich detection method give some hope to distinguish the closely resembling models at high redshifts.

  16. Spherical collapse model in time varying vacuum cosmologies

    SciTech Connect

    Basilakos, Spyros; Plionis, Manolis; Sola, Joan

    2010-10-15

    We investigate the virialization of cosmic structures in the framework of flat Friedmann-Lemaitre-Robertson-Walker cosmological models, in which the vacuum energy density evolves with time. In particular, our analysis focuses on the study of spherical matter perturbations, as they decouple from the background expansion, 'turn around', and finally collapse. We generalize the spherical collapse model in the case when the vacuum energy is a running function of the Hubble rate, {Lambda}={Lambda}(H). A particularly well-motivated model of this type is the so-called quantum field vacuum, in which {Lambda}(H) is a quadratic function, {Lambda}(H)=n{sub 0}+n{sub 2}H{sup 2}, with n{sub 0{ne}}0. This model was previously studied by our team using the latest high quality cosmological data to constrain its free parameters, as well as the predicted cluster formation rate. It turns out that the corresponding Hubble expansion history resembles that of the traditional {Lambda}CDM cosmology. We use this {Lambda}(t)CDM framework to illustrate the fact that the properties of the spherical collapse model (virial density, collapse factor, etc.) depend on the choice of the considered vacuum energy (homogeneous or clustered). In particular, if the distribution of the vacuum energy is clustered, then, under specific conditions, we can produce more concentrated structures with respect to the homogeneous vacuum energy case.

  17. The Type Ia Supernova Rate and Delay-Time Distribution

    NASA Astrophysics Data System (ADS)

    Graur, Or

    2013-11-01

    The nature of the progenitor stellar systems of thermonuclear, or Type Ia, supernovae (SNe Ia) remains unknown. Unlike core-collapse (CC) SNe, which have been successfully linked, at least partially, to various types of massive stars, the progenitors of SNe Ia are to date undetected in pre-explosion images and the nature of these progenitors can only be probed using indirect methods. In this thesis, I present three SN surveys aimed at measuring the rates at which SNe Ia explode at different times throughout the Universe's history and in different types of galaxies. I use these rates to re-construct the SN Ia delay-time distribution (DTD), a function that connects between the star-formation history (SFH) of a specific stellar environment and its SN Ia rate, and I use it to constrain different progenitor models. In Chapter 1, I provide a brief introduction of the field. This is followed, in Chapter 2, by a description of the Subaru Deep Field (SDF) SN Survey. Over a period of three years between 2005-2008, the SDF was observed on four independent epochs with Suprime-Cam on the Subaru 8.2-m telescope, with two nights of exposure per epoch, in the R, i', and z' bands. In this survey, I discover 150 SNe out to redshift z ~ 2, including 27 SNe Ia in the range 1.0 < z < 1.5 and 10 in the range 1.5 < z < 2.0. The SN Ia rate measurements from this sample are consistent with those derived from the Hubble Space Telescope (HST) GOODS sample, but the overall uncertainty of the 1.5 < z < 2.0 measurement is a factor of 2 smaller, of 35-50%. Based on this sample, we find that the SN Ia rate evolution levels off at 1.0 < z < 2.0, but shows no sign of declining. Combining our SN Ia rate measurements and those from the literature, and comparing to a wide range of possible SFHs, the best-fitting DTD is a power law of the form Psi(t) ~ t^beta, with index beta = -1.1 ± 0.1 (statistical) ± 0.17 (systematic). By combining the contribution from CC SNe, based on the wide range of SFHs

  18. A Parallel Pipelined Renderer for the Time-Varying Volume Data

    NASA Technical Reports Server (NTRS)

    Chiueh, Tzi-Cker; Ma, Kwan-Liu

    1997-01-01

    This paper presents a strategy for efficiently rendering time-varying volume data sets on a distributed-memory parallel computer. Time-varying volume data take large storage space and visualizing them requires reading large files continuously or periodically throughout the course of the visualization process. Instead of using all the processors to collectively render one volume at a time, a pipelined rendering process is formed by partitioning processors into groups to render multiple volumes concurrently. In this way, the overall rendering time may be greatly reduced because the pipelined rendering tasks are overlapped with the I/O required to load each volume into a group of processors; moreover, parallelization overhead may be reduced as a result of partitioning the processors. We modify an existing parallel volume renderer to exploit various levels of rendering parallelism and to study how the partitioning of processors may lead to optimal rendering performance. Two factors which are important to the overall execution time are re-source utilization efficiency and pipeline startup latency. The optimal partitioning configuration is the one that balances these two factors. Tests on Intel Paragon computers show that in general optimal partitionings do exist for a given rendering task and result in 40-50% saving in overall rendering time.

  19. Least expected time paths in stochastic, time-varying transportation networks

    SciTech Connect

    Miller-Hooks, E.D.; Mahmassani, H.S.

    1999-06-01

    The authors consider stochastic, time-varying transportation networks, where the arc weights (arc travel times) are random variables with probability distribution functions that vary with time. Efficient procedures are widely available for determining least time paths in deterministic networks. In stochastic but time-invariant networks, least expected time paths can be determined by setting each random arc weight to its expected value and solving an equivalent deterministic problem. This paper addresses the problem of determining least expected time paths in stochastic, time-varying networks. Two procedures are presented. The first procedure determines the a priori least expected time paths from all origins to a single destination for each departure time in the peak period. The second procedure determines lower bounds on the expected times of these a priori least expected time paths. This procedure determines an exact solution for the problem where the driver is permitted to react to revealed travel times on traveled links en route, i.e. in a time-adaptive route choice framework. Modifications to each of these procedures for determining least expected cost (where cost is not necessarily travel time) paths and lower bounds on the expected costs of these paths are given. Extensive numerical tests are conducted to illustrate the algorithms` computational performance as well as the properties of the solution.

  20. Stability and Hopf bifurcation for a regulated logistic growth model with discrete and distributed delays

    NASA Astrophysics Data System (ADS)

    Fang, Shengle; Jiang, Minghui

    2009-12-01

    In this paper, we investigate the stability and Hopf bifurcation of a new regulated logistic growth with discrete and distributed delays. By choosing the discrete delay τ as a bifurcation parameter, we prove that the system is locally asymptotically stable in a range of the delay and Hopf bifurcation occurs as τ crosses a critical value. Furthermore, explicit algorithm for determining the direction of the Hopf bifurcation and the stability of the bifurcating periodic solutions is derived by normal form theorem and center manifold argument. Finally, an illustrative example is also given to support the theoretical results.

  1. Dynamics of the logistic delay equation with a large spatially distributed control coefficient

    NASA Astrophysics Data System (ADS)

    Kashchenko, I. S.; Kashchenko, S. A.

    2014-05-01

    The local dynamics of the logistic delay equation with a large spatially distributed control coefficient is asymptotically studied. The basic bifurcation scenarios are analyzed depending on the relations between the parameters of the equation. It is shown that the equilibrium states can lose stability even for asymptotically small values of the delay parameter. The corresponding critical cases can have an infinite dimension. Special nonlinear parabolic equations are constructed whose nonlocal dynamics determine the local behavior of solutions to the original boundary value problem.

  2. Time-Varying Transition Probability Matrix Estimation and Its Application to Brand Share Analysis

    PubMed Central

    Chiba, Tomoaki; Akaho, Shotaro; Murata, Noboru

    2017-01-01

    In a product market or stock market, different products or stocks compete for the same consumers or purchasers. We propose a method to estimate the time-varying transition matrix of the product share using a multivariate time series of the product share. The method is based on the assumption that each of the observed time series of shares is a stationary distribution of the underlying Markov processes characterized by transition probability matrices. We estimate transition probability matrices for every observation under natural assumptions. We demonstrate, on a real-world dataset of the share of automobiles, that the proposed method can find intrinsic transition of shares. The resulting transition matrices reveal interesting phenomena, for example, the change in flows between TOYOTA group and GM group for the fiscal year where TOYOTA group’s sales beat GM’s sales, which is a reasonable scenario. PMID:28076383

  3. Recursive state estimation for discrete time-varying stochastic nonlinear systems with randomly occurring deception attacks

    NASA Astrophysics Data System (ADS)

    Ding, Derui; Shen, Yuxuan; Song, Yan; Wang, Yongxiong

    2016-07-01

    This paper is concerned with the state estimation problem for a class of discrete time-varying stochastic nonlinear systems with randomly occurring deception attacks. The stochastic nonlinearity described by statistical means which covers several classes of well-studied nonlinearities as special cases is taken into discussion. The randomly occurring deception attacks are modelled by a set of random variables obeying Bernoulli distributions with given probabilities. The purpose of the addressed state estimation problem is to design an estimator with hope to minimize the upper bound for estimation error covariance at each sampling instant. Such an upper bound is minimized by properly designing the estimator gain. The proposed estimation scheme in the form of two Riccati-like difference equations is of a recursive form. Finally, a simulation example is exploited to demonstrate the effectiveness of the proposed scheme.

  4. Time-Varying Transition Probability Matrix Estimation and Its Application to Brand Share Analysis.

    PubMed

    Chiba, Tomoaki; Hino, Hideitsu; Akaho, Shotaro; Murata, Noboru

    2017-01-01

    In a product market or stock market, different products or stocks compete for the same consumers or purchasers. We propose a method to estimate the time-varying transition matrix of the product share using a multivariate time series of the product share. The method is based on the assumption that each of the observed time series of shares is a stationary distribution of the underlying Markov processes characterized by transition probability matrices. We estimate transition probability matrices for every observation under natural assumptions. We demonstrate, on a real-world dataset of the share of automobiles, that the proposed method can find intrinsic transition of shares. The resulting transition matrices reveal interesting phenomena, for example, the change in flows between TOYOTA group and GM group for the fiscal year where TOYOTA group's sales beat GM's sales, which is a reasonable scenario.

  5. Stability Analysis of SIR Model with Distributed Delay on Complex Networks

    PubMed Central

    Huang, Chuangxia; Cao, Jie; Wen, Fenghua; Yang, Xiaoguang

    2016-01-01

    In this paper, by taking full consideration of distributed delay, demographics and contact heterogeneity of the individuals, we present a detailed analytical study of the Susceptible-Infected-Removed (SIR) epidemic model on complex population networks. The basic reproduction number R0 of the model is dominated by the topology of the underlying network, the properties of individuals which include birth rate, death rate, removed rate and infected rate, and continuously distributed time delay. By constructing suitable Lyapunov functional and employing Kirchhoff’s matrix tree theorem, we investigate the globally asymptotical stability of the disease-free and endemic equilibrium points. Specifically, the system shows threshold behaviors: if R0≤1, then the disease-free equilibrium is globally asymptotically stable, otherwise the endemic equilibrium is globally asymptotically stable. Furthermore, the obtained results show that SIR models with different types of delays have different converge time in the process of contagion: if R0>1, then the system with distributed time delay stabilizes fastest; while R0≤1, the system with distributed time delay converges most slowly. The validness and effectiveness of these results are demonstrated through numerical simulations. PMID:27490363

  6. Stability Analysis of SIR Model with Distributed Delay on Complex Networks.

    PubMed

    Huang, Chuangxia; Cao, Jie; Wen, Fenghua; Yang, Xiaoguang

    2016-01-01

    In this paper, by taking full consideration of distributed delay, demographics and contact heterogeneity of the individuals, we present a detailed analytical study of the Susceptible-Infected-Removed (SIR) epidemic model on complex population networks. The basic reproduction number [Formula: see text] of the model is dominated by the topology of the underlying network, the properties of individuals which include birth rate, death rate, removed rate and infected rate, and continuously distributed time delay. By constructing suitable Lyapunov functional and employing Kirchhoff's matrix tree theorem, we investigate the globally asymptotical stability of the disease-free and endemic equilibrium points. Specifically, the system shows threshold behaviors: if [Formula: see text], then the disease-free equilibrium is globally asymptotically stable, otherwise the endemic equilibrium is globally asymptotically stable. Furthermore, the obtained results show that SIR models with different types of delays have different converge time in the process of contagion: if [Formula: see text], then the system with distributed time delay stabilizes fastest; while [Formula: see text], the system with distributed time delay converges most slowly. The validness and effectiveness of these results are demonstrated through numerical simulations.

  7. Window-Based Channel Impulse Response Prediction for Time-Varying Ultra-Wideband Channels

    PubMed Central

    Al-Samman, A. M.; Azmi, M. H.; Rahman, T. A.; Khan, I.; Hindia, M. N.; Fattouh, A.

    2016-01-01

    This work proposes channel impulse response (CIR) prediction for time-varying ultra-wideband (UWB) channels by exploiting the fast movement of channel taps within delay bins. Considering the sparsity of UWB channels, we introduce a window-based CIR (WB-CIR) to approximate the high temporal resolutions of UWB channels. A recursive least square (RLS) algorithm is adopted to predict the time evolution of the WB-CIR. For predicting the future WB-CIR tap of window wk, three RLS filter coefficients are computed from the observed WB-CIRs of the left wk−1, the current wk and the right wk+1 windows. The filter coefficient with the lowest RLS error is used to predict the future WB-CIR tap. To evaluate our proposed prediction method, UWB CIRs are collected through measurement campaigns in outdoor environments considering line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. Under similar computational complexity, our proposed method provides an improvement in prediction errors of approximately 80% for LOS and 63% for NLOS scenarios compared with a conventional method. PMID:27992445

  8. Time-varying formation control for double-integrator multi-agent systems with jointly connected topologies

    NASA Astrophysics Data System (ADS)

    Dong, Xiwang; Han, Liang; Li, Qingdong; Ren, Zhang

    2016-12-01

    Time-varying formation analysis and design problems for double-integrator multi-agent systems with jointly connected topologies are investigated. Different from the previous work on formation control, in this paper, the formation is specified by time-varying piecewise continuously differentiable vectors and the topology can be disconnected at any time instant. First, a distributed formation control protocol is constructed using local neighbour-to-neighbour information. In the case where the switching topology is jointly connected, necessary and sufficient conditions for double-integrator multi-agent systems to achieve time-varying formations are proposed, where the formation feasibility constraint is also derived. To describe the macroscopic movement of the whole formation, explicit expressions of the formation reference are presented, the motion modes of which can be partially assigned. Moreover, an approach to design the formation control protocol is given, which is fully distributed and requires no global information about the topology. Finally, the obtained theoretical results are applied to deal with the time-varying formation control problems of multi-vehicle systems.

  9. Synchronization transmission of spatiotemporal chaotic signal in the uncertain time-varying network

    NASA Astrophysics Data System (ADS)

    Lü, Ling; Chen, Liansong; Han, Changhui; Ge, Lianjun; Gao, Liyu

    2017-02-01

    In this paper, a new method is presented for the synchronization transmission of spatiotemporal chaotic signal in the uncertain time-varying network. By designing a special function to construct the Lyapunov function of the network, it is sure that the uncertain time-varying network can effectively synchronize the spatiotemporal chaotic signal generated by the synchronization target. At the same time, we also design the identification laws of uncertain parameters and the adaptive laws of the time-varying coupling matrix elements. Especially in our work, the nodes of the uncertain time-varying network and the synchronization target are different. Obviously, this research has the reference value for the application fields.

  10. A multiscale MDCT image-based breathing lung model with time-varying regional ventilation

    SciTech Connect

    Yin, Youbing; Choi, Jiwoong; Hoffman, Eric A.; Tawhai, Merryn H.; Lin, Ching-Long

    2013-07-01

    A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C{sub 1} continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.

  11. A multiscale MDCT image-based breathing lung model with time-varying regional ventilation

    NASA Astrophysics Data System (ADS)

    Yin, Youbing; Choi, Jiwoong; Hoffman, Eric A.; Tawhai, Merryn H.; Lin, Ching-Long

    2013-07-01

    A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C1 continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.

  12. Reliable H∞ filtering for discrete piecewise linear systems with infinite distributed delays

    NASA Astrophysics Data System (ADS)

    Wei, Guoliang; Han, Fei; Wang, Licheng; Song, Yan

    2014-05-01

    This paper is concerned with the reliable H∞ filtering problem for discrete-time piecewise linear systems subject to sensor failures and time delays. The considered sensor failures are depicted by bounded variables taking value on a certain interval. The time delays are assumed to be infinitely distributed in the discrete-time domain. The purpose of the addressed reliable H∞ filtering problem is to design a piecewise linear filter such that, for the admissible sensor failures and possible infinite distributed delays, the augmented dynamics is exponentially stable and the H∞ performance is guaranteed with a prescribed attenuation level γ. With the aid of the convex optimal method, the filter parameters are obtained in terms of the solution to a set of LMIs which can be solved by the Matlab Toolbox. At last, an illustrative simulation is presented to demonstrate the effectiveness and applicability of the proposed algorithms.

  13. Distributed Consensus of Stochastic Delayed Multi-agent Systems Under Asynchronous Switching.

    PubMed

    Wu, Xiaotai; Tang, Yang; Cao, Jinde; Zhang, Wenbing

    2016-08-01

    In this paper, the distributed exponential consensus of stochastic delayed multi-agent systems with nonlinear dynamics is investigated under asynchronous switching. The asynchronous switching considered here is to account for the time of identifying the active modes of multi-agent systems. After receipt of confirmation of mode's switching, the matched controller can be applied, which means that the switching time of the matched controller in each node usually lags behind that of system switching. In order to handle the coexistence of switched signals and stochastic disturbances, a comparison principle of stochastic switched delayed systems is first proved. By means of this extended comparison principle, several easy to verified conditions for the existence of an asynchronously switched distributed controller are derived such that stochastic delayed multi-agent systems with asynchronous switching and nonlinear dynamics can achieve global exponential consensus. Two examples are given to illustrate the effectiveness of the proposed method.

  14. Propagation of a laser beam in a time-varying waveguide. [plasma heating for controlled fusion

    NASA Technical Reports Server (NTRS)

    Chapman, J. M.; Kevorkian, J.

    1978-01-01

    The propagation of an axisymmetric laser beam in a plasma column having a radially parabolic electron density distribution is reported. For the case of an axially uniform waveguide it is found that the basic characteristics of alternating focusing and defocusing beams are maintained. However, the intensity distribution is changed at the foci and outer-beam regions. The features of paraxial beam propagation are discussed with reference to axially varying waveguides. Laser plasma coupling is considered noting the case where laser heating produces a density distribution radially parabolic near the axis and the energy absorbed over the focal length of the plasma is small. It is found that: (1) beam-propagation stability is governed by the relative magnitude of the density fluctuations existing in the axial variation of the waveguides due to laser heating, and (2) for beam propagation in a time-varying waveguide, the global instability of the propagation is a function of the initial fluctuation growth rate as compared to the initial time rate of change in the radial curvature of the waveguide.

  15. Distributed output regulation for linear multi-agent systems with communication delays

    NASA Astrophysics Data System (ADS)

    Yu, Lu; Wang, Jinzhi

    2015-11-01

    In this paper, a distributed output regulation approach is presented for the cooperative control of linear multi-agent systems in the presence of communication delays. Both dynamic state and output feedback control laws are designed for achieving the property of output regulation. Sufficient conditions for the existence of these control laws are provided in terms of linear matrix inequalities. Simulation results are given to support the efficiency of the proposed distributed output regulation approach.

  16. Identification of Time-Varying Pilot Control Behavior in Multi-Axis Control Tasks

    NASA Technical Reports Server (NTRS)

    Zaal, Peter M. T.; Sweet, Barbara T.

    2012-01-01

    Recent developments in fly-by-wire control architectures for rotorcraft have introduced new interest in the identification of time-varying pilot control behavior in multi-axis control tasks. In this paper a maximum likelihood estimation method is used to estimate the parameters of a pilot model with time-dependent sigmoid functions to characterize time-varying human control behavior. An experiment was performed by 9 general aviation pilots who had to perform a simultaneous roll and pitch control task with time-varying aircraft dynamics. In 8 different conditions, the axis containing the time-varying dynamics and the growth factor of the dynamics were varied, allowing for an analysis of the performance of the estimation method when estimating time-dependent parameter functions. In addition, a detailed analysis of pilots adaptation to the time-varying aircraft dynamics in both the roll and pitch axes could be performed. Pilot control behavior in both axes was significantly affected by the time-varying aircraft dynamics in roll and pitch, and by the growth factor. The main effect was found in the axis that contained the time-varying dynamics. However, pilot control behavior also changed over time in the axis not containing the time-varying aircraft dynamics. This indicates that some cross coupling exists in the perception and control processes between the roll and pitch axes.

  17. Effects of Paleoclimate and Time-Varying Canopy Structures on Paleo-Water Fluxes

    NASA Astrophysics Data System (ADS)

    Yin, J.; Young, M. H.; Yu, Z.

    2007-12-01

    We combined a long-term (18,000 years) climatological record and time-varying vegetation conditions to evaluate the role that climate change and vegetation might play in paleo-water fluxes in arid settings. The HYDRUS-1D model, which solves Richards Equation for variably saturated flow, the convection-dispersion equation for chloride transport and the heat flow equation, was used to simulate water flux and chloride (Cl) transport. Six distinct case studies were compared, for different boundary conditions and root distributions. A Mojave Desert- type canopy including evergreens, drought deciduous shrubs, annuals, grasses, and succulents was used as representative vegetation to transpire soil water, and was modeled using ground cover percentage and leaf area index (LAI) as the bases for partitioning evapotranspiration (ET). The results showed that, under water limited conditions, realistic root zone distributions and climate sequences (including extreme events) were both needed to simulate the accumulation of Cl in Mojave Desert soils. Results also showed that increasing precipitation intensity affected paleo-water fluxes. However, contrary to the results of other researchers, we found that simulated chloride bulges were located at depths of around 20-30 cm, rather than at the base of the root zone, if current and normal climate conditions were applied. Moreover, the climatic shift beginning in the late Pleistocene was not the major reason for the chloride accumulation.

  18. Effects of paleoclimate and time-varying canopy structures on paleowater fluxes

    NASA Astrophysics Data System (ADS)

    Yin, Jun; Young, Michael H.; Yu, Zhongbo

    2008-03-01

    We combined a long-term (18,000 years) climatological record and time-varying vegetation conditions to evaluate the role that climate change and vegetation might play in paleowater fluxes in arid settings. The HYDRUS-1D model, which solves Richards Equation for variably saturated flow, the convection-dispersion equation for chloride transport and the heat flow equation, was used to simulate water flux and chloride (Cl) transport. Six distinct case studies were compared for different boundary conditions and root distributions. A Mojave Desert-type canopy including evergreens, drought deciduous shrubs, annuals, grasses, and succulents was used as representative vegetation to transpire soil water and was modeled using ground cover percentage and leaf area index (LAI) as the bases for partitioning evapotranspiration (ET). The results showed that under water limited conditions, realistic root zone distributions and climate sequences (including extreme events) were both needed to simulate the accumulation of Cl in Mojave Desert soils. Results also showed that increasing precipitation intensity affected paleowater fluxes. However, contrary to the results of other researchers, we found that simulated chloride bulges were located at depths of around 20-30 cm, rather than at the base of the root zone, if current and normal climate conditions were applied. Moreover, the climatic shift beginning in the late Pleistocene was not the major reason for the chloride accumulation.

  19. Time-Varying Network Measures in Resting and Task States Using Graph Theoretical Analysis.

    PubMed

    Yang, Chia-Yen; Lin, Ching-Po

    2015-07-01

    Recent studies have shown the importance of graph theory in analyzing characteristic features of functional networks of the human brain. However, many of these explorations have focused on static patterns of a representative graph that describe the relatively long-term brain activity. Therefore, this study established and characterized functional networks based on the synchronization likelihood and graph theory. Quasidynamic graphs were constructed simply by dividing a long-term static graph into a sequence of subgraphs that each had a timescale of 1 s. Irregular changes were then used to investigate differences in human brain networks between resting and math-operation states using magnetoencephalography, which may provide insights into the functional substrates underlying logical reasoning. We found that graph properties could differ from brain frequency rhythms, with a higher frequency indicating a lower small-worldness, while changes in human brain state altered the functional networks into more-centralized and segregated distributions according to the task requirements. Time-varying connectivity maps could provide detailed information about the structure distribution. The frontal theta activity represents the essential foundation and may subsequently interact with high-frequency activity in cognitive processing.

  20. Exponential Stability of Almost Periodic Solutions for Memristor-Based Neural Networks with Distributed Leakage Delays.

    PubMed

    Xu, Changjin; Li, Peiluan; Pang, Yicheng

    2016-12-01

    In this letter, we deal with a class of memristor-based neural networks with distributed leakage delays. By applying a new Lyapunov function method, we obtain some sufficient conditions that ensure the existence, uniqueness, and global exponential stability of almost periodic solutions of neural networks. We apply the results of this solution to prove the existence and stability of periodic solutions for this delayed neural network with periodic coefficients. We then provide an example to illustrate the effectiveness of the theoretical results. Our results are completely new and complement the previous studies Chen, Zeng, and Jiang ( 2014 ) and Jiang, Zeng, and Chen ( 2015 ).

  1. Mathematical model describing the thyroids-pituitary axis with distributed time delays in hormone transportation

    NASA Astrophysics Data System (ADS)

    Neamţu, Mihaela; Stoian, Dana; Navolan, Dan Bogdan

    2014-12-01

    In the present paper we provide a mathematical model that describe the hypothalamus-pituitary-thyroid axis in autoimmune (Hashimoto's) thyroiditis. Since there is a spatial separation between thyroid and pituitary gland in the body, time is needed for transportation of thyrotropin and thyroxine between the glands. Thus, the distributed time delays are considered as both weak and Dirac kernels. The delayed model is analyzed regarding the stability and bifurcation behavior. The last part contains some numerical simulations to illustrate the effectiveness of our results and conclusions.

  2. Length distributions of nanowires: Effects of surface diffusion versus nucleation delay

    NASA Astrophysics Data System (ADS)

    Dubrovskii, Vladimir G.

    2017-04-01

    It is often thought that the ensembles of semiconductor nanowires are uniform in length due to the initial organization of the growth seeds such as lithographically defined droplets or holes in the substrate. However, several recent works have already demonstrated that most nanowire length distributions are broader than Poissonian. Herein, we consider theoretically the length distributions of non-interacting nanowires that grow by the material collection from the entire length of their sidewalls and with a delay of nucleation of the very first nanowire monolayer. The obtained analytic length distribution is controlled by two parameters that describe the strength of surface diffusion and the nanowire nucleation rate. We show how the distribution changes from the symmetrical Polya shape without the nucleation delay to a much broader and asymmetrical one for longer delays. In the continuum limit (for tall enough nanowires), the length distribution is given by a power law times an incomplete gamma-function. We discuss interesting scaling properties of this solution and give a recipe for analyzing and tailoring the experimental length histograms of nanowires which should work for a wide range of material systems and growth conditions.

  3. A monolithic constant-fraction discriminator using distributed R-C delay-line shaping

    SciTech Connect

    Simpson, M.L.; Young, G.R.; Xu, M.

    1995-06-01

    A monolithic, CMOS, constant-fraction discriminator (CFD) was fabricated in the Orbit Semiconductor, 1.2 {mu} N-well process. This circuit uses an on-chip, distributed, R-C delay-line to realize the constant-fraction shaping. The delay-line is constructed from a narrow, 500-{mu} serpentine layer of polysilicon above a wide, grounded, second layer of polysilicon. This R-C delay-line generates about 1.1 ns of delay for 5 ns risetime signals with a slope degradation of only {approx_equal} 15% and an amplitude reduction of about 6.1%. The CFD also features an automatic walk adjustment. The entire circuit, including the delay line, has a 200 {mu} pitch and is 950 {mu} long. The walk for a 5 ns risetime signal was measured as {plus_minus} 100 ps over the 100:1 dynamic range from {minus}15 mV to {minus}1.5 mV. to {minus}1.5 V. The CFD consumes 15 mW.

  4. Dealing with the time-varying parameter problem of robot manipulators performing path tracking tasks

    NASA Technical Reports Server (NTRS)

    Song, Y. D.; Middleton, R. H.

    1992-01-01

    Many robotic applications involve time-varying payloads during the operation of the robot. It is therefore of interest to consider control schemes that deal with time-varying parameters. Using the properties of the element by element (or Hadarmad) product of matrices, we obtain the robot dynamics in parameter-isolated form, from which a new control scheme is developed. The controller proposed yields zero asymptotic tracking errors when applied to robotic systems with time-varying parameters by using a switching type control law. The results obtained are global in the initial state of the robot, and can be applied to rapidly varying systems.

  5. Non-exponential Stabilization of Linear Time-invariant Systems by Time-varying Controllers

    NASA Astrophysics Data System (ADS)

    Inoue, Masaki; Wada, Teruyo; Ikeda, Masao

    This paper proposes non-exponential stabilization of linear time-invariant systems by linear time-varying controllers. We consider state feedback and dynamic output feedback to make the states of the closed-loop systems decay non-exponentially. We first introduce a non-exponential stability concept that the state of a time-varying system converges to the origin with a bound provided by a desired function. Then, we give non-exponential stabilizability conditions and time-varying controllers to achieve the desired behavior of the closed-loop systems. By the proposed methods, we can realize various non-exponential behaviors, which may improve control performance.

  6. Decelerated invasion and waning-moon patterns in public goods games with delayed distribution

    NASA Astrophysics Data System (ADS)

    Szolnoki, Attila; Perc, Matjaž

    2013-05-01

    We study the evolution of cooperation in the spatial public goods game, focusing on the effects that are brought about by the delayed distribution of goods that accumulate in groups due to the continuous investments of cooperators. We find that intermediate delays enhance network reciprocity because of a decelerated invasion of defectors, who are unable to reap the same high short-term benefits as they do in the absence of delayed distribution. Long delays, however, introduce a risk because the large accumulated wealth might fall into the wrong hands. Indeed, as soon as the curvature of a cooperative cluster turns negative, the engulfed defectors can collect the heritage of many generations of cooperators and by doing so start a waning-moon pattern that nullifies the benefits of decelerated invasion. Accidental meeting points of growing cooperative clusters may also act as triggers for the waning-moon effect, thus linking the success of cooperators with their propensity to fail in a rather bizarre way. Our results highlight that “investing in the future” is a good idea only if that future is sufficiently near and not likely to be burdened by inflation.

  7. Decelerated invasion and waning-moon patterns in public goods games with delayed distribution.

    PubMed

    Szolnoki, Attila; Perc, Matjaž

    2013-05-01

    We study the evolution of cooperation in the spatial public goods game, focusing on the effects that are brought about by the delayed distribution of goods that accumulate in groups due to the continuous investments of cooperators. We find that intermediate delays enhance network reciprocity because of a decelerated invasion of defectors, who are unable to reap the same high short-term benefits as they do in the absence of delayed distribution. Long delays, however, introduce a risk because the large accumulated wealth might fall into the wrong hands. Indeed, as soon as the curvature of a cooperative cluster turns negative, the engulfed defectors can collect the heritage of many generations of cooperators and by doing so start a waning-moon pattern that nullifies the benefits of decelerated invasion. Accidental meeting points of growing cooperative clusters may also act as triggers for the waning-moon effect, thus linking the success of cooperators with their propensity to fail in a rather bizarre way. Our results highlight that "investing in the future" is a good idea only if that future is sufficiently near and not likely to be burdened by inflation.

  8. "Tools For Analysis and Visualization of Large Time- Varying CFD Data Sets"

    NASA Technical Reports Server (NTRS)

    Wilhelms, Jane; vanGelder, Allen

    1999-01-01

    During the four years of this grant (including the one year extension), we have explored many aspects of the visualization of large CFD (Computational Fluid Dynamics) datasets. These have included new direct volume rendering approaches, hierarchical methods, volume decimation, error metrics, parallelization, hardware texture mapping, and methods for analyzing and comparing images. First, we implemented an extremely general direct volume rendering approach that can be used to render rectilinear, curvilinear, or tetrahedral grids, including overlapping multiple zone grids, and time-varying grids. Next, we developed techniques for associating the sample data with a k-d tree, a simple hierarchial data model to approximate samples in the regions covered by each node of the tree, and an error metric for the accuracy of the model. We also explored a new method for determining the accuracy of approximate models based on the light field method described at ACM SIGGRAPH (Association for Computing Machinery Special Interest Group on Computer Graphics) '96. In our initial implementation, we automatically image the volume from 32 approximately evenly distributed positions on the surface of an enclosing tessellated sphere. We then calculate differences between these images under different conditions of volume approximation or decimation.

  9. In the interests of time: improving HIV allocative efficiency modelling via optimal time-varying allocations

    PubMed Central

    Shattock, Andrew J; Kerr, Cliff C; Stuart, Robyn M; Masaki, Emiko; Fraser, Nicole; Benedikt, Clemens; Gorgens, Marelize; Wilson, David P; Gray, Richard T

    2016-01-01

    Introduction International investment in the response to HIV and AIDS has plateaued and its future level is uncertain. With many countries committed to ending the epidemic, it is essential to allocate available resources efficiently over different response periods to maximize impact. The objective of this study is to propose a technique to determine the optimal allocation of funds over time across a set of HIV programmes to achieve desirable health outcomes. Methods We developed a technique to determine the optimal time-varying allocation of funds (1) when the future annual HIV budget is pre-defined and (2) when the total budget over a period is pre-defined, but the year-on-year budget is to be optimally determined. We use this methodology with Optima, an HIV transmission model that uses non-linear relationships between programme spending and associated programmatic outcomes to quantify the expected epidemiological impact of spending. We apply these methods to data collected from Zambia to determine the optimal distribution of resources to fund the right programmes, for the right people, at the right time. Results and discussion Considering realistic implementation and ethical constraints, we estimate that the optimal time-varying redistribution of the 2014 Zambian HIV budget between 2015 and 2025 will lead to a 7.6% (7.3% to 7.8%) decrease in cumulative new HIV infections compared with a baseline scenario where programme allocations remain at 2014 levels. This compares to a 5.1% (4.6% to 5.6%) reduction in new infections using an optimal allocation with constant programme spending that recommends unrealistic programmatic changes. Contrasting priorities for programme funding arise when assessing outcomes for a five-year funding period over 5-, 10- and 20-year time horizons. Conclusions Countries increasingly face the need to do more with the resources available. The methodology presented here can aid decision-makers in planning as to when to expand or contract

  10. Transformation of binaural response properties in the ascending auditory pathway: influence of time-varying interaural phase disparity.

    PubMed

    Spitzer, M W; Semple, M N

    1998-12-01

    motion, resulting in highly contiguous discharge profiles for overlapping stimuli. This finding indicates that responses of PL-SOC units to time-varying IPD reflect only instantaneous IPD with no additional influence of dynamic stimulus attributes. Thus the neuronal representation of auditory spatial information undergoes a major transformation as interaural delay is initially processed in the SOC and subsequently reprocessed in IC. The finding that motion sensitivity in IC emerges from motion-insensitive input suggests that information about change of position is crucial to spatial processing at higher levels of the auditory system.

  11. Robust Estimation for Neural Networks With Randomly Occurring Distributed Delays and Markovian Jump Coupling.

    PubMed

    Xu, Yong; Lu, Renquan; Shi, Peng; Tao, Jie; Xie, Shengli

    2017-01-24

    This paper studies the issue of robust state estimation for coupled neural networks with parameter uncertainty and randomly occurring distributed delays, where the polytopic model is employed to describe the parameter uncertainty. A set of Bernoulli processes with different stochastic properties are introduced to model the randomly occurrences of the distributed delays. Novel state estimators based on the local coupling structure are proposed to make full use of the coupling information. The augmented estimation error system is obtained based on the Kronecker product. A new Lyapunov function, which depends both on the polytopic uncertainty and the coupling information, is introduced to reduce the conservatism. Sufficient conditions, which guarantee the stochastic stability and the l₂-l∞ performance of the augmented estimation error system, are established. Then, the estimator gains are further obtained on the basis of these conditions. Finally, a numerical example is used to prove the effectiveness of the results.

  12. A new approach of analyzing time-varying dynamical equation via an optimal principle

    NASA Astrophysics Data System (ADS)

    Zhao, Hui; Li, Lixiang; Peng, Haipeng; Kurths, Jürgen; Xiao, Jinghua; Yang, Yixian; Li, Ang

    2017-03-01

    In this paper, an innovative design approach is proposed to solve time-varying dynamical equation, including matrix inverse equation and Sylvester equation. Based on the precondition of the existing solution of time-varying dynamical equation, different from previous approach to solve unknown matrix, an optimal design principle is used to solve the unknown variables. A performance index is introduced based on the inherent properties of the time-varying dynamical equation and Euler equation. The solution of time-varying dynamical equation is converted to an optimal problem of performance index. Furthermore, convergence and sensitivity to additive noise are also analyzed, and simulation results confirm that the method is feasible and effective. Especially, in simulations we design a tunable positive parameter in the dynamic optimization model. The tunable parameter is not only helpful to accelerate its convergence but also reduce its sensitivity to additive noise. Meanwhile the comparative simulation results are shown for the convergence accuracy and robustness of this method.

  13. JOINT STRUCTURE SELECTION AND ESTIMATION IN THE TIME-VARYING COEFFICIENT COX MODEL

    PubMed Central

    Xiao, Wei; Lu, Wenbin; Zhang, Hao Helen

    2016-01-01

    Time-varying coefficient Cox model has been widely studied and popularly used in survival data analysis due to its flexibility for modeling covariate effects. It is of great practical interest to accurately identify the structure of covariate effects in a time-varying coefficient Cox model, i.e. covariates with null effect, constant effect and truly time-varying effect, and estimate the corresponding regression coefficients. Combining the ideas of local polynomial smoothing and group nonnegative garrote, we develop a new penalization approach to achieve such goals. Our method is able to identify the underlying true model structure with probability tending to one and simultaneously estimate the time-varying coefficients consistently. The asymptotic normalities of the resulting estimators are also established. We demonstrate the performance of our method using simulations and an application to the primary biliary cirrhosis data. PMID:27540275

  14. Synthesis procedure for linear time-varying feedback systems with large parameter ignorance

    NASA Technical Reports Server (NTRS)

    Mcdonald, T. E., Jr.

    1972-01-01

    The development of synthesis procedures for linear time-varying feedback systems is considered. It is assumed that the plant can be described by linear differential equations with time-varying coefficients; however, ignorance is associated with the plant in that only the range of the time-variations are known instead of exact functional relationships. As a result of this plant ignorance the use of time-varying compensation is ineffective so that only time-invariant compensation is employed. In addition, there is a noise source at the plant output which feeds noise through the feedback elements to the plant input. Because of this noise source the gain of the feedback elements must be as small as possible. No attempt is made to develop a stability criterion for time-varying systems in this work.

  15. Necessity of Time-Varying Electromagnetic Force Consideration in MHD Calculation for Electromagnetic Stirring

    NASA Astrophysics Data System (ADS)

    Sato, Shoji; Fujisaki, Keisuke; Furukawa, Tatsuya

    In continuous casting process, MHD calculation is utilized to make clear and design the process. Previous MHD calculation takes no account of time-varying electromagnetic force which is enough smaller than mass inertia, because previous purpose is estimation of time average major flow in interior of mold. However, to improve surface quality of slab more, the dynamic behavior of free surface where the solidification begins must be made clear in detail. In this paper, we evaluated influence that time-varying electromagnetic force exerts on the flow in MHD calculation. As the result, the flow of free surface is disordered intensely by the taking into account of time-varying electromagnetic force. Therefore, time-varying electromagnetic force must be used, to make clear the dynamic behavior of free surface. However, previous MHD calculation with small computation cost suits to evaluate major flow in interior of mold, because it is same approximately in both methods.

  16. Noise Covariance Matrices Estimation for Systems with Time-Varying Availability of Sensors

    NASA Astrophysics Data System (ADS)

    Kost, Oliver; Duník, Jindřich; Straka, Ondřej

    2017-01-01

    The paper deals with the estimation of the noise covariance matrices of a time-varying system described by a state-space model with a time-varying set of sensors. In particular, the measurement difference autocovariance method, is proposed. The method is based on a statistical analysis of linearity transformed measurements leading to a system of linear matrix equations. The theoretical results are discussed and illustrated using a numerical study.

  17. Empirical mode decomposition as a time-varying multirate signal processing system

    NASA Astrophysics Data System (ADS)

    Yang, Yanli

    2016-08-01

    Empirical mode decomposition (EMD) can adaptively split composite signals into narrow subbands termed intrinsic mode functions (IMFs). Although an analytical expression of IMFs extracted by EMD from signals is introduced in Yang et al. (2013) [1], it is only used for the case of extrema spaced uniformly. In this paper, the EMD algorithm is analyzed from digital signal processing perspective for the case of extrema spaced nonuniformly. Firstly, the extrema extraction is represented by a time-varying extrema decimator. The nonuniform extrema extraction is analyzed through modeling the time-varying extrema decimation at a fixed time point as a time-invariant decimation. Secondly, by using the impulse/summation approach, spline interpolation for knots spaced nonuniformly is shown as two basic operations, time-varying interpolation and filtering by a time-varying spline filter. Thirdly, envelopes of signals are written as the output of the time-varying spline filter. An expression of envelopes of signals in both time and frequency domain is presented. The EMD algorithm is then described as a time-varying multirate signal processing system. Finally, an equation to model IMFs is derived by using a matrix formulation in time domain for the general case of extrema spaced nonuniformly.

  18. Dynamic Stability Analysis of Linear Time-varying Systems via an Extended Modal Identification Approach

    NASA Astrophysics Data System (ADS)

    Ma, Zhisai; Liu, Li; Zhou, Sida; Naets, Frank; Heylen, Ward; Desmet, Wim

    2017-03-01

    The problem of linear time-varying(LTV) system modal analysis is considered based on time-dependent state space representations, as classical modal analysis of linear time-invariant systems and current LTV system modal analysis under the "frozen-time" assumption are not able to determine the dynamic stability of LTV systems. Time-dependent state space representations of LTV systems are first introduced, and the corresponding modal analysis theories are subsequently presented via a stability-preserving state transformation. The time-varying modes of LTV systems are extended in terms of uniqueness, and are further interpreted to determine the system's stability. An extended modal identification is proposed to estimate the time-varying modes, consisting of the estimation of the state transition matrix via a subspace-based method and the extraction of the time-varying modes by the QR decomposition. The proposed approach is numerically validated by three numerical cases, and is experimentally validated by a coupled moving-mass simply supported beam experimental case. The proposed approach is capable of accurately estimating the time-varying modes, and provides a new way to determine the dynamic stability of LTV systems by using the estimated time-varying modes.

  19. Applied Time Domain Stability Margin Assessment for Nonlinear Time-Varying Systems

    NASA Technical Reports Server (NTRS)

    Kiefer, J. M.; Johnson, M. D.; Wall, J. H.; Dominguez, A.

    2016-01-01

    The baseline stability margins for NASA's Space Launch System (SLS) launch vehicle were generated via the classical approach of linearizing the system equations of motion and determining the gain and phase margins from the resulting frequency domain model. To improve the fidelity of the classical methods, the linear frequency domain approach can be extended by replacing static, memoryless nonlinearities with describing functions. This technique, however, does not address the time varying nature of the dynamics of a launch vehicle in flight. An alternative technique for the evaluation of the stability of the nonlinear launch vehicle dynamics along its trajectory is to incrementally adjust the gain and/or time delay in the time domain simulation until the system exhibits unstable behavior. This technique has the added benefit of providing a direct comparison between the time domain and frequency domain tools in support of simulation validation. This technique was implemented by using the Stability Aerospace Vehicle Analysis Tool (SAVANT) computer simulation to evaluate the stability of the SLS system with the Adaptive Augmenting Control (AAC) active and inactive along its ascent trajectory. The gains for which the vehicle maintains apparent time-domain stability defines the gain margins, and the time delay similarly defines the phase margin. This method of extracting the control stability margins from the time-domain simulation is relatively straightforward and the resultant margins can be compared to the linearized system results. The sections herein describe the techniques employed to extract the time-domain margins, compare the results between these nonlinear and the linear methods, and provide explanations for observed discrepancies. The SLS ascent trajectory was simulated with SAVANT and the classical linear stability margins were evaluated at one second intervals. The linear analysis was performed with the AAC algorithm disabled to attain baseline stability

  20. Time-varying exposure and the impact of stressful life events on onset of affective disorder.

    PubMed

    Wainwright, Nicholas W J; Surtees, Paul G

    2002-07-30

    Stressful life events are now established as risk factors for the onset of affective disorder but few studies have investigated time-varying exposure effects. Discrete (grouped) time survival methods provide a flexible framework for evaluating multiple time-dependent covariates and time-varying covariate effects. Here, we use these methods to investigate the time-varying influence of life events on the onset of affective disorder. Various straightforward time-varying exposure models are compared, involving one or more (stepped) time-dependent covariates and time-dependent covariates constructed or estimated according to exponential decay. These models are applied to data from two quite different studies. The first, a small scale interviewer-based longitudinal study (n = 180) concerned with affective disorder onset following loss (or threat of loss) event experiences. The second, a questionnaire assessment as part of an ongoing population study (n = 3353), provides a history of marital loss events and of depressive disorder onset. From the first study the initial impact of loss events was found to decay with a half-life of 5 weeks. Psychological coping strategy was found to modify vulnerability to the adverse effects of these events. The second study revealed that while men had a lower immediate risk of disorder onset following loss event experience their risk period was greater than for women. Time-varying exposure effects were well described by the appropriate use of simple time-dependent covariates.

  1. Model Predictive Optimal Control of a Time-Delay Distributed-Parameter Systems

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan

    2006-01-01

    This paper presents an optimal control method for a class of distributed-parameter systems governed by first order, quasilinear hyperbolic partial differential equations that arise in many physical systems. Such systems are characterized by time delays since information is transported from one state to another by wave propagation. A general closed-loop hyperbolic transport model is controlled by a boundary control embedded in a periodic boundary condition. The boundary control is subject to a nonlinear differential equation constraint that models actuator dynamics of the system. The hyperbolic equation is thus coupled with the ordinary differential equation via the boundary condition. Optimality of this coupled system is investigated using variational principles to seek an adjoint formulation of the optimal control problem. The results are then applied to implement a model predictive control design for a wind tunnel to eliminate a transport delay effect that causes a poor Mach number regulation.

  2. Bayesian Switching Factor Analysis for Estimating Time-varying Functional Connectivity in fMRI.

    PubMed

    Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod

    2017-03-03

    There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal

  3. Investigation of the delay time distribution of high power microwave surface flashover

    SciTech Connect

    Foster, J.; Krompholz, H.; Neuber, A.

    2011-01-15

    Characterizing and modeling the statistics associated with the initiation of gas breakdown has proven to be difficult due to a variety of rather unexplored phenomena involved. Experimental conditions for high power microwave window breakdown for pressures on the order of 100 to several 100 torr are complex: there are little to no naturally occurring free electrons in the breakdown region. The initial electron generation rate, from an external source, for example, is time dependent and so is the charge carrier amplification in the increasing radio frequency (RF) field amplitude with a rise time of 50 ns, which can be on the same order as the breakdown delay time. The probability of reaching a critical electron density within a given time period is composed of the statistical waiting time for the appearance of initiating electrons in the high-field region and the build-up of an avalanche with an inherent statistical distribution of the electron number. High power microwave breakdown and its delay time is of critical importance, since it limits the transmission through necessary windows, especially for high power, high altitude, low pressure applications. The delay time distribution of pulsed high power microwave surface flashover has been examined for nitrogen and argon as test gases for pressures ranging from 60 to 400 torr, with and without external UV illumination. A model has been developed for predicting the discharge delay time for these conditions. The results provide indications that field induced electron generation, other than standard field emission, plays a dominant role, which might be valid for other gas discharge types as well.

  4. Investigation of the delay time distribution of high power microwave surface flashover

    NASA Astrophysics Data System (ADS)

    Foster, J.; Krompholz, H.; Neuber, A.

    2011-01-01

    Characterizing and modeling the statistics associated with the initiation of gas breakdown has proven to be difficult due to a variety of rather unexplored phenomena involved. Experimental conditions for high power microwave window breakdown for pressures on the order of 100 to several 100 torr are complex: there are little to no naturally occurring free electrons in the breakdown region. The initial electron generation rate, from an external source, for example, is time dependent and so is the charge carrier amplification in the increasing radio frequency (RF) field amplitude with a rise time of 50 ns, which can be on the same order as the breakdown delay time. The probability of reaching a critical electron density within a given time period is composed of the statistical waiting time for the appearance of initiating electrons in the high-field region and the build-up of an avalanche with an inherent statistical distribution of the electron number. High power microwave breakdown and its delay time is of critical importance, since it limits the transmission through necessary windows, especially for high power, high altitude, low pressure applications. The delay time distribution of pulsed high power microwave surface flashover has been examined for nitrogen and argon as test gases for pressures ranging from 60 to 400 torr, with and without external UV illumination. A model has been developed for predicting the discharge delay time for these conditions. The results provide indications that field induced electron generation, other than standard field emission, plays a dominant role, which might be valid for other gas discharge types as well.

  5. Consensus-based distributed estimation in multi-agent systems with time delay

    NASA Astrophysics Data System (ADS)

    Abdelmawgoud, Ahmed

    During the last years, research in the field of cooperative control of swarm of robots, especially Unmanned Aerial Vehicles (UAV); have been improved due to the increase of UAV applications. The ability to track targets using UAVs has a wide range of applications not only civilian but also military as well. For civilian applications, UAVs can perform tasks including, but not limited to: map an unknown area, weather forecasting, land survey, and search and rescue missions. On the other hand, for military personnel, UAV can track and locate a variety of objects, including the movement of enemy vehicles. Consensus problems arise in a number of applications including coordination of UAVs, information processing in wireless sensor networks, and distributed multi-agent optimization. We consider a widely studied consensus algorithms for processing sensed data by different sensors in wireless sensor networks of dynamic agents. Every agent involved in the network forms a weighted average of its own estimated value of some state with the values received from its neighboring agents. We introduced a novelty of consensus-based distributed estimation algorithms. We propose a new algorithm to reach a consensus given time delay constraints. The proposed algorithm performance was observed in a scenario where a swarm of UAVs measuring the location of a ground maneuvering target. We assume that each UAV computes its state prediction and shares it with its neighbors only. However, the shared information applied to different agents with variant time delays. The entire group of UAVs must reach a consensus on target state. Different scenarios were also simulated to examine the effectiveness and performance in terms of overall estimation error, disagreement between delayed and non-delayed agents, and time to reach a consensus for each parameter contributing on the proposed algorithm.

  6. Experimental Demonstration of Frequency Autolocking an Optical Cavity Using a Time-Varying Kalman Filter

    NASA Astrophysics Data System (ADS)

    Schütte, Dirk; Hassen, S. Z. Sayed; Karvinen, Kai S.; Boyson, Toby K.; Kallapur, Abhijit G.; Song, Hongbin; Petersen, Ian R.; Huntington, Elanor H.; Heurs, Michèle

    2016-01-01

    We propose and demonstrate a new autolocking scheme using a three-mirror ring cavity consisting of a linear quadratic regulator and a time-varying Kalman filter. Our technique does not require a frequency scan to acquire resonance. We utilize the singular perturbation method to simplify our system dynamics and to permit the application of linear control techniques. The error signal combined with the transmitted power is used to estimate the cavity detuning. This estimate is used by a linear time-varying Kalman filter which enables the implementation of an optimal controller. The experimental results validate the controller design, and we demonstrate improved robustness to disturbances and a faster locking time than a traditional proportional-integral controller. More important, the time-varying Kalman filtering approach automatically reacquires lock for large detunings, where the error signal leaves its linear capture range, a feat which linear time-invariant controllers cannot achieve.

  7. On-line Parameter Estimation of Time-varying Systems by Radial Basis Function Networks

    NASA Astrophysics Data System (ADS)

    Kobayashi, Yasuhide; Tanaka, Shinichi; Okita, Tsuyoshi

    This paper proposes a new on-line parameter estimation method with radial basis function networks for time-varying linear discrete-time systems. The time-varying parameters of the system are expressed with the radial basis function networks. These parameters are estimated by the nonlinear optimization technique, and the setting rules of the initial values in the optimization are proposed. The system parameters are usually unknown because they are changed by the circumstance conditions. Then, it is reasonable that the structures of the radial basis function networks are regulated according to the change of parameters. The minimum description length criterion studied in the encoding theory is applied to select the network structures. It is demonstrated in digital simulation that the proposed on-line estimation method succeeded to reduce the computaion time extremely, for time-varying parameters system.

  8. New Stability Criteria for High-Order Neural Networks with Proportional Delays

    NASA Astrophysics Data System (ADS)

    Xu, Chang-Jin; Li, Pei-Luan

    2017-03-01

    This paper is concerned with high-order neural networks with proportional delays. The proportional delay is a time-varying unbounded delay which is different from the constant delay, bounded time-varying delay and distributed delay. By the nonlinear transformation {y}i(t)={u}i({{{e}}}t){{ }}(i=1,2,\\ldots ,n), we transform a class of high-order neural networks with proportional delays into a class of high-order neural networks with constant delays and time-varying coefficients. With the aid of Brouwer fixed point theorem and constructing the delay differential inequality, we obtain some delay-independent and delay-dependent sufficient conditions to ensure the existence, uniqueness and global exponential stability of equilibrium of the network. Two examples with their simulations are given to illustrate the theoretical findings. Our results are new and complement previously known results. Supported by National Natural Science Foundation of China under Grant Nos. 61673008 and 11261010, and Project of High-level Innovative Talents of Guizhou Province ([2016]5651)

  9. Time-varying long term memory in the European Union stock markets

    NASA Astrophysics Data System (ADS)

    Sensoy, Ahmet; Tabak, Benjamin M.

    2015-10-01

    This paper proposes a new efficiency index to model time-varying inefficiency in stock markets. We focus on European stock markets and show that they have different degrees of time-varying efficiency. We observe that the 2008 global financial crisis has an adverse effect on almost all EU stock markets. However, the Eurozone sovereign debt crisis has a significant adverse effect only on the markets in France, Spain and Greece. For the late members, joining EU does not have a uniform effect on stock market efficiency. Our results have important implications for policy makers, investors, risk managers and academics.

  10. Model-free adaptive fractional order control of stable linear time-varying systems.

    PubMed

    Yakoub, Z; Amairi, M; Chetoui, M; Saidi, B; Aoun, M

    2017-03-01

    This paper presents a new model-free adaptive fractional order control approach for linear time-varying systems. An online algorithm is proposed to determine some frequency characteristics using a selective filtering and to design a fractional PID controller based on the numerical optimization of the frequency-domain criterion. When the system parameters are time-varying, the controller is updated to keep the same desired performances. The main advantage of the proposed approach is that the controller design depends only on the measured input and output signals of the process. The effectiveness of the proposed method is assessed through a numerical example.

  11. Modeling polar cap F-region patches using time varying convection

    SciTech Connect

    Sojka, J.J.; Bowline, M.D.; Schunk, R.W.; Decker, D.T.; Valladares, C.E.; Sheehan, R.; Anderson, D.N.; Heelis, R.A.

    1993-09-03

    Here the authors present the results of computerized simulations of the polar cap regions which were able to model the formation of polar cap patches. They used the Utah State University Time-Dependent Ionospheric Model (TDIM) and the Phillips Laboratory (PL) F-region models in this work. By allowing a time varying magnetospheric electric field in the models, they were able to generate the patches. This time varying field generates a convection in the ionosphere. This convection is similar to convective changes observed in the ionosphere at times of southward pointing interplanetary magnetic field, due to changes in the B[sub y] component of the IMF.

  12. Investigation on the coloured noise in GPS-derived position with time-varying seasonal signals

    NASA Astrophysics Data System (ADS)

    Gruszczynska, Marta; Klos, Anna; Bos, Machiel Simon; Bogusz, Janusz

    2016-04-01

    The seasonal signals in the GPS-derived time series arise from real geophysical signals related to tidal (residual) or non-tidal (loadings from atmosphere, ocean and continental hydrosphere, thermo elastic strain, etc.) effects and numerical artefacts including aliasing from mismodelling in short periods or repeatability of the GPS satellite constellation with respect to the Sun (draconitics). Singular Spectrum Analysis (SSA) is a method for investigation of nonlinear dynamics, suitable to either stationary or non-stationary data series without prior knowledge about their character. The aim of SSA is to mathematically decompose the original time series into a sum of slowly varying trend, seasonal oscillations and noise. In this presentation we will explore the ability of SSA to subtract the time-varying seasonal signals in GPS-derived North-East-Up topocentric components and show properties of coloured noise from residua. For this purpose we used data from globally distributed IGS (International GNSS Service) permanent stations processed by the JPL (Jet Propulsion Laboratory) in a PPP (Precise Point Positioning) mode. After introducing a threshold of 13 years, 264 stations left with a maximum length reaching 23 years. The data was initially pre-processed for outliers, offsets and gaps. The SSA was applied to pre-processed series to estimate the time-varying seasonal signals. We adopted a 3-years window as the optimal dimension of its size determined with the Akaike's Information Criteria (AIC) values. A Fisher-Snedecor test corrected for the presence of temporal correlation was used to determine the statistical significance of reconstructed components. This procedure showed that first four components describing annual and semi-annual signals, are significant at a 99.7% confidence level, which corresponds to 3-sigma criterion. We compared the non-parametric SSA approach with a commonly chosen parametric Least-Squares Estimation that assumes constant amplitudes and

  13. The effects of impulsive harvest on a predator-prey system with distributed time delay

    NASA Astrophysics Data System (ADS)

    Guo, Hongjian; Chen, Lansun

    2009-05-01

    A kind of predator-prey system with distributed time delay and impulsive harvest is firstly presented and then the effects of impulsive harvest on the system are discussed by means of chain transform. By using the Floquet's theory and the comparison theorem of impulsive differential equation, the thresholds between permanence and extinction of each species are obtained as functions of model parameters. It is proved that the impulsive period and the proportion of the impulsive harvest will ultimately affect the fate of each species. Finally, the theoretical results obtained in this paper are confirmed by numerical simulations.

  14. Distributed Interplanetary Delay/Disruption Tolerant Network (DTN) Monitor and Control System

    NASA Technical Reports Server (NTRS)

    Wang, Shin-Ywan

    2012-01-01

    The main purpose of Distributed interplanetary Delay Tolerant Network Monitor and Control System as a DTN system network management implementation in JPL is defined to provide methods and tools that can monitor the DTN operation status, detect and resolve DTN operation failures in some automated style while either space network or some heterogeneous network is infused with DTN capability. In this paper, "DTN Monitor and Control system in Deep Space Network (DSN)" exemplifies a case how DTN Monitor and Control system can be adapted into a space network as it is DTN enabled.

  15. A stage-structured predator-prey model with distributed maturation delay and harvesting.

    PubMed

    Al-Omari, J F M

    2015-01-01

    A stage-structured predator-prey system with distributed maturation delay and harvesting is investigated. General birth and death functions are used. The local stability of each feasible equilibria is discussed. By using the persistence theory, it is proven that the system is permanent if the coexistence equilibrium exists. By using Lyapunov functional and LaSalle invariant principle, it is shown that the trivial equilibrium is globally stable when the other equilibria are not feasible, and that the boundary equilibrium is globally stable if the coexistence equilibrium does not exist. Finally, sufficient conditions are derived for the global stability of the coexistence equilibrium.

  16. Asymptotic behavior of stochastic multi-group epidemic models with distributed delays

    NASA Astrophysics Data System (ADS)

    Liu, Qun; Jiang, Daqing; Shi, Ningzhong; Hayat, Tasawar; Alsaedi, Ahmed

    2017-02-01

    In this paper, we introduce stochasticity into multi-group epidemic models with distributed delays and general kernel functions. The stochasticity in the model is a standard technique in stochastic population modeling. When the perturbations are small, by using the method of stochastic Lyapunov functions, we carry out a detailed analysis on the asymptotic behavior of the stochastic model regarding of the basic reproduction number R0. If R0 ≤ 1, the solution of the stochastic system oscillates around the disease-free equilibrium E0, while if R0 > 1, the solution of the stochastic model fluctuates around the endemic equilibrium E∗. Moreover, we also establish sufficient conditions of these results.

  17. A multi-moded rf delay line distribution system for the next linear collider

    SciTech Connect

    Tantawi, S.G.; Bowden, G.; Farkas, Z.D.; Irwin, J.; Ko, K.; Kroll, N.; Lavine, T.; Li, Z.; Loewen, R.; Miller, R.; Nantista, C.; Ruth, R.D.; Rifkin, J.; Vlieks, A.E.; Wilson, P.B.; Adolphsen, C.; Wang, J.

    1999-07-01

    The Delay Line Distribution System (DLDS) (1) is an alternative to conventional pulse compression which enhances the peak power of an rf source while matching the long pulse of that source to the shorter filling time of the accelerator structure. We present a variation on that scheme that combines the parallel delay lines of the system into one single line. The power of several sources is combined into a single waveguide delay line using a multi-mode launcher. The output mode of the launcher is determined by the phase coding of the input signals. The combined power is extracted using several mode extractors, each of which extracts only one single mode. Hence, the phase coding of the sources controls the output port of the combined power. The power is then fed to the local accelerator structures. We present a detailed design of such a system, including several implementation methods for the launchers, extractors, and ancillary high power rf components. The system is designed so that it can handle the 600 MW peak power required by the NLC design, while maintaining high efficiency. {copyright} {ital 1999 American Institute of Physics.}

  18. Laser imaging of chemistry-flowfield interactions: Enhanced soot formation in time-varying diffusion flames

    SciTech Connect

    Harrington, J.E.; Shaddix, C.R.; Smyth, K.C.

    1994-12-31

    Models of detailed flame chemistry and soot formation are based upon experimental results obtained in steady, laminar flames. For successful application of these descriptions to turbulent combustion, it is instructive to test predictions against measurements in time-varying flowfields. This paper reports the use of optical methods to examine soot production and oxidation processes in a co-flowing, axisymmetric CH{sub 4}/air diffusion flame in which the fuel flow rate is acoustically forced to create a time-varying flowfield. For a particular forcing condition in which tip clipping occurs (0.75 V loudspeaker excitation), elastic scattering of vertically polarized light from the soot particles increases by nearly an order of magnitude with respect to that observed for a steady flame with the same mean fuel flow rate. The visible flame luminosity and laser-induced fluorescence attributed to polycyclic aromatic hydrocarbons (PAH) are also enhanced. Peak soot volume fractions, as measured by time-resolved laser extinction/tomography at 632.8 and 454.5 nm and calibrated laser-induced incandescence (LII), show a factor of 4--5 enhancement in this flickering flame. The LII method is found to track the soot volume fraction closely and to give better signal-to-noise than the extinction measurements in both the steady and time-varying flowfields. A Mie analysis suggests that most of the enhanced soot production results from the formation of larger particles in the time-varying flowfield.

  19. Right factorization of a class of time-varying nonlinear systems

    NASA Technical Reports Server (NTRS)

    Desoer, C. A.; Kabuli, M. G.

    1988-01-01

    A class of nonlinear continuous-time, time-varying plants with a state-space description which has a uniformly completely controllable linear part is considered. For this class, a right factorization is obtained. For the case in which the state is available for feedback, a normalized right-coprime factorization is realized.

  20. The generalized harmonic potential theorem in the presence of a time-varying magnetic field

    PubMed Central

    Lai, Meng-Yun; Pan, Xiao-Yin

    2016-01-01

    We investigate the evolution of the many-body wave function of a quantum system with time-varying effective mass, confined by a harmonic potential with time-varying frequency in the presence of a uniform time-varying magnetic field, and perturbed by a time-dependent uniform electric field. It is found that the wave function is comprised of a phase factor times the solution to the unperturbed time-dependent Schrödinger equation with the latter being translated by a time-dependent value that satisfies the classical driven equation of motion. In other words, we generalize the harmonic potential theorem to the case when the effective mass, harmonic potential, and the external uniform magnetic field with arbitrary orientation are all time-varying. The results reduce to various special cases obtained in the literature, particulary to that of the harmonic potential theorem wave function when the effective mass and frequency are both static and the external magnetic field is absent. PMID:27748461

  1. Model reference adaptive control for linear time varying and nonlinear systems

    NASA Technical Reports Server (NTRS)

    Abida, L.; Kaufman, H.

    1982-01-01

    Model reference adaptive control is applied to linear time varying systems and to nonlinear systems amenable to virtual linearization. Asymptotic stability is guaranteed even if the perfect model following conditions do not hold, provided that some sufficient conditions are satisfied. Simulations show the scheme to be capable of effectively controlling certain nonlinear systems.

  2. Coherent time-varying graph drawing with multifocus+context interaction.

    PubMed

    Feng, Kun-Chuan; Wang, Chaoli; Shen, Han-Wei; Lee, Tong-Yee

    2012-08-01

    We present a new approach for time-varying graph drawing that achieves both spatiotemporal coherence and multifocus+context visualization in a single framework. Our approach utilizes existing graph layout algorithms to produce the initial graph layout, and formulates the problem of generating coherent time-varying graph visualization with the focus+context capability as a specially tailored deformation optimization problem. We adopt the concept of the super graph to maintain spatiotemporal coherence and further balance the needs for aesthetic quality and dynamic stability when interacting with time-varying graphs through focus+context visualization. Our method is particularly useful for multifocus+context visualization of time-varying graphs where we can preserve the mental map by preventing nodes in the focus from undergoing abrupt changes in size and location in the time sequence. Experiments demonstrate that our method strikes a good balance between maintaining spatiotemporal coherence and accentuating visual foci, thus providing a more engaging viewing experience for the users.

  3. Time-Critical Cooperative Path Following of Multiple UAVs over Time-Varying Networks

    DTIC Science & Technology

    2011-01-01

    Contract No. W911NF-06-1-0330. †PhD Candidate, Department of Mechanical Science & Engineering, University of Illinois at Urbana-Champaign; xar- gay ...vehicle is allowed to exchange only its coordination parameter ξi(t) with its neigh- bors Gi, which are defined by the possibly time-varying communications

  4. Resting-State Time-Varying Analysis Reveals Aberrant Variations of Functional Connectivity in Autism

    PubMed Central

    Yao, Zhijun; Hu, Bin; Xie, Yuanwei; Zheng, Fang; Liu, Guangyao; Chen, Xuejiao; Zheng, Weihao

    2016-01-01

    Recently, studies based on time-varying functional connectivity have unveiled brain states diversity in some neuropsychiatric disorders, such as schizophrenia and major depressive disorder. However, time-varying functional connectivity analysis of resting-state functional Magnetic Resonance Imaging (fMRI) have been rarely performed on the Autism Spectrum Disorder (ASD). Hence, we performed time-varying connectivity analysis on resting-state fMRI data to investigate brain states mutation in ASD children. ASD showed an imbalance of connectivity state and aberrant ratio of connectivity with different strengths in the whole brain network, and decreased connectivity associated precuneus/posterior cingulate gyrus with medial prefrontal gyrus in default mode network. As compared to typical development children, weak relevance condition (the strength of a large number of connectivities in the state was less than means minus standard deviation of all connection strength) was maintained for a longer time between brain areas of ASD children, and ratios of weak connectivity in brain states varied dramatically in the ASD. In the ASD, the abnormal brain state might be related to repetitive behaviors and stereotypical interests, and macroscopically reflect disruption of gamma-aminobutyric acid at the cellular level. The detection of brain states based on time-varying functional connectivity analysis of resting-state fMRI might be conducive for diagnosis and early intervention of ASD before obvious clinical symptoms. PMID:27695408

  5. The generalized harmonic potential theorem in the presence of a time-varying magnetic field

    NASA Astrophysics Data System (ADS)

    Lai, Meng-Yun; Pan, Xiao-Yin

    2016-10-01

    We investigate the evolution of the many-body wave function of a quantum system with time-varying effective mass, confined by a harmonic potential with time-varying frequency in the presence of a uniform time-varying magnetic field, and perturbed by a time-dependent uniform electric field. It is found that the wave function is comprised of a phase factor times the solution to the unperturbed time-dependent Schrödinger equation with the latter being translated by a time-dependent value that satisfies the classical driven equation of motion. In other words, we generalize the harmonic potential theorem to the case when the effective mass, harmonic potential, and the external uniform magnetic field with arbitrary orientation are all time-varying. The results reduce to various special cases obtained in the literature, particulary to that of the harmonic potential theorem wave function when the effective mass and frequency are both static and the external magnetic field is absent.

  6. The generalized harmonic potential theorem in the presence of a time-varying magnetic field.

    PubMed

    Lai, Meng-Yun; Pan, Xiao-Yin

    2016-10-17

    We investigate the evolution of the many-body wave function of a quantum system with time-varying effective mass, confined by a harmonic potential with time-varying frequency in the presence of a uniform time-varying magnetic field, and perturbed by a time-dependent uniform electric field. It is found that the wave function is comprised of a phase factor times the solution to the unperturbed time-dependent Schrödinger equation with the latter being translated by a time-dependent value that satisfies the classical driven equation of motion. In other words, we generalize the harmonic potential theorem to the case when the effective mass, harmonic potential, and the external uniform magnetic field with arbitrary orientation are all time-varying. The results reduce to various special cases obtained in the literature, particulary to that of the harmonic potential theorem wave function when the effective mass and frequency are both static and the external magnetic field is absent.

  7. Interactions between time-varying mesh stiffness and clearance non-linearities in a geared system

    NASA Astrophysics Data System (ADS)

    Kahraman, A.; Singh, R.

    1991-04-01

    Frequency response characteristics of a non-linear geared rotor-bearing system with time-varying mesh stiffness k h( overlinet) are examined in this paper. First, the single-degree-of-freedom spur gear pair model with backlash is extended to include sinusoidal or periodic mesh stiffness k h( overlinet) . Second, a three-degree-of-freedom model with k h( overlinet) and clearance non-lineariries associated with gear backlash and rolling element bearings, as excited by the static transmission error overlinee( overlinet) under a mean torque load, is developed. The governing equations are solved using digital simulation technique and only the primary resonances are studied. Resonances of the corresponding linear time-varying system associated with parametric and external excitations are identified using the method of multiple scales and digital simulation. Interactions between the mesh stiffness variation and clearance non-linearities have been investigated; a strong interaction between time-varying mesh stiffness k h( overlinet) and gear backlash is found, whereas the coupling between k h( overlinet) and bearing non-linearities is weak. Finally, our time-varying non-linear formulations yield reasonably good predictions when compared with the benchmark experimental results available in the literature.

  8. Resting-State Time-Varying Analysis Reveals Aberrant Variations of Functional Connectivity in Autism.

    PubMed

    Yao, Zhijun; Hu, Bin; Xie, Yuanwei; Zheng, Fang; Liu, Guangyao; Chen, Xuejiao; Zheng, Weihao

    2016-01-01

    Recently, studies based on time-varying functional connectivity have unveiled brain states diversity in some neuropsychiatric disorders, such as schizophrenia and major depressive disorder. However, time-varying functional connectivity analysis of resting-state functional Magnetic Resonance Imaging (fMRI) have been rarely performed on the Autism Spectrum Disorder (ASD). Hence, we performed time-varying connectivity analysis on resting-state fMRI data to investigate brain states mutation in ASD children. ASD showed an imbalance of connectivity state and aberrant ratio of connectivity with different strengths in the whole brain network, and decreased connectivity associated precuneus/posterior cingulate gyrus with medial prefrontal gyrus in default mode network. As compared to typical development children, weak relevance condition (the strength of a large number of connectivities in the state was less than means minus standard deviation of all connection strength) was maintained for a longer time between brain areas of ASD children, and ratios of weak connectivity in brain states varied dramatically in the ASD. In the ASD, the abnormal brain state might be related to repetitive behaviors and stereotypical interests, and macroscopically reflect disruption of gamma-aminobutyric acid at the cellular level. The detection of brain states based on time-varying functional connectivity analysis of resting-state fMRI might be conducive for diagnosis and early intervention of ASD before obvious clinical symptoms.

  9. The Role of Thermal Properties in Periodic Time-Varying Phenomena

    ERIC Educational Resources Information Center

    Marin, E.

    2007-01-01

    The role played by physical parameters governing the transport of heat in periodical time-varying phenomena within solids is discussed. Starting with a brief look at the conduction heat transport mechanism, the equations governing heat conduction under static, stationary and non-stationary conditions, and the physical parameters involved, are…

  10. Delay modeling of high-speed distributed interconnect for the signal integrity prediction

    NASA Astrophysics Data System (ADS)

    Raveloa, B.

    2012-02-01

    A relevant modeling-method of distributed interconnect line for the high-speed signal integrity (SI) application is introduced in this paper. By using the microwave and transmission line (TL) theory, the interconnect lines are assumed as its distributed RLC-model. Then, based on the transfer matrix analysis, the second-order global transfer function of the interconnect network comprised of the TL driven by voltage source including its internal resistance and the impedance load is expressed. Thus, mathematical analysis enabling the physical SI-parameters' extraction was established by using the transient response of the loaded line. To verify the relevance of the developed model, RC- and RLC-lines excited by square-wavepulse with 10-Gbits/s-rate were investigated. So, comparisons with SPICE-computations were performed. As results, transient responses perfectly well correlated to the reference SPICE-models were evidenced. As application of the introduced model, evaluations of rise-/fall-times, propagation delays, signal attenuations and even the settling times were realized for different values of TL-parameters. Compared to other methods, the computation execution time and data memory consumed by the program implementing the proposed delay modeling-method algorithm are much better.

  11. An Integral Method for Determining Induced Voltage in Time-Varying Wire Inductors

    SciTech Connect

    Fasenfest, B; White, D; Rockway, J

    2005-05-27

    This report documents the creation of software tools to model time-varying wire inductors. The class of inductors studied consists of arbitrary wire shapes in nonmagnetic material. When the wire structures are deformed, the inductance changes, and a voltage is induced. This voltage is of interest, for instance when the inductor is used to measure or sense a shockwave. An integral technique, which only requires integrating over the wire segments, is used to find the inductance at each time step, with backwards-difference approximations being used on successive time steps to determine the voltage. This method allows for arbitrary time-varying wire structures. It was tested for several canonical problems and used to model a double helix solenoid compressed by a shockwave.

  12. Well-posedness of the time-varying linear electromagnetic initial-boundary value problem

    NASA Astrophysics Data System (ADS)

    Xie, Li; Lei, Yin-Zhao

    2007-09-01

    The well-posedness of the initial-boundary value problem of the time-varying linear electromagnetic field in a multi-medium region is investigated. Function spaces are defined, with Faraday's law of electromagnetic induction and the initial-boundary conditions considered as constraints. Gauss's formula applied to a multi-medium region is used to derive the energy-estimating inequality. After converting the initial-boundary conditions into homogeneous ones and analysing the characteristics of an operator introduced according to the total current law, the existence, uniqueness and stability of the weak solution to the initial-boundary value problem of the time-varying linear electromagnetic field are proved.

  13. Applications, dosimetry and biological interactions of static and time-varying magnetic fields

    NASA Astrophysics Data System (ADS)

    Tenforde, T. S.

    1988-08-01

    The primary topics of this presentation include: (1) the applications of magnetic fields in research, industry, and medical technologies; (2) mechanisms of interaction of static and time-varying magnetic fields with living systems; (3) human health effects of exposure to static and time-varying magnetic fields in occupational, medical, and residential settings; and (4) recent advances in the dosimetry of extremely-low-frequency electromagnetic fields. The discussion of these topics is centered about two issues of considerable contemporary interest: (1) potential health effects of the fields used in magnetic resonance imaging and in vivo spectroscopy, and (2) the controversial issue of whether exposure to extremely-low-frequency (ELF) electromagnetic fields in the home and workplace leads to an elevated risk of cancer.

  14. Structural Nested Mean Models for Assessing Time-Varying Effect Moderation

    PubMed Central

    Almirall, Daniel; Ten Have, Thomas; Murphy, Susan A.

    2009-01-01

    SUMMARY This article considers the problem of assessing causal effect moderation in longitudinal settings in which treatment (or exposure) is time-varying and so are the covariates said to moderate its effect. Intermediate Causal Effects that describe time-varying causal effects of treatment conditional on past covariate history are introduced and considered as part of Robins’ Structural Nested Mean Model. Two estimators of the intermediate causal effects, and their standard errors, are presented and discussed: The first is a proposed 2-Stage Regression Estimator. The second is Robins’ G-Estimator. The results of a small simulation study that begins to shed light on the small versus large sample performance of the estimators, and on the bias-variance trade-off between the two estimators are presented. The methodology is illustrated using longitudinal data from a depression study. PMID:19397586

  15. Finite-time consensus of time-varying nonlinear multi-agent systems

    NASA Astrophysics Data System (ADS)

    Liu, Qingrong; Liang, Zhishan

    2016-08-01

    This paper investigates the problem of leader-follower finite-time consensus for a class of time-varying nonlinear multi-agent systems. The dynamics of each agent is assumed to be represented by a strict feedback nonlinear system, where nonlinearities satisfy Lipschitz growth conditions with time-varying gains. The main design procedure is outlined as follows. First, it is shown that the leader-follower consensus problem is equivalent to a conventional control problem of multi-variable high-dimension systems. Second, by introducing a state transformation, the control problem is converted into the construction problem of two dynamic equations. Third, based on the Lyapunov stability theorem, the global finite-time stability of the closed-loop control system is proved, and the finite-time consensus of the concerned multi-agent systems is thus guaranteed. An example is given to verify the effectiveness of the proposed consensus protocol algorithm.

  16. Time-varying linear and nonlinear parametric model for Granger causality analysis.

    PubMed

    Li, Yang; Wei, Hua-Liang; Billings, Steve A; Liao, Xiao-Feng

    2012-04-01

    Statistical measures such as coherence, mutual information, or correlation are usually applied to evaluate the interactions between two or more signals. However, these methods cannot distinguish directions of flow between two signals. The capability to detect causalities is highly desirable for understanding the cooperative nature of complex systems. The main objective of this work is to present a linear and nonlinear time-varying parametric modeling and identification approach that can be used to detect Granger causality, which may change with time and may not be detected by traditional methods. A numerical example, in which the exact causal influences relationships, is presented to illustrate the performance of the method for time-varying Granger causality detection. The approach is applied to EEG signals to track and detect hidden potential causalities. One advantage of the proposed model, compared with traditional Granger causality, is that the results are easier to interpret and yield additional insights into the transient directed dynamical Granger causality interactions.

  17. Piezoceramic devices and artificial intelligence time varying concepts in smart structures

    NASA Technical Reports Server (NTRS)

    Hanagud, S.; Calise, A. J.; Glass, B. J.

    1990-01-01

    The problem of development of smart structures and their vibration control by the use of piezoceramic sensors and actuators have been discussed. In particular, these structures are assumed to have time varying model form and parameters. The model form may change significantly and suddenly. Combined identification of the model from parameters of these structures and model adaptive control of these structures are discussed in this paper.

  18. Simulink-Based Implementation and Performance Analysis of TDS-OFDM in Time-Varying Environments

    DTIC Science & Technology

    2014-09-01

    IMPLEMENTATION AND PERFORMANCE ANALYSIS OF TDS- OFDM IN TIME- VARYING ENVIRONMENTS by Hui-Chen Lai September 2014 Thesis Advisor: Monique P...2014 3. REPORT TYPE AND DATES COVERED Master’s Thesis 4. TITLE AND SUBTITLE SIMULINK-BASED IMPLEMENTATION AND PERFORMANCE ANALYSIS OF TDS- OFDM ...simulink-based software models to implement and test the time-domain synchronous OFDM (TDS- OFDM ) transmitter and receiver systems. This technique

  19. Model selection and change detection for a time-varying mean in process monitoring

    NASA Astrophysics Data System (ADS)

    Burr, Tom; Hamada, Michael S.; Ticknor, Larry; Weaver, Brian

    2014-07-01

    Process monitoring (PM) for nuclear safeguards sometimes requires estimation of thresholds corresponding to small false alarm rates. Threshold estimation is an old topic; however, because possible new roles for PM are being evaluated in nuclear safeguards, it is timely to consider modern model selection options in the context of alarm threshold estimation. One of the possible new PM roles involves PM residuals, where a residual is defined as residual=data-prediction. This paper briefly reviews alarm threshold estimation, introduces model selection options, and considers several assumptions regarding the data-generating mechanism for PM residuals. Four PM examples from nuclear safeguards are included. One example involves frequent by-batch material balance closures where a dissolution vessel has time-varying efficiency, leading to time-varying material holdup. Another example involves periodic partial cleanout of in-process inventory, leading to challenging structure in the time series of PM residuals. Our main focus is model selection to select a defensible model for normal behavior with a time-varying mean in a PM residual stream. We use approximate Bayesian computation to perform the model selection and parameter estimation for normal behavior. We then describe a simple lag-one-differencing option similar to that used to monitor non-stationary times series to monitor for off-normal behavior.

  20. Time-Varying Vocal Folds Vibration Detection Using a 24 GHz Portable Auditory Radar

    PubMed Central

    Hong, Hong; Zhao, Heng; Peng, Zhengyu; Li, Hui; Gu, Chen; Li, Changzhi; Zhu, Xiaohua

    2016-01-01

    Time-varying vocal folds vibration information is of crucial importance in speech processing, and the traditional devices to acquire speech signals are easily smeared by the high background noise and voice interference. In this paper, we present a non-acoustic way to capture the human vocal folds vibration using a 24-GHz portable auditory radar. Since the vocal folds vibration only reaches several millimeters, the high operating frequency and the 4 × 4 array antennas are applied to achieve the high sensitivity. The Variational Mode Decomposition (VMD) based algorithm is proposed to decompose the radar-detected auditory signal into a sequence of intrinsic modes firstly, and then, extract the time-varying vocal folds vibration frequency from the corresponding mode. Feasibility demonstration, evaluation, and comparison are conducted with tonal and non-tonal languages, and the low relative errors show a high consistency between the radar-detected auditory time-varying vocal folds vibration and acoustic fundamental frequency, except that the auditory radar significantly improves the frequency-resolving power. PMID:27483261

  1. Stochastic Modeling and Power Control of Time-Varying Wireless Communication Networks

    SciTech Connect

    Olama, Mohammed M; Djouadi, Seddik M; Charalambous, Prof. Charalambos

    2014-01-01

    Wireless networks are characterized by nodes mobility, which makes the propagation environment time-varying and subject to fading. As a consequence, the statistical characteristics of the received signal vary continuously, giving rise to a Doppler power spectral density (DPSD) that varies from one observation instant to the next. This paper is concerned with dynamical modeling of time-varying wireless fading channels, their estimation and parameter identification, and optimal power control from received signal measurement data. The wireless channel is characterized using a stochastic state-space form and derived by approximating the time-varying DPSD of the channel. The expected maximization and Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Moreover, we investigate a centralized optimal power control algorithm based on predictable strategies and employing the estimated channel parameters and states. The proposed models together with the estimation and power control algorithms are tested using experimental measurement data and the results are presented.

  2. Time-Varying Vocal Folds Vibration Detection Using a 24 GHz Portable Auditory Radar.

    PubMed

    Hong, Hong; Zhao, Heng; Peng, Zhengyu; Li, Hui; Gu, Chen; Li, Changzhi; Zhu, Xiaohua

    2016-07-28

    Time-varying vocal folds vibration information is of crucial importance in speech processing, and the traditional devices to acquire speech signals are easily smeared by the high background noise and voice interference. In this paper, we present a non-acoustic way to capture the human vocal folds vibration using a 24-GHz portable auditory radar. Since the vocal folds vibration only reaches several millimeters, the high operating frequency and the 4 × 4 array antennas are applied to achieve the high sensitivity. The Variational Mode Decomposition (VMD) based algorithm is proposed to decompose the radar-detected auditory signal into a sequence of intrinsic modes firstly, and then, extract the time-varying vocal folds vibration frequency from the corresponding mode. Feasibility demonstration, evaluation, and comparison are conducted with tonal and non-tonal languages, and the low relative errors show a high consistency between the radar-detected auditory time-varying vocal folds vibration and acoustic fundamental frequency, except that the auditory radar significantly improves the frequency-resolving power.

  3. Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula

    NASA Astrophysics Data System (ADS)

    Sarhadi, Ali; Burn, Donald H.; Concepción Ausín, María.; Wiper, Michael P.

    2016-03-01

    A time-varying risk analysis is proposed for an adaptive design framework in nonstationary conditions arising from climate change. A Bayesian, dynamic conditional copula is developed for modeling the time-varying dependence structure between mixed continuous and discrete multiattributes of multidimensional hydrometeorological phenomena. Joint Bayesian inference is carried out to fit the marginals and copula in an illustrative example using an adaptive, Gibbs Markov Chain Monte Carlo (MCMC) sampler. Posterior mean estimates and credible intervals are provided for the model parameters and the Deviance Information Criterion (DIC) is used to select the model that best captures different forms of nonstationarity over time. This study also introduces a fully Bayesian, time-varying joint return period for multivariate time-dependent risk analysis in nonstationary environments. The results demonstrate that the nature and the risk of extreme-climate multidimensional processes are changed over time under the impact of climate change, and accordingly the long-term decision making strategies should be updated based on the anomalies of the nonstationary environment.

  4. A New Time-varying Concept of Risk in a Changing Climate

    NASA Astrophysics Data System (ADS)

    Sarhadi, Ali; Ausín, María Concepción; Wiper, Michael P.

    2016-10-01

    In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments.

  5. Inferring time-varying recharge from inverse analysis of long-term water levels

    USGS Publications Warehouse

    Dickinson, J.E.; Hanson, R.T.; Ferre, T. P. A.; Leake, S.A.

    2004-01-01

    Water levels in aquifers typically vary in response to time-varying rates of recharge, suggesting the possibility of inferring time-varying recharge rates on the basis of long-term water level records. Presumably, in the southwestern United States (Arizona, Nevada, New Mexico, southern California, and southern Utah), rates of mountain front recharge to alluvial aquifers depend on variations in precipitation rates due to known climate cycles such as the El Nin??o-Southern Oscillation index and the Pacific Decadal Oscillation. This investigation examined the inverse application of a one-dimensional analytical model for periodic flow described by Lloyd R. Townley in 1995 to estimate periodic recharge variations on the basis of variations in long-term water level records using southwest aquifers as the case study. Time-varying water level records at various locations along the flow line were obtained by simulation of forward models of synthetic basins with applied sinusoidal recharge of either a single period or composite of multiple periods of length similar to known climate cycles. Periodic water level components, reconstructed using singular spectrum analysis (SSA), were used to calibrate the analytical model to estimate each recharge component. The results demonstrated that periodic recharge estimates were most accurate in basins with nearly uniform transmissivity and the accuracy of the recharge estimates depends on monitoring well location. A case study of the San Pedro Basin, Arizona, is presented as an example of calibrating the analytical model to real data.

  6. Opinion formation in time-varying social networks: The case of the naming game

    NASA Astrophysics Data System (ADS)

    Maity, Suman Kalyan; Manoj, T. Venkat; Mukherjee, Animesh

    2012-09-01

    We study the dynamics of the naming game as an opinion formation model on time-varying social networks. This agent-based model captures the essential features of the agreement dynamics by means of a memory-based negotiation process. Our study focuses on the impact of time-varying properties of the social network of the agents on the naming game dynamics. In particular, we perform a computational exploration of this model using simulations on top of real networks. We investigate the outcomes of the dynamics on two different types of time-varying data: (1) the networks vary on a day-to-day basis and (2) the networks vary within very short intervals of time (20 sec). In the first case, we find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the naming game in these networks maintains clusters of coexisting opinions indefinitely leading to metastability. In the second case, we investigate the evolution of the naming game in perfect synchronization with the time evolution of the underlying social network shedding new light on the traditional emergent properties of the game that differ largely from what has been reported in the existing literature.

  7. Time-varying effect modeling with longitudinal data truncated by death: conditional models, interpretations, and inference.

    PubMed

    Estes, Jason P; Nguyen, Danh V; Dalrymple, Lorien S; Mu, Yi; Şentürk, Damla

    2016-05-20

    Recent studies found that infection-related hospitalization was associated with increased risk of cardiovascular (CV) events, such as myocardial infarction and stroke in the dialysis population. In this work, we develop time-varying effects modeling tools in order to examine the CV outcome risk trajectories during the time periods before and after an initial infection-related hospitalization. For this, we propose partly conditional and fully conditional partially linear generalized varying coefficient models (PL-GVCMs) for modeling time-varying effects in longitudinal data with substantial follow-up truncation by death. Unconditional models that implicitly target an immortal population is not a relevant target of inference in applications involving a population with high mortality, like the dialysis population. A partly conditional model characterizes the outcome trajectory for the dynamic cohort of survivors, where each point in the longitudinal trajectory represents a snapshot of the population relationships among subjects who are alive at that time point. In contrast, a fully conditional approach models the time-varying effects of the population stratified by the actual time of death, where the mean response characterizes individual trends in each cohort stratum. We compare and contrast partly and fully conditional PL-GVCMs in our aforementioned application using hospitalization data from the United States Renal Data System. For inference, we develop generalized likelihood ratio tests. Simulation studies examine the efficacy of estimation and inference procedures.

  8. Correcting for Measurement Error in Time-Varying Covariates in Marginal Structural Models.

    PubMed

    Kyle, Ryan P; Moodie, Erica E M; Klein, Marina B; Abrahamowicz, Michał

    2016-08-01

    Unbiased estimation of causal parameters from marginal structural models (MSMs) requires a fundamental assumption of no unmeasured confounding. Unfortunately, the time-varying covariates used to obtain inverse probability weights are often error-prone. Although substantial measurement error in important confounders is known to undermine control of confounders in conventional unweighted regression models, this issue has received comparatively limited attention in the MSM literature. Here we propose a novel application of the simulation-extrapolation (SIMEX) procedure to address measurement error in time-varying covariates, and we compare 2 approaches. The direct approach to SIMEX-based correction targets outcome model parameters, while the indirect approach corrects the weights estimated using the exposure model. We assess the performance of the proposed methods in simulations under different clinically plausible assumptions. The simulations demonstrate that measurement errors in time-dependent covariates may induce substantial bias in MSM estimators of causal effects of time-varying exposures, and that both proposed SIMEX approaches yield practically unbiased estimates in scenarios featuring low-to-moderate degrees of error. We illustrate the proposed approach in a simple analysis of the relationship between sustained virological response and liver fibrosis progression among persons infected with hepatitis C virus, while accounting for measurement error in γ-glutamyltransferase, using data collected in the Canadian Co-infection Cohort Study from 2003 to 2014.

  9. Multimodal Pilot Behavior in Multi-Axis Tracking Tasks with Time-Varying Motion Cueing Gains

    NASA Technical Reports Server (NTRS)

    Zaal, P. M. T; Pool, D. M.

    2014-01-01

    In a large number of motion-base simulators, adaptive motion filters are utilized to maximize the use of the available motion envelope of the motion system. However, not much is known about how the time-varying characteristics of such adaptive filters affect pilots when performing manual aircraft control. This paper presents the results of a study investigating the effects of time-varying motion filter gains on pilot control behavior and performance. An experiment was performed in a motion-base simulator where participants performed a simultaneous roll and pitch tracking task, while the roll and/or pitch motion filter gains changed over time. Results indicate that performance increases over time with increasing motion gains. This increase is a result of a time-varying adaptation of pilots' equalization dynamics, characterized by increased visual and motion response gains and decreased visual lead time constants. Opposite trends are found for decreasing motion filter gains. Even though the trends in both controlled axes are found to be largely the same, effects are less significant in roll. In addition, results indicate minor cross-coupling effects between pitch and roll, where a cueing variation in one axis affects the behavior adopted in the other axis.

  10. A New Time-varying Concept of Risk in a Changing Climate

    PubMed Central

    Sarhadi, Ali; Ausín, María Concepción; Wiper, Michael P.

    2016-01-01

    In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments. PMID:27762398

  11. State Space Modeling of Time-Varying Contemporaneous and Lagged Relations in Connectivity Maps

    PubMed Central

    Molenaar, Peter C. M.; Beltz, Adriene M.; Gates, Kathleen M.; Wilson, Stephen J.

    2017-01-01

    Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. PMID:26546863

  12. A comparison of DC and time-varying measurement of electrical conductivity in randomly generated two-phase networks.

    NASA Astrophysics Data System (ADS)

    Mandolesi, Eric; Moorkamp, Max; Jones, Alan G.

    2015-04-01

    Most electromagnetic (EM) geophysical methods focus on the electrical properties of rocks and sediments to determine reliable images of the subsurface, images routinely used in a broad range of applications. Often laboratory measurements of the same EM properties return equivocal results that are difficult to reconcile with observations obtained by EM imaging techniques. These inconsistencies lead to major interpretation problems. Different numerical approaches have been investigated in order to understand the consequences of the presence or absence of interconnected networks of fractures and pores on EM field measurements. These networks have a crucial effect on the EM field measurements, given that they can be permeated by conductive fluids that enhance the conductivity measurements of the whole environment. Most of the above-mentioned studies restrict their examination to direct current (DC) sources only. Bearing in mind that the time-varying nature of the natural electromagnetic sources play a major role in field measurements, we numerically model the effects of such EM sources on the conductivity measured on the surface of a randomly generated three-dimensional body buried in a uniform conductivity host by simulating a magnetotelluric (MT) station measurements on the top of the target random host itself. As a second experiment we simulated a DC measurement of the target bulk conductivity. The spatial distribution and shape of the conductor network allows in fact the propagation of time-varying EM fields by induction, leading the two different methods to measure a different numerical value for the bulk of the same physical property. We have compared the results from the simulated measurements obtained considering time-varying and DC sources with electrical conductivity predicted by both Hashin-Shtrikman (HS) bounds and Archie's Law, and we have compared these results with statistical properties of the model themselves. Our results suggest that for time-varying

  13. Dissipative control for state-saturated discrete time-varying systems with randomly occurring nonlinearities and missing measurements

    NASA Astrophysics Data System (ADS)

    Ding, Derui; Wang, Zidong; Hu, Jun; Shu, Huisheng

    2013-04-01

    In this paper, the dissipative control problem is investigated for a class of discrete time-varying systems with simultaneous presence of state saturations, randomly occurring nonlinearities as well as multiple missing measurements. In order to render more practical significance of the system model, some Bernoulli distributed white sequences with known conditional probabilities are adopted to describe the phenomena of the randomly occurring nonlinearities and the multiple missing measurements. The purpose of the addressed problem is to design a time-varying output-feedback controller such that the dissipativity performance index is guaranteed over a given finite-horizon. By introducing a free matrix with its infinity norm less than or equal to 1, the system state is bounded by a convex hull so that some sufficient conditions can be obtained in the form of recursive nonlinear matrix inequalities. A novel controller design algorithm is then developed to deal with the recursive nonlinear matrix inequalities. Furthermore, the obtained results are extended to the case when the state saturation is partial. Two numerical simulation examples are provided to demonstrate the effectiveness and applicability of the proposed controller design approach.

  14. Failure Modes in Capacitors When Tested Under a Time-Varying Stress

    NASA Technical Reports Server (NTRS)

    Liu, David (Donhang)

    2011-01-01

    Power-on failure has been the prevalent failure mechanism for solid tantalum capacitors in decoupling applications. A surge step stress test (SSST) has been previously applied to identify the critical stress level of a capacitor batch to give some predictability to the power-on failure mechanism [1]. But SSST can also be viewed as an electrically destructive test under a time-varying stress (voltage). It consists of rapidly charging the capacitor with incremental voltage increases, through a low resistance in series, until the capacitor under test is electrically shorted. When the reliability of capacitors is evaluated, a highly accelerated life test (HALT) is usually adopted since it is a time-efficient method of determining the failure mechanism; however, a destructive test under a time-varying stress such as SSST is even more time efficient. It usually takes days or weeks to complete a HALT test, but it only takes minutes for a time-varying stress test to produce failures. The advantage of incorporating a specific time-varying stress profile into a statistical model is significant in providing an alternative life test method for quickly revealing the failure mechanism in capacitors. In this paper, a time-varying stress that mimics a typical SSST has been incorporated into the Weibull model to characterize the failure mechanism in different types of capacitors. The SSST circuit and transient conditions for correctly surge testing capacitors are discussed. Finally, the SSST was applied for testing Ta capacitors, polymer aluminum capacitors (PA capacitors), and multi-layer ceramic (MLC) capacitors with both precious metal electrodes (PME) and base metal electrodes (BME). The test results are found to be directly associated with the dielectric layer breakdown in Ta and PA capacitors and are independent of the capacitor values, the way the capacitors were built, and the capacitors manufacturers. The test results also show that MLC capacitors exhibit surge breakdown

  15. Analysis of an SIR Epidemic Model with Pulse Vaccination and Distributed Time Delay

    PubMed Central

    Gao, Shujing; Teng, Zhidong; Nieto, Juan J.; Torres, Angela

    2007-01-01

    Pulse vaccination, the repeated application of vaccine over a defined age range, is gaining prominence as an effective strategy for the elimination of infectious diseases. An SIR epidemic model with pulse vaccination and distributed time delay is proposed in this paper. Using the discrete dynamical system determined by the stroboscopic map, we obtain the exact infection-free periodic solution of the impulsive epidemic system and prove that the infection-free periodic solution is globally attractive if the vaccination rate is larger enough. Moreover, we show that the disease is uniformly persistent if the vaccination rate is less than some critical value. The permanence of the model is investigated analytically. Our results indicate that a large pulse vaccination rate is sufficient for the eradication of the disease. PMID:18322563

  16. Cluster synchronization of community network with distributed time delays via impulsive control

    NASA Astrophysics Data System (ADS)

    Leng, Hui; Wu, Zhao-Yan

    2016-11-01

    Cluster synchronization is an important dynamical behavior in community networks and deserves further investigations. A community network with distributed time delays is investigated in this paper. For achieving cluster synchronization, an impulsive control scheme is introduced to design proper controllers and an adaptive strategy is adopted to make the impulsive controllers unified for different networks. Through taking advantage of the linear matrix inequality technique and constructing Lyapunov functions, some synchronization criteria with respect to the impulsive gains, instants, and system parameters without adaptive strategy are obtained and generalized to the adaptive case. Finally, numerical examples are presented to demonstrate the effectiveness of the theoretical results. Project supported by the National Natural Science Foundation of China (Grant No. 61463022), the Natural Science Foundation of Jiangxi Province, China (Grant No. 20161BAB201021), and the Natural Science Foundation of Jiangxi Educational Committee, China (Grant No. GJJ14273).

  17. Tracking time-varying cerebral autoregulation in response to changes in respiratory PaCO2.

    PubMed

    Liu, Jia; Simpson, M David; Yan, Jingyu; Allen, Robert

    2010-10-01

    Cerebral autoregulation has been studied by linear filter systems, with arterial blood pressure (ABP) as the input and cerebral blood flow velocity (CBFV-from transcranial Doppler Ultrasound) as the output. The current work extends this by using adaptive filters to investigate the dynamics of time-varying cerebral autoregulation during step-wise changes in arterial PaCO(2). Cerebral autoregulation was transiently impaired in 11 normal adult volunteers, by switching inspiratory air to a CO(2)/air mixture (5% CO(2), 30% O(2) and 65% N(2)) for approximately 2 min and then back to the ambient air, causing step-wise changes in end-tidal CO(2) (EtCO(2)). Simultaneously, ABP and CBFV were recorded continuously. Simulated data corresponding to the same protocol were also generated using an established physiological model, in order to refine the signal analysis methods. Autoregulation was quantified by the time-varying phase lead, estimated from the adaptive filter model. The adaptive filter was able to follow rapid changes in autoregulation, as was confirmed in the simulated data. In the recorded signals, there was a slow decrease in autoregulatory function following the step-wise increase in PaCO(2) (but this did not reach a steady state within approximately 2 min of recording), with a more rapid change in autoregulation on return to normocapnia. Adaptive filter modelling was thus able to demonstrate time-varying autoregulation. It was further noted that impairment and recovery of autoregulation during transient increases in EtCO(2) occur in an asymmetric manner, which should be taken into account when designing experimental protocols for the study of autoregulation.

  18. Nonlinearly Activated Neural Network for Solving Time-Varying Complex Sylvester Equation.

    PubMed

    Li, Shuai; Li, Yangming

    2013-10-28

    The Sylvester equation is often encountered in mathematics and control theory. For the general time-invariant Sylvester equation problem, which is defined in the domain of complex numbers, the Bartels-Stewart algorithm and its extensions are effective and widely used with an O(n³) time complexity. When applied to solving the time-varying Sylvester equation, the computation burden increases intensively with the decrease of sampling period and cannot satisfy continuous realtime calculation requirements. For the special case of the general Sylvester equation problem defined in the domain of real numbers, gradient-based recurrent neural networks are able to solve the time-varying Sylvester equation in real time, but there always exists an estimation error while a recently proposed recurrent neural network by Zhang et al [this type of neural network is called Zhang neural network (ZNN)] converges to the solution ideally. The advancements in complex-valued neural networks cast light to extend the existing real-valued ZNN for solving the time-varying real-valued Sylvester equation to its counterpart in the domain of complex numbers. In this paper, a complex-valued ZNN for solving the complex-valued Sylvester equation problem is investigated and the global convergence of the neural network is proven with the proposed nonlinear complex-valued activation functions. Moreover, a special type of activation function with a core function, called sign-bi-power function, is proven to enable the ZNN to converge in finite time, which further enhances its advantage in online processing. In this case, the upper bound of the convergence time is also derived analytically. Simulations are performed to evaluate and compare the performance of the neural network with different parameters and activation functions. Both theoretical analysis and numerical simulations validate the effectiveness of the proposed method.

  19. Energy harvesting using parametric resonant system due to time-varying damping

    NASA Astrophysics Data System (ADS)

    Scapolan, Matteo; Tehrani, Maryam Ghandchi; Bonisoli, Elvio

    2016-10-01

    In this paper, the problem of energy harvesting is considered using an electromechanical oscillator. The energy harvester is modelled as a spring-mass-damper, in which the dissipated energy in the damper can be stored rather than wasted. Previous research provided the optimum damping parameter, to harvest maximum amount of energy, taking into account the stroke limit of the device. However, the amount of the maximum harvested energy is limited to a single frequency in which the device is tuned. Active and semi-active strategies have been suggested, which increases the performance of the harvester. Recently, nonlinear damping in the form of cubic damping has been proposed to extend the dynamic range of the harvester. In this paper, a periodic time-varying damper is introduced, which results in a parametrically excited system. When the frequency of the periodic time-varying damper is twice the excitation frequency, the system internal energy increases proportionally to the energy already stored in the system. Thus, for certain parametric damping values, the system can become unstable. This phenomenon can be exploited for energy harvesting. The transition curves, which separate the stable and unstable dynamics are derived, both analytically using harmonic balance method, and numerically using time simulations. The design of the harvester is such that its response is close to the transition curves of the Floquet diagram, leading to stable but resonant system. The performance of the parametric harvester is compared with the non-parametric one. It is demonstrated that performances and the frequency bandwidth in which the energy can be harvested can be both increased using time-varying damping.

  20. A Kalman-Filter Based Approach to Identification of Time-Varying Gene Regulatory Networks

    PubMed Central

    Xiong, Jie; Zhou, Tong

    2013-01-01

    Motivation Conventional identification methods for gene regulatory networks (GRNs) have overwhelmingly adopted static topology models, which remains unchanged over time to represent the underlying molecular interactions of a biological system. However, GRNs are dynamic in response to physiological and environmental changes. Although there is a rich literature in modeling static or temporally invariant networks, how to systematically recover these temporally changing networks remains a major and significant pressing challenge. The purpose of this study is to suggest a two-step strategy that recovers time-varying GRNs. Results It is suggested in this paper to utilize a switching auto-regressive model to describe the dynamics of time-varying GRNs, and a two-step strategy is proposed to recover the structure of time-varying GRNs. In the first step, the change points are detected by a Kalman-filter based method. The observed time series are divided into several segments using these detection results; and each time series segment belonging to two successive demarcating change points is associated with an individual static regulatory network. In the second step, conditional network structure identification methods are used to reconstruct the topology for each time interval. This two-step strategy efficiently decouples the change point detection problem and the topology inference problem. Simulation results show that the proposed strategy can detect the change points precisely and recover each individual topology structure effectively. Moreover, computation results with the developmental data of Drosophila Melanogaster show that the proposed change point detection procedure is also able to work effectively in real world applications and the change point estimation accuracy exceeds other existing approaches, which means the suggested strategy may also be helpful in solving actual GRN reconstruction problem. PMID:24116005

  1. Time-varying Reeb Graphs for Continuous Space-Time Data

    SciTech Connect

    Edelsbrunner, H; Harer, J; Mascarenhas, A; Pascucci, V; Snoeyink, J

    2008-04-22

    The Reeb graph is a useful tool in visualizing real-valued data obtained from computational simulations of physical processes. We characterize the evolution of the Reeb graph of a time-varying continuous function defined in three-dimensional space. We show how to maintain the Reeb graph over time and compress the entire sequence of Reeb graphs into a single, partially persistent data structure, and augment this data structure with Betti numbers to describe the topology of level sets and with path seeds to assist in the fast extraction of level sets for visualization.

  2. Control of Magnetic Bearings for Rotor Unbalance With Plug-In Time-Varying Resonators

    PubMed Central

    Kang, Christopher; Tsao, Tsu-Chin

    2016-01-01

    Rotor unbalance, common phenomenon of rotational systems, manifests itself as a periodic disturbance synchronized with the rotor's angular velocity. In active magnetic bearing (AMB) systems, feedback control is required to stabilize the open-loop unstable electromagnetic levitation. Further, feedback action can be added to suppress the repeatable runout but maintain closed-loop stability. In this paper, a plug-in time-varying resonator is designed by inverting cascaded notch filters. This formulation allows flexibility in designing the internal model for appropriate disturbance rejection. The plug-in structure ensures that stability can be maintained for varying rotor speeds. Experimental results of an AMB–rotor system are presented. PMID:27222600

  3. Indirect M-MRAC for Systems with Time Varying Parameters and Bounded Disturbances

    NASA Technical Reports Server (NTRS)

    Stepanyan, Vahram; Krishnakumar, Kalmanje

    2012-01-01

    The paper presents a prediction-identification model based adaptive control method for uncertain systems with time varying parameters in the presence of bounded external disturbances. The method guarantees desired tracking performance for the system s state and input signals. This is achieved by feeding back the state prediction error to the identification model. It is shown that the desired closed-loop properties are obtained with fast adaptation when the error feedback gain is selected proportional to the square root of the adaptation rate. The theoretical findings are confirmed via a simulation example.

  4. A method for time-varying annoyance rating of aircraft noise.

    PubMed

    Dickson, Crispin

    2009-07-01

    The method of continuous judgment by category is used and evaluated to measure time-varying attributes in aircraft flyover sounds. The results are also used to estimate preference between the different experimental sounds. Jurors were asked to rate perceived annoyance on a Borg CR 100 scale continuously during the playback of 11 flyover sequences and the results showed differences in perception in the time segment where the sound had been modified. The method can be used to evaluate maximum perceived annoyance, threshold levels, duration of perceptual presence temporal integration in perception, and perceptual mixtures over time.

  5. Dealing with periodical loads and harmonics in operational modal analysis using time-varying transmissibility functions

    NASA Astrophysics Data System (ADS)

    Weijtjens, Wout; Lataire, John; Devriendt, Christof; Guillaume, Patrick

    2014-12-01

    Periodical loads, such as waves and rotating machinery, form a problem for operational modal analysis (OMA). In OMA only the vibrations of a structure of interest are measured and little to nothing is known about the loads causing these vibrations. Therefore, it is often assumed that all dynamics in the measured data are linked to the system of interest. Periodical loads defy this assumption as their periodical behavior is often visible within the measured vibrations. As a consequence most OMA techniques falsely associate the dynamics of the periodical load with the system of interest. Without additional information about the load, one is not able to correctly differentiate between structural dynamics and the dynamics of the load. In several applications, e.g. turbines and helicopters, it was observed that because of periodical loads one was unable to correctly identify one or multiple modes. Transmissibility based OMA (TOMA) is a completely different approach to OMA. By using transmissibility functions to estimate the structural dynamics of the system of interest, all influence of the load-spectrum can be eliminated. TOMA therefore allows to identify the modal parameters without being influenced by the presence of periodical loads, such as harmonics. One of the difficulties of TOMA is that the analyst is required to find two independent datasets, each associated with a different loading condition of the system of interest. This poses a dilemma for TOMA; how can an analyst identify two different loading conditions when little is known about the loads on the system? This paper tackles that problem by assuming that the loading conditions vary continuously over time, e.g. the changing wind directions. From this assumption TOMA is developed into a time-varying framework. This development allows TOMA to not only cope with the continuously changing loading conditions. The time-varying framework also enables the identification of the modal parameters from a single dataset

  6. Time-Varying Expression of the Formation Flying along Circular Trajectories

    NASA Technical Reports Server (NTRS)

    Kawaguchi, Jun'ichiro

    2007-01-01

    Usually, the formation flying associated with circular orbits is discussed through the well-known Hill s or C-W equations of motion. This paper dares to present and discuss the coordinates that may contain time-varying coefficients. The discussion presents how the controller s performance is affected by the selection of coordinates, and also looks at the special coordinate suitable for designating a target bin to which each spacecraft in the formation has only to be guided. It is revealed that the latter strategy may incorporate the J2 disturbance automatically.

  7. Flow visualization of time-varying structural characteristics of dean vortices in a curved channel

    NASA Astrophysics Data System (ADS)

    Bella, David Wayne

    1988-12-01

    The time varying development and structure of Dean vortices were studied using flow visualization. Observations were made over a range of Dean numbers from 40 to 200 using a transparent channel with mild curvature, 40:1 aspect ratio, and an inner to outer radius ratio of 0.979. Seven flow visualization techniques were tried but only one, a wood burning smoke generator, produced usable results. Different vortex characteristics were observed and documented in sequences of photographs spaced one quarter of a second apart at locations ranging from 85 to 135 degrees from the start of curvature. Evidence is presented that supports the twisting/rocking nature of the flow.

  8. Control of Magnetic Bearings for Rotor Unbalance With Plug-In Time-Varying Resonators.

    PubMed

    Kang, Christopher; Tsao, Tsu-Chin

    2016-01-01

    Rotor unbalance, common phenomenon of rotational systems, manifests itself as a periodic disturbance synchronized with the rotor's angular velocity. In active magnetic bearing (AMB) systems, feedback control is required to stabilize the open-loop unstable electromagnetic levitation. Further, feedback action can be added to suppress the repeatable runout but maintain closed-loop stability. In this paper, a plug-in time-varying resonator is designed by inverting cascaded notch filters. This formulation allows flexibility in designing the internal model for appropriate disturbance rejection. The plug-in structure ensures that stability can be maintained for varying rotor speeds. Experimental results of an AMB-rotor system are presented.

  9. Carrier frequency offset estimation for OFDM systems with time-varying DC Offset

    NASA Astrophysics Data System (ADS)

    Liu, Tao; Li, Hanzhang

    2012-12-01

    Orthogonal frequency division multiplexing (OFDM) systems with direct-conversion architecture suffer from both carrier frequency offset (CFO) and dc offset (DCO). In this paper, we study CFO estimation problem for OFDM systems with time-varying DCO (TV-DCO) caused by gain mode switch of low noise amplifier (LNA). Based on linear approximation of TV-DCO, a blind algorithm is proposed for CFO estimation by means of DCO compensation and power leakage minimization. Performance of the proposed algorithm is demonstrated by simulations.

  10. A novel time varying signal processing method for Coriolis mass flowmeter.

    PubMed

    Shen, Ting-Ao; Tu, Ya-Qing; Zhang, Hai-Tao

    2014-06-01

    The precision of frequency tracking method and phase difference calculation method affects the measurement precision of Coriolis Mass Flowmeter directly. To improve the accuracy of the mass flowrate, a novel signal processing method for Coriolis Mass Flowmeter is proposed for this time varying signal, which is comprised of a modified adaptive lattice notch filter and a revised sliding recursive discrete-time Fourier transform algorithm. The method cannot only track the change of frequency continuously, but also ensure the calculation accuracy when measuring phase difference. The computational load of the proposed method is small with higher accuracy. Simulation and experiment results show that the proposed method is effective.

  11. On stability of cooperative and hereditary systems with a distributed delay

    NASA Astrophysics Data System (ADS)

    Berezansky, Leonid; Braverman, Elena

    2015-06-01

    We consider a system \\frac{dx}{dt}=r_1(t) G_1(x) [ \\inth_1(t)t f_1(y(s))~ds R1 (t,s) - x(t) ] , \\frac{dy}{dt}=r_2(t) G_2(y) [ \\inth_2(t)t f_2(x(s))~ds R2 (t,s) - y(t)] with increasing functions f1 and f2, which has at most one positive equilibrium. Here the values of the functions ri, Gi, fi are positive for positive arguments, the delays in the cooperative term can be distributed and unbounded, both systems with concentrated delays and integro-differential systems are a particular case of the considered system. Analyzing the relation of the functions f1 and f2, we obtain several possible scenarios of the global behaviour. They include the cases when all nontrivial positive solutions tend to the same attractor which can be the positive equilibrium, the origin or infinity. Another possibility is the dependency of asymptotics on the initial conditions: either solutions with large enough initial values tend to the equilibrium, while others tend to zero, or solutions with small enough initial values tend to the equilibrium, while others infinitely grow. In some sense solutions of the equation are intrinsically non-oscillatory: if both initial functions are less/greater than the equilibrium value, so is the solution for any positive time value. The paper continues the study of equations with monotone production functions initiated in Berezansky and Braverman (2013 Nonlinearity 26 2833-49).

  12. Fast Time-Varying Volume Rendering Using Time-Space Partition (TSP) Tree

    NASA Technical Reports Server (NTRS)

    Shen, Han-Wei; Chiang, Ling-Jen; Ma, Kwan-Liu

    1999-01-01

    We present a new, algorithm for rapid rendering of time-varying volumes. A new hierarchical data structure that is capable of capturing both the temporal and the spatial coherence is proposed. Conventional hierarchical data structures such as octrees are effective in characterizing the homogeneity of the field values existing in the spatial domain. However, when treating time merely as another dimension for a time-varying field, difficulties frequently arise due to the discrepancy between the field's spatial and temporal resolutions. In addition, treating spatial and temporal dimensions equally often prevents the possibility of detecting the coherence that is unique in the temporal domain. Using the proposed data structure, our algorithm can meet the following goals. First, both spatial and temporal coherence are identified and exploited for accelerating the rendering process. Second, our algorithm allows the user to supply the desired error tolerances at run time for the purpose of image-quality/rendering-speed trade-off. Third, the amount of data that are required to be loaded into main memory is reduced, and thus the I/O overhead is minimized. This low I/O overhead makes our algorithm suitable for out-of-core applications.

  13. First order coupled dynamic model of flexible space structures with time-varying configurations

    NASA Astrophysics Data System (ADS)

    Wang, Jie; Li, Dongxu; Jiang, Jianping

    2017-03-01

    This paper proposes a first order coupled dynamic modeling method for flexible space structures with time-varying configurations for the purpose of deriving the characteristics of the system. The model considers the first time derivative of the coordinate transformation matrix between the platform's body frame and the appendage's floating frame. As a result it can accurately predict characteristics of the system even if flexible appendages rotate with complex trajectory relative to the rigid part. In general, flexible appendages are fixed on the rigid platform or forced to rotate with a slow angular velocity. So only the zero order of the transformation matrix is considered in conventional models. However, due to neglecting of time-varying terms of the transformation matrix, these models introduce severe error when appendages, like antennas, for example, rotate with a fast speed relative to the platform. The first order coupled dynamic model for flexible space structures proposed in this paper resolve this problem by introducing the first time derivative of the transformation matrix. As a numerical example, a central core with a rotating solar panel is considered and the results are compared with those given by the conventional model. It has been shown that the first order terms are of great importance on the attitude of the rigid body and dynamic response of the flexible appendage.

  14. Impact of Time-Varying Treatment Exposures on the Risk of Venous Thromboembolism in Multiple Myeloma

    PubMed Central

    Brown, Joshua D.; Adams, Val R.; Moga, Daniela C.

    2016-01-01

    Multiple myeloma (MM) has one of the highest risks of venous thromboembolism (VTE) of all cancers due to pathologic changes and treatment-related exposures. This study assessed the one-year incidence of VTE in newly diagnosed MM and to determine the baseline and time-varying treatment-related factors associated with VTE risk in a U.S.-based cohort. MM patients were identified and age, gender, and baseline comorbidities were determined. Treatment-related exposures included thalidomide derivatives (IMIDs), proteasome inhibitors, cytotoxic chemotherapy, steroids, erythropoietin-stimulating agents (ESAs), stem cell transplants (SCT), hospitalizations, infection, and central venous catheters (CVC). Multiple statistical models were used including a baseline competing risks model, a time-varying exposure Cox proportional hazard (CPH) model, and a case-time-control analysis. The overall incidence of VTE was 107.2 per 1000 person-years with one-half of the VTEs occurring in the first 90 days. The baseline model showed that increasing age, heart failure, and hypertension were associated with one-year incidence of VTE. MM-specific IMID treatment had lower than expected associations with VTE based on prior literature. Instead, exposure to ESAs, SCT, CVC, and infection had higher associations. Based on these results, VTE risk in MM may be less straightforward than considering only chemotherapy exposures, and other treatment-related exposures should be considered to determine patient risk. PMID:27999418

  15. Non-Invasive Neuromodulation Using Time-Varying Caloric Vestibular Stimulation

    PubMed Central

    Rogers, Lesco L.; Ade, Kristen K.; Nicoletto, Heather A.; Adkins, Heather D.; Laskowitz, Daniel T.

    2016-01-01

    Caloric vestibular stimulation (CVS) to elicit the vestibulo-ocular reflex has long been used in clinical settings to aid in the diagnosis of balance disorders and to confirm the absence of brainstem function. While a number of studies have hinted at the potential therapeutic applications of CVS, the limitations of existing devices have frustrated that potential. Current CVS irrigators use water or air during short-duration applications; however, this approach is not tenable for longer duration therapeutic protocols or home use. Here, we describe a solid-state CVS device we developed in order to address these limitations. This device delivers tightly controlled time-varying thermal waveforms, which can be programmed through an external control unit. It contains several safety features, which limit patients to the prescribed waveform and prevent the potential for temperature extremes. In this paper, we provide evidence that CVS treatment with time-varying, but not constant temperature waveforms, elicits changes in cerebral blood flow physiology consistent with the neuromodulation of brainstem centers, and we present results from a small pilot study, which demonstrate that the CVS can safely and feasibly be used longitudinally in the home setting to treat episodic migraine. Together, these results indicate that this solid-state CVS device may be a viable tool for non-invasive neuromodulation. PMID:27777829

  16. Time-instant sampling based encoding of time-varying acoustic spectrum

    NASA Astrophysics Data System (ADS)

    Sharma, Neeraj Kumar

    2015-12-01

    The inner ear has been shown to characterize an acoustic stimuli by transducing fluid motion in the inner ear to mechanical bending of stereocilia on the inner hair cells (IHCs). The excitation motion/energy transferred to an IHC is dependent on the frequency spectrum of the acoustic stimuli, and the spatial location of the IHC along the length of the basilar membrane (BM). Subsequently, the afferent auditory nerve fiber (ANF) bundle samples the encoded waveform in the IHCs by synapsing with them. In this work we focus on sampling of information by afferent ANFs from the IHCs, and show computationally that sampling at specific time instants is sufficient for decoding of time-varying acoustic spectrum embedded in the acoustic stimuli. The approach is based on sampling the signal at its zero-crossings and higher-order derivative zero-crossings. We show results of the approach on time-varying acoustic spectrum estimation from cricket call signal recording. The framework gives a time-domain and non-spatial processing perspective to auditory signal processing. The approach works on the full band signal, and is devoid of modeling any bandpass filtering mimicking the BM action. Instead, we motivate the approach from the perspective of event-triggered sampling by afferent ANFs on the stimuli encoded in the IHCs. Though the approach gives acoustic spectrum estimation but it is shallow on its complete understanding for plausible bio-mechanical replication with current mammalian auditory mechanics insights.

  17. Tracking of time-varying genomic regulatory networks with a LASSO-Kalman smoother

    PubMed Central

    2014-01-01

    It is widely accepted that cellular requirements and environmental conditions dictate the architecture of genetic regulatory networks. Nonetheless, the status quo in regulatory network modeling and analysis assumes an invariant network topology over time. In this paper, we refocus on a dynamic perspective of genetic networks, one that can uncover substantial topological changes in network structure during biological processes such as developmental growth. We propose a novel outlook on the inference of time-varying genetic networks, from a limited number of noisy observations, by formulating the network estimation as a target tracking problem. We overcome the limited number of observations (small n large p problem) by performing tracking in a compressed domain. Assuming linear dynamics, we derive the LASSO-Kalman smoother, which recursively computes the minimum mean-square sparse estimate of the network connectivity at each time point. The LASSO operator, motivated by the sparsity of the genetic regulatory networks, allows simultaneous signal recovery and compression, thereby reducing the amount of required observations. The smoothing improves the estimation by incorporating all observations. We track the time-varying networks during the life cycle of the Drosophila melanogaster. The recovered networks show that few genes are permanent, whereas most are transient, acting only during specific developmental phases of the organism. PMID:24517200

  18. Exploratory Analysis in Time-Varying Data Sets: a Healthcare Network Application.

    PubMed

    Manukyan, Narine; Eppstein, Margaret J; Horbar, Jeffrey D; Leahy, Kathleen A; Kenny, Michael J; Mukherjee, Shreya; Rizzo, Donna M

    2013-07-01

    We introduce a new method for exploratory analysis of large data sets with time-varying features, where the aim is to automatically discover novel relationships between features (over some time period) that are predictive of any of a number of time-varying outcomes (over some other time period). Using a genetic algorithm, we co-evolve (i) a subset of predictive features, (ii) which attribute will be predicted (iii) the time period over which to assess the predictive features, and (iv) the time period over which to assess the predicted attribute. After validating the method on 15 synthetic test problems, we used the approach for exploratory analysis of a large healthcare network data set. We discovered a strong association, with 100% sensitivity, between hospital participation in multi-institutional quality improvement collaboratives during or before 2002, and changes in the risk-adjusted rates of mortality and morbidity observed after a 1-2 year lag. The proposed approach is a potentially powerful and general tool for exploratory analysis of a wide range of time-series data sets.

  19. Biomechanics of cell membrane under low-frequency time-varying magnetic field: a shell model.

    PubMed

    Ye, Hui; Curcuru, Austen

    2016-12-01

    Cell membrane deforms in the electromagnetic field, suggesting an interesting control of cellular physiology by the field. Previous research has focused on the biomechanical analysis of membrane deformation under electric fields that are generated by electrodes. An alternative, noninvasive method to generate an electric field is the use of electromagnetic induction with a time-varying magnetic field, such as that used for transcranial magnetic stimulation (TMS). Although references reporting the magnetic control of cellular mechanics have recently emerged, theoretical analysis of the membrane biomechanics under a time-varying magnetic field is inadequate. We developed a cell model that included the membrane as a low-conductive, capacitive shell and investigated the electric pressure generated on the membrane by a low-frequency magnetic field (0-200 kHz). Our results show that externally applied magnetic field induced surface charges on both sides of the membrane. The charges interacted with the induced electric field to produce a radial pressure upon the membrane. Under the low-frequency range, the radial pressure pulled the cell membrane along the axis that was defined by the magnetically induced electric field. The radial pressure was a function of the field frequency, the conductivity ratio of the cytoplasm to the medium, and the size of the cell. It is quantitatively insignificant in deforming the membrane at the frequency used in TMS, but could be significant at a relatively higher-frequency range (>100 kHz).

  20. A GPU-Accelerated Approach for Feature Tracking in Time-Varying Imagery Datasets.

    PubMed

    Peng, Chao; Sahani, Saindip; Rushing, John

    2016-12-09

    We propose a novel parallel Connected Component Labeling (CCL) algorithm along with efficient out-of-core data management to detect and track feature regions of large time-varying imagery datasets. Our approach contributes to big data field with parallel algorithms tailored for GPU architectures. We remove the data dependency between frames and achieve pixel-level parallelism. Due to the large size, the entire dataset cannot fit into cached memory. Frames have to be streamed through the memory hierarchy (disk to CPU main memory and then to GPU memory), partitioned and processed as batches, where each batch is small enough to fit into the GPU. To reconnect separated feature regions caused by data partitioning, we present a novel batch merging algorithm that extracts the connection information of feature regions in multiple batches in a parallel fashion. The information is organized in a memory-efficient structure and supports fast indexing on the GPU. For the experiment we use a real-world weather dataset. Using a commodity workstation equipped with a single GPU, our approach can process terabytes of time-varying imagery data. The advantages of our approach are demonstrated by comparing to the performance of a CPU cluster implementation that is being used by weather scientists.

  1. Quantifying Time-Varying Multiunit Neural Activity Using Entropy-Based Measures

    PubMed Central

    Choi, Young-Seok; Koenig, Matthew A.; Jia, Xiaofeng

    2011-01-01

    Modern microelectrode arrays make it possible to simultaneously record population neural activity. However, methods to analyze multiunit activity (MUA), which reflects the aggregate spiking activity of a population of neurons, have remained underdeveloped in comparison to those used for studying single unit activity (SUA). In scenarios where SUA is hard to record and maintain or is not representative of brain’s response, MUA is informative in deciphering the brain’s complex time-varying response to stimuli or to clinical insults. Here, we present two quantitative methods of analysis of the time-varying dynamics of MUA without spike detection. These methods are based on the multiresolution discrete wavelet transform (DWT) of an envelope of MUA (eMUA) followed by information theoretic measures: multiresolution entropy (MRE) and the multiresolution Kullback–Leibler distance (MRKLD).We test the proposed quantifiers on both simulated and experimental MUA recorded from rodent cortex in an experimental model of global hypoxic–ischemic brain injury. First, our results validate the use of the eMUA as an alternative to detecting and analyzing transient and complex spike activity. Second, the MRE and MRKLD are shown to respond to dynamic changes due to the brain’s response to global injury and to identify the transient changes in the MUA. PMID:20460201

  2. Shape Morphing of an Elastic Cylinder via Time-Varying Internal Viscous Flows

    NASA Astrophysics Data System (ADS)

    Elbaz, Shai; Gat, Amir

    2013-11-01

    Viscous flows in contact with an elastic body apply both pressure and shear stress on the solid-liquid interface and thus create internal stress- and deformation-fields within the solid structure. We study the interaction between elastic slender axi-symmetric structures and internal time-varying viscous flows as a tool to create controlled shape-morphing of such elastic cylindrical structures. We neglect inertia in the liquid and solid and focus on two cases. Case 1 is viscous flow through a hollow elastic cylinder and case 2 is axial flow in the shallow gap created by two concentric cylinders, where the internal cylinder is rigid and the external elastic. For case 1, we obtain a linear diffusion equation and for case 2 we obtain a non-linear diffusion equation governing the deformation. Solutions for both cases allowing control of the time varying deformation field by way of controlling the liquid pressure at the inlet and outlet are presented. This research is of interest to applications such as micro-swimmers and soft-robotics. This research was supported by the ISRAEL SCIENCE FOUNDATION (Grant No. 818/13).

  3. Modeling ventricular function during cardiac assist: does time-varying elastance work?

    PubMed

    Vandenberghe, Stijn; Segers, Patrick; Steendijk, Paul; Meyns, Bart; Dion, Robert A E; Antaki, James F; Verdonck, Pascal

    2006-01-01

    The time-varying elastance theory of Suga et al. is widely used to simulate left ventricular function in mathematical models and in contemporary in vitro models. We investigated the validity of this theory in the presence of a left ventricular assist device. Left ventricular pressure and volume data are presented that demonstrate the heart-device interaction for a positive-displacement pump (Novacor) and a rotary blood pump (Medos). The Novacor was implanted in a calf and used in fixed-rate mode (85 BPM), whereas the Medos was used at several flow levels (0-3 l/min) in seven healthy sheep. The Novacor data display high beat-to-beat variations in the amplitude of the elastance curve, and the normalized curves deviate strongly from the typical bovine curve. The Medos data show how the maximum elastance depends on the pump flow level. We conclude that the original time-varying elastance theory insufficiently models the complex hemodynamic behavior of a left ventricle that is mechanically assisted, and that there is need for an updated ventricular model to simulate the heart-device interaction.

  4. Time-Varying Multifractal Characteristics and Formation Mechanism of Loaded Coal Electromagnetic Radiation

    NASA Astrophysics Data System (ADS)

    Hu, Shaobin; Wang, Enyuan; Li, Zhonghui; Shen, Rongxi; Liu, Jie

    2014-09-01

    Dynamic collapses of deeply mined coal rocks are severe threats to miners. To predict the collapses more accurately using electromagnetic radiation (EMR), we investigate the time-varying multifractal characteristics and formation mechanism of EMR induced by underground coal mining. A series of uniaxial compression and multi-stage loading experiments with coal samples of different mechanical properties were carried out. The EMR signals during their damage evolution were monitored in real-time; the inherent law of EMR time series was analyzed by fractal theory. The results show that the time-varying multifractal characteristics of EMR are determined by damage evolutions process, the dissipated energy caused by damage evolutions such as crack propagation, fractal sliding and shearing can be regard as the fingerprint of various EMR micro-mechanics. Based on the Irreversible thermodynamics and damage mechanics, we introduced the damage internal variable, constructed the dissipative potential function and established the coupled model of the EMR and the dissipative energy, which revealed the nature of dynamic nonlinear characteristics of EMR. Dynamic multifractal spectrum is the objective response of EMR signals, thus it can be used to evaluate the coal deformation and fracture process.

  5. Time-varying coupling functions: Dynamical inference and cause of synchronization transitions

    NASA Astrophysics Data System (ADS)

    Stankovski, Tomislav

    2017-02-01

    Interactions in nature can be described by their coupling strength, direction of coupling, and coupling function. The coupling strength and directionality are relatively well understood and studied, at least for two interacting systems; however, there can be a complexity in the interactions uniquely dependent on the coupling functions. Such a special case is studied here: synchronization transition occurs only due to the time variability of the coupling functions, while the net coupling strength is constant throughout the observation time. To motivate the investigation, an example is used to present an analysis of cross-frequency coupling functions between delta and alpha brain waves extracted from the electroencephalography recording of a healthy human subject in a free-running resting state. The results indicate that time-varying coupling functions are a reality for biological interactions. A model of phase oscillators is used to demonstrate and detect the synchronization transition caused by the varying coupling functions during an invariant coupling strength. The ability to detect this phenomenon is discussed with the method of dynamical Bayesian inference, which was able to infer the time-varying coupling functions. The form of the coupling function acts as an additional dimension for the interactions, and it should be taken into account when detecting biological or other interactions from data.

  6. Identification of time-varying structural dynamic systems - An artificial intelligence approach

    NASA Technical Reports Server (NTRS)

    Glass, B. J.; Hanagud, S.

    1992-01-01

    An application of the artificial intelligence-derived methodologies of heuristic search and object-oriented programming to the problem of identifying the form of the model and the associated parameters of a time-varying structural dynamic system is presented in this paper. Possible model variations due to changes in boundary conditions or configurations of a structure are organized into a taxonomy of models, and a variant of best-first search is used to identify the model whose simulated response best matches that of the current physical structure. Simulated model responses are verified experimentally. An output-error approach is used in a discontinuous model space, and an equation-error approach is used in the parameter space. The advantages of the AI methods used, compared with conventional programming techniques for implementing knowledge structuring and inheritance, are discussed. Convergence conditions and example problems have been discussed. In the example problem, both the time-varying model and its new parameters have been identified when changes occur.

  7. Time-varying coupling functions: Dynamical inference and cause of synchronization transitions.

    PubMed

    Stankovski, Tomislav

    2017-02-01

    Interactions in nature can be described by their coupling strength, direction of coupling, and coupling function. The coupling strength and directionality are relatively well understood and studied, at least for two interacting systems; however, there can be a complexity in the interactions uniquely dependent on the coupling functions. Such a special case is studied here: synchronization transition occurs only due to the time variability of the coupling functions, while the net coupling strength is constant throughout the observation time. To motivate the investigation, an example is used to present an analysis of cross-frequency coupling functions between delta and alpha brain waves extracted from the electroencephalography recording of a healthy human subject in a free-running resting state. The results indicate that time-varying coupling functions are a reality for biological interactions. A model of phase oscillators is used to demonstrate and detect the synchronization transition caused by the varying coupling functions during an invariant coupling strength. The ability to detect this phenomenon is discussed with the method of dynamical Bayesian inference, which was able to infer the time-varying coupling functions. The form of the coupling function acts as an additional dimension for the interactions, and it should be taken into account when detecting biological or other interactions from data.

  8. Time-varying singular value decomposition for periodic transient identification in bearing fault diagnosis

    NASA Astrophysics Data System (ADS)

    Zhang, Shangbin; Lu, Siliang; He, Qingbo; Kong, Fanrang

    2016-09-01

    For rotating machines, the defective faults of bearings generally are represented as periodic transient impulses in acquired signals. The extraction of transient features from signals has been a key issue for fault diagnosis. However, the background noise reduces identification performance of periodic faults in practice. This paper proposes a time-varying singular value decomposition (TSVD) method to enhance the identification of periodic faults. The proposed method is inspired by the sliding window method. By applying singular value decomposition (SVD) to the signal under a sliding window, we can obtain a time-varying singular value matrix (TSVM). Each column in the TSVM is occupied by the singular values of the corresponding sliding window, and each row represents the intrinsic structure of the raw signal, namely time-singular-value-sequence (TSVS). Theoretical and experimental analyses show that the frequency of TSVS is exactly twice that of the corresponding intrinsic structure. Moreover, the signal-to-noise ratio (SNR) of TSVS is improved significantly in comparison with the raw signal. The proposed method takes advantages of the TSVS in noise suppression and feature extraction to enhance fault frequency for diagnosis. The effectiveness of the TSVD is verified by means of simulation studies and applications to diagnosis of bearing faults. Results indicate that the proposed method is superior to traditional methods for bearing fault diagnosis.

  9. The Time-Varying Relationship between Mortality and Business Cycles in the USA.

    PubMed

    Lam, Jean-Paul; Piérard, Emmanuelle

    2017-02-01

    We examine the relationship between total mortality, deaths due to motor vehicle accidents, cardiovascular disease and measures of business cycles for the USA, using a time-varying parameter model for the periods 1961-2010. We first present a theoretical model to outline the transmission mechanism from business cycles to health status, to motivate our empirical framework and to explain why the relationship between mortality and the economy may have changed over time. We find overwhelming evidence of structural breaks in the relationship between mortality and business cycles over the sample period. Overall, the relationship between total mortality, cardiovascular mortality and the economy has become less procyclical over time and even countercyclical in recent times for certain age groups. Deaths due to motor vehicle accidents have remained strongly procyclical. Using drugs and medical patent data and data on hours worked, we argue that important advances in medical technology and changes in the effects that working hours have on health are important reasons for this time-varying relationship. Copyright © 2015 John Wiley & Sons, Ltd.

  10. Time-varying land subsidence detected by radar altimetry: California, Taiwan and north China

    PubMed Central

    Hwang, Cheinway; Yang, Yuande; Kao, Ricky; Han, Jiancheng; Shum, C. K.; Galloway, Devin L.; Sneed, Michelle; Hung, Wei-Chia; Cheng, Yung-Sheng; Li, Fei

    2016-01-01

    Contemporary applications of radar altimetry include sea-level rise, ocean circulation, marine gravity, and icesheet elevation change. Unlike InSAR and GNSS, which are widely used to map surface deformation, altimetry is neither reliant on highly temporally-correlated ground features nor as limited by the available spatial coverage, and can provide long-term temporal subsidence monitoring capability. Here we use multi-mission radar altimetry with an approximately 23 year data-span to quantify land subsidence in cropland areas. Subsidence rates from TOPEX/POSEIDON, JASON-1, ENVISAT, and JASON-2 during 1992–2015 show time-varying trends with respect to displacement over time in California’s San Joaquin Valley and central Taiwan, possibly related to changes in land use, climatic conditions (drought) and regulatory measures affecting groundwater use. Near Hanford, California, subsidence rates reach 18 cm yr−1 with a cumulative subsidence of 206 cm, which potentially could adversely affect operations of the planned California High-Speed Rail. The maximum subsidence rate in central Taiwan is 8 cm yr−1. Radar altimetry also reveals time-varying subsidence in the North China Plain consistent with the declines of groundwater storage and existing water infrastructure detected by the Gravity Recovery And Climate Experiment (GRACE) satellites, with rates reaching 20 cm yr−1 and cumulative subsidence as much as 155 cm. PMID:27324935

  11. Physiological and Molecular Genetic Effects of Time-Varying Electromagnetic Fields on Human Neuronal Cells

    NASA Technical Reports Server (NTRS)

    Goodwin, Thomas J.

    2003-01-01

    The present investigation details the development of model systems for growing two- and three-dimensional human neural progenitor cells within a culture medium facilitated by a time-varying electromagnetic field (TVEMF). The cells and culture medium are contained within a two- or three-dimensional culture vessel, and the electromagnetic field is emitted from an electrode or coil. These studies further provide methods to promote neural tissue regeneration by means of culturing the neural cells in either configuration. Grown in two dimensions, neuronal cells extended longitudinally, forming tissue strands extending axially along and within electrodes comprising electrically conductive channels or guides through which a time-varying electrical current was conducted. In the three-dimensional aspect, exposure to TVEMF resulted in the development of three-dimensional aggregates, which emulated organized neural tissues. In both experimental configurations, the proliferation rate of the TVEMF cells was 2.5 to 4.0 times the rate of the non-waveform cells. Each of the experimental embodiments resulted in similar molecular genetic changes regarding the growth potential of the tissues as measured by gene chip analyses, which measured more than 10,000 human genes simultaneously.

  12. Time-varying land subsidence detected by radar altimetry: California, Taiwan and north China

    USGS Publications Warehouse

    Hwang, Cheinway; Yang, Yuande; Kao, Ricky; Han, Jiancheng; Shum, C.K.; Galloway, Devin L.; Sneed, Michelle; Hung, Wei-Chia; Cheng, Yung-Sheng; Li, Fei

    2016-01-01

    Contemporary applications of radar altimetry include sea-level rise, ocean circulation, marine gravity, and ice sheet elevation change. Unlike InSAR and GNSS, which are widely used to map surface deformation, altimetry is neither reliant on highly temporally-correlated ground features nor as limited by the available spatial coverage, and can provide long-term temporal subsidence monitoring capability. Here we use multi-mission radar altimetry with an approximately 23 year data-span to quantify land subsidence in cropland areas. Subsidence rates from TOPEX/POSEIDON, JASON-1, ENVISAT, and JASON-2 during 1992–2015 show time-varying trends with respect to displacement over time in California’s San Joaquin Valley and central Taiwan, possibly related to changes in land use, climatic conditions (drought) and regulatory measures affecting groundwater use. Near Hanford, California, subsidence rates reach 18 cm/yr with a cumulative subsidence of 206 cm, which potentially could adversely affect operations of the planned California High-Speed Rail. The maximum subsidence rate in central Taiwan is 8 cm/yr. Radar altimetry also reveals time-varying subsidence in the North China Plain consistent with the declines of groundwater storage and existing water infrastructure detected by the Gravity Recovery And Climate Experiment (GRACE) satellites, with rates reaching 20 cm/yr and cumulative subsidence as much as 155 cm.

  13. Time-varying land subsidence detected by radar altimetry: California, Taiwan and north China.

    PubMed

    Hwang, Cheinway; Yang, Yuande; Kao, Ricky; Han, Jiancheng; Shum, C K; Galloway, Devin L; Sneed, Michelle; Hung, Wei-Chia; Cheng, Yung-Sheng; Li, Fei

    2016-06-21

    Contemporary applications of radar altimetry include sea-level rise, ocean circulation, marine gravity, and icesheet elevation change. Unlike InSAR and GNSS, which are widely used to map surface deformation, altimetry is neither reliant on highly temporally-correlated ground features nor as limited by the available spatial coverage, and can provide long-term temporal subsidence monitoring capability. Here we use multi-mission radar altimetry with an approximately 23 year data-span to quantify land subsidence in cropland areas. Subsidence rates from TOPEX/POSEIDON, JASON-1, ENVISAT, and JASON-2 during 1992-2015 show time-varying trends with respect to displacement over time in California's San Joaquin Valley and central Taiwan, possibly related to changes in land use, climatic conditions (drought) and regulatory measures affecting groundwater use. Near Hanford, California, subsidence rates reach 18 cm yr(-1) with a cumulative subsidence of 206 cm, which potentially could adversely affect operations of the planned California High-Speed Rail. The maximum subsidence rate in central Taiwan is 8 cm yr(-1). Radar altimetry also reveals time-varying subsidence in the North China Plain consistent with the declines of groundwater storage and existing water infrastructure detected by the Gravity Recovery And Climate Experiment (GRACE) satellites, with rates reaching 20 cm yr(-1) and cumulative subsidence as much as 155 cm.

  14. Time-varying land subsidence detected by radar altimetry: California, Taiwan and north China

    NASA Astrophysics Data System (ADS)

    Hwang, Cheinway; Yang, Yuande; Kao, Ricky; Han, Jiancheng; Shum, C. K.; Galloway, Devin L.; Sneed, Michelle; Hung, Wei-Chia; Cheng, Yung-Sheng; Li, Fei

    2016-06-01

    Contemporary applications of radar altimetry include sea-level rise, ocean circulation, marine gravity, and icesheet elevation change. Unlike InSAR and GNSS, which are widely used to map surface deformation, altimetry is neither reliant on highly temporally-correlated ground features nor as limited by the available spatial coverage, and can provide long-term temporal subsidence monitoring capability. Here we use multi-mission radar altimetry with an approximately 23 year data-span to quantify land subsidence in cropland areas. Subsidence rates from TOPEX/POSEIDON, JASON-1, ENVISAT, and JASON-2 during 1992–2015 show time-varying trends with respect to displacement over time in California’s San Joaquin Valley and central Taiwan, possibly related to changes in land use, climatic conditions (drought) and regulatory measures affecting groundwater use. Near Hanford, California, subsidence rates reach 18 cm yr‑1 with a cumulative subsidence of 206 cm, which potentially could adversely affect operations of the planned California High-Speed Rail. The maximum subsidence rate in central Taiwan is 8 cm yr‑1. Radar altimetry also reveals time-varying subsidence in the North China Plain consistent with the declines of groundwater storage and existing water infrastructure detected by the Gravity Recovery And Climate Experiment (GRACE) satellites, with rates reaching 20 cm yr‑1 and cumulative subsidence as much as 155 cm.

  15. Application of extremum seeking for time-varying systems to resonance control of RF cavities

    SciTech Connect

    Scheinker, Alexander

    2016-09-13

    A recently developed form of extremum seeking for time-varying systems is implemented in hardware for the resonance control of radio-frequency cavities without phase measurements. Normal conducting RF cavity resonance control is performed via a slug tuner, while superconducting TESLA-type cavity resonance control is performed via piezo actuators. The controller maintains resonance by minimizing reflected power by utilizing model-independent adaptive feedback. Unlike standard phase-measurement-based resonance control, the presented approach is not sensitive to arbitrary phase shifts of the RF signals due to temperature-dependent cable length or phasemeasurement hardware changes. The phase independence of this method removes common slowly varying drifts and required periodic recalibration of phase-based methods. A general overview of the adaptive controller is presented along with the proof of principle experimental results at room temperature. Lastly, this method allows us to both maintain a cavity at a desired resonance frequency and also to dynamically modify its resonance frequency to track the unknown time-varying frequency of an RF source, thereby maintaining maximal cavity field strength, based only on power-level measurements.

  16. Application of extremum seeking for time-varying systems to resonance control of RF cavities

    DOE PAGES

    Scheinker, Alexander

    2016-09-13

    A recently developed form of extremum seeking for time-varying systems is implemented in hardware for the resonance control of radio-frequency cavities without phase measurements. Normal conducting RF cavity resonance control is performed via a slug tuner, while superconducting TESLA-type cavity resonance control is performed via piezo actuators. The controller maintains resonance by minimizing reflected power by utilizing model-independent adaptive feedback. Unlike standard phase-measurement-based resonance control, the presented approach is not sensitive to arbitrary phase shifts of the RF signals due to temperature-dependent cable length or phasemeasurement hardware changes. The phase independence of this method removes common slowly varying drifts andmore » required periodic recalibration of phase-based methods. A general overview of the adaptive controller is presented along with the proof of principle experimental results at room temperature. Lastly, this method allows us to both maintain a cavity at a desired resonance frequency and also to dynamically modify its resonance frequency to track the unknown time-varying frequency of an RF source, thereby maintaining maximal cavity field strength, based only on power-level measurements.« less

  17. Modeling the time--varying subjective quality of HTTP video streams with rate adaptations.

    PubMed

    Chen, Chao; Choi, Lark Kwon; de Veciana, Gustavo; Caramanis, Constantine; Heath, Robert W; Bovik, Alan C

    2014-05-01

    Newly developed hypertext transfer protocol (HTTP)-based video streaming technologies enable flexible rate-adaptation under varying channel conditions. Accurately predicting the users' quality of experience (QoE) for rate-adaptive HTTP video streams is thus critical to achieve efficiency. An important aspect of understanding and modeling QoE is predicting the up-to-the-moment subjective quality of a video as it is played, which is difficult due to hysteresis effects and nonlinearities in human behavioral responses. This paper presents a Hammerstein-Wiener model for predicting the time-varying subjective quality (TVSQ) of rate-adaptive videos. To collect data for model parameterization and validation, a database of longer duration videos with time-varying distortions was built and the TVSQs of the videos were measured in a large-scale subjective study. The proposed method is able to reliably predict the TVSQ of rate adaptive videos. Since the Hammerstein-Wiener model has a very simple structure, the proposed method is suitable for online TVSQ prediction in HTTP-based streaming.

  18. Inferring the mesoscale structure of layered, edge-valued, and time-varying networks

    NASA Astrophysics Data System (ADS)

    Peixoto, Tiago P.

    2015-10-01

    Many network systems are composed of interdependent but distinct types of interactions, which cannot be fully understood in isolation. These different types of interactions are often represented as layers, attributes on the edges, or as a time dependence of the network structure. Although they are crucial for a more comprehensive scientific understanding, these representations offer substantial challenges. Namely, it is an open problem how to precisely characterize the large or mesoscale structure of network systems in relation to these additional aspects. Furthermore, the direct incorporation of these features invariably increases the effective dimension of the network description, and hence aggravates the problem of overfitting, i.e., the use of overly complex characterizations that mistake purely random fluctuations for actual structure. In this work, we propose a robust and principled method to tackle these problems, by constructing generative models of modular network structure, incorporating layered, attributed and time-varying properties, as well as a nonparametric Bayesian methodology to infer the parameters from data and select the most appropriate model according to statistical evidence. We show that the method is capable of revealing hidden structure in layered, edge-valued, and time-varying networks, and that the most appropriate level of granularity with respect to the additional dimensions can be reliably identified. We illustrate our approach on a variety of empirical systems, including a social network of physicians, the voting correlations of deputies in the Brazilian national congress, the global airport network, and a proximity network of high-school students.

  19. PIV measurements of flow in a centrifugal blood pump: time-varying flow.

    PubMed

    Day, Steven W; McDaniel, James C

    2005-04-01

    Measurements of the time-varying flow in a centrifugal blood pump operating as a left ventricular assist device (LVAD) are presented. This includes changes in both the pump flow rate as a function of the left ventricle contraction and the interaction of the rotating impeller and fixed exit volute. When operating with a pulsing ventricle, the flow rate through the LVAD varies from 0-11 L/min during each cycle of the heartbeat. Phase-averaged measurements of mean velocity and some turbulence statistics within several regions of the pump, including the inlet, blade passage, exit volute, and diffuser, are reported at 20 phases of the cardiac cycle. The transient flow fields are compared to the constant flow rate condition that was reported previously in order to investigate the transient effects within the pump. It is shown that the quasi-steady assumption is a fair treatment of the time varying flow field in all regions of this representative pump, which greatly simplifies the comprehension and modeling of this flow field. The measurements are further interpreted to identify the effects that the transient nature of the flow field will have on blood damage. Although regions of recirculation and stagnant flow exist at some phases of the cardiac cycle, there is no location where flow is stagnant during the entire heartbeat.

  20. Delay-Throughput Performance Evaluator for Distributed Systems. TDMA and Token Ring Schemes (Version 1)

    DTIC Science & Technology

    1990-09-01

    standart deviation (queue-size, simu.) is: 8.976742237234827 mean delay (simulation) is: 113.440046565774200 standard deviation (delay, simulation) is...000000000 99 .000000000 .003205128 >=100 .000000000 .429487179 mean queue-size (simulation) is : 4.856969696969697 standart deviation (queue-size, simu.) is...is ’,qrnean write(6,*) Istandart deviation (queue-size, simu.) is ’,var write(6,*) ’mean delay (simulation) is: ’,wmean write(6,*) ’ standart

  1. Permanence of a predator-prey discrete system with Holling-IV functional response and distributed delays.

    PubMed

    Zhang, X; Wu, Z; Zhou, T

    2016-01-01

    A predator-prey discrete-time model with Holling-IV functional response and distributed delays is investigated in this paper. By using the comparison theorem of the difference equation and some analysis technique, some sufficient conditions are obtained for the permanence of the discrete predator-prey system. Two examples are given to illustrate the feasibility of the obtained result.

  2. Estimating the Attack Ratio of Dengue Epidemics under Time-varying Force of Infection using Aggregated Notification Data

    NASA Astrophysics Data System (ADS)

    Coelho, Flavio Codeço; Carvalho, Luiz Max De

    2015-12-01

    Quantifying the attack ratio of disease is key to epidemiological inference and public health planning. For multi-serotype pathogens, however, different levels of serotype-specific immunity make it difficult to assess the population at risk. In this paper we propose a Bayesian method for estimation of the attack ratio of an epidemic and the initial fraction of susceptibles using aggregated incidence data. We derive the probability distribution of the effective reproductive number, Rt, and use MCMC to obtain posterior distributions of the parameters of a single-strain SIR transmission model with time-varying force of infection. Our method is showcased in a data set consisting of 18 years of dengue incidence in the city of Rio de Janeiro, Brazil. We demonstrate that it is possible to learn about the initial fraction of susceptibles and the attack ratio even in the absence of serotype specific data. On the other hand, the information provided by this approach is limited, stressing the need for detailed serological surveys to characterise the distribution of serotype-specific immunity in the population.

  3. Estimating the Attack Ratio of Dengue Epidemics under Time-varying Force of Infection using Aggregated Notification Data.

    PubMed

    Coelho, Flavio Codeço; de Carvalho, Luiz Max

    2015-12-17

    Quantifying the attack ratio of disease is key to epidemiological inference and public health planning. For multi-serotype pathogens, however, different levels of serotype-specific immunity make it difficult to assess the population at risk. In this paper we propose a Bayesian method for estimation of the attack ratio of an epidemic and the initial fraction of susceptibles using aggregated incidence data. We derive the probability distribution of the effective reproductive number, Rt, and use MCMC to obtain posterior distributions of the parameters of a single-strain SIR transmission model with time-varying force of infection. Our method is showcased in a data set consisting of 18 years of dengue incidence in the city of Rio de Janeiro, Brazil. We demonstrate that it is possible to learn about the initial fraction of susceptibles and the attack ratio even in the absence of serotype specific data. On the other hand, the information provided by this approach is limited, stressing the need for detailed serological surveys to characterise the distribution of serotype-specific immunity in the population.

  4. Intelligent robust control for uncertain nonlinear time-varying systems and its application to robotic systems.

    PubMed

    Chang, Yeong-Chan

    2005-12-01

    This paper addresses the problem of designing adaptive fuzzy-based (or neural network-based) robust controls for a large class of uncertain nonlinear time-varying systems. This class of systems can be perturbed by plant uncertainties, unmodeled perturbations, and external disturbances. Nonlinear H(infinity) control technique incorporated with adaptive control technique and VSC technique is employed to construct the intelligent robust stabilization controller such that an H(infinity) control is achieved. The problem of the robust tracking control design for uncertain robotic systems is employed to demonstrate the effectiveness of the developed robust stabilization control scheme. Therefore, an intelligent robust tracking controller for uncertain robotic systems in the presence of high-degree uncertainties can easily be implemented. Its solution requires only to solve a linear algebraic matrix inequality and a satisfactorily transient and asymptotical tracking performance is guaranteed. A simulation example is made to confirm the performance of the developed control algorithms.

  5. Research plan for establishing the effects of time varying noise exposures on community annoyance and acceptability

    NASA Technical Reports Server (NTRS)

    Borsky, P. N.

    1980-01-01

    The design of a community noise survey to determine the effects of time varying noise exposures in residential communities is presented. Complex physical and human variables involved in the health and welfare effects of environmental noise and the number-level tradeoffs and time of day penalties are among the factors considered. Emphasis is placed on community reactions where noise exposures are equal in day or evening but differ in the night time, and the effects of ambient noise on more intense aircraft noise exposures. Thirteen different times of day and types of operation situations with exposed populations up to 8-10 miles from the airport are identified. A detailed personal interview questionnaire as well as specific instructions to interviewers are included.

  6. Correlation-based characterisation of time-varying dynamical complexity in the Earth's magnetosphere

    NASA Astrophysics Data System (ADS)

    Donner, Reik V.; Balasis, George; Kurths, Jürgen

    2014-05-01

    The dynamical behaviour of the magnetosphere is known to be a sensitive indicator for the response of the system to solar wind coupling. Since the solar activity commonly displays very interesting non-stationary and multi-scale dynamics, the magnetospheric response also exhibits a high degree of dynamical complexity associated with fundamentally different characteristics during periods of quiescence and magnetic storms. The resulting temporal complexity profile has been explored regarding several approaches from applied statistics, dynamical systems theory and statistical mechanics. Here, we propose an alternative way of looking at time-varying dynamical complexity of nonlinear geophysical time series utilising subtle but significant changes in the linear auto-correlation structure of the recorded data. Our approach is demonstrated to sensitively trace the dynamic signatures associated with intense magnetic storms, and to display reasonable skills in distinguishing between quiescence and storm periods. The potentials and methodological limitations of this new viewpoint are discussed in some detail.

  7. Correlation-based characterisation of time-varying dynamical complexity in the Earth's magnetosphere

    NASA Astrophysics Data System (ADS)

    Donner, R. V.; Balasis, G.

    2013-11-01

    The dynamical behaviour of the magnetosphere is known to be a sensitive indicator for the response of the system to solar wind coupling. Since the solar activity commonly displays very interesting non-stationary and multi-scale dynamics, the magnetospheric response also exhibits a high degree of dynamical complexity associated with fundamentally different characteristics during periods of quiescence and magnetic storms. The resulting temporal complexity profile has been explored using several approaches from applied statistics, dynamical systems theory and statistical mechanics. Here, we propose an alternative way of looking at time-varying dynamical complexity of nonlinear geophysical time series utilising subtle but significant changes in the linear autocorrelation structure of the recorded data. Our approach is demonstrated to sensitively trace the dynamic signatures associated with intense magnetic storms, and to display reasonable skills in distinguishing between quiescence and storm periods. The potentials and methodological limitations of this new viewpoint are discussed in some detail.

  8. Induction of Oxidation in Living Cells by Time-Varying Electromagnetic Fields

    NASA Technical Reports Server (NTRS)

    Stolc, Viktor

    2015-01-01

    We are studying how biological systems can harness quantum effects of time varying electromagnetic (EM) waves as the time-setting basis for universal biochemical organization via the redox cycle. The effects of extremely weak EM field on the biochemical redox cycle can be monitored through real-time detection of oxidation-induced light emissions of reporter molecules in living cells. It has been shown that EM fields can also induce changes in fluid transport rates through capillaries (approximately 300 microns inner diameter) by generating annular proton gradients. This effect may be relevant to understanding cardiovascular dis-function in spaceflight, beyond the ionosphere. Importantly, we show that these EM effects can be attenuated using an active EM field cancellation device. Central for NASA's Human Research Program is the fact that the absence of ambient EM field in spaceflight can also have a detrimental influence, namely via increased oxidative damage, on DNA replication, which controls heredity.

  9. Decoding Time-Varying Functional Connectivity Networks via Linear Graph Embedding Methods

    PubMed Central

    Monti, Ricardo P.; Lorenz, Romy; Hellyer, Peter; Leech, Robert; Anagnostopoulos, Christoforos; Montana, Giovanni

    2017-01-01

    An exciting avenue of neuroscientific research involves quantifying the time-varying properties of functional connectivity networks. As a result, many methods have been proposed to estimate the dynamic properties of such networks. However, one of the challenges associated with such methods involves the interpretation and visualization of high-dimensional, dynamic networks. In this work, we employ graph embedding algorithms to provide low-dimensional vector representations of networks, thus facilitating traditional objectives such as visualization, interpretation and classification. We focus on linear graph embedding methods based on principal component analysis and regularized linear discriminant analysis. The proposed graph embedding methods are validated through a series of simulations and applied to fMRI data from the Human Connectome Project. PMID:28373838

  10. A method for the time-varying nonlinear prediction of complex nonstationary biomedical signals.

    PubMed

    Faes, Luca; Chon, Ki H; Nollo, Giandomenico

    2009-02-01

    A method to perform time-varying (TV) nonlinear prediction of biomedical signals in the presence of nonstationarity is presented in this paper. The method is based on identification of TV autoregressive models through expansion of the TV coefficients onto a set of basis functions and on k-nearest neighbor local linear approximation to perform nonlinear prediction. The approach provides reasonable nonlinear prediction even for TV deterministic chaotic signals, which has been a daunting task to date. Moreover, the method is used in conjunction with a TV surrogate method to provide statistical validation that the presence of nonlinearity is not due to nonstationarity itself. The approach is tested on simulated linear and nonlinear signals reproducing both time-invariant (TIV) and TV dynamics to assess its ability to quantify TIV and TV degrees of predictability and detect nonlinearity. Applicative examples relevant to heart rate variability and EEG analyses are then illustrated.

  11. Measurement of speech levels in the presence of time varying background noise

    NASA Technical Reports Server (NTRS)

    Pearsons, K. S.; Horonjeff, R.

    1982-01-01

    Short-term speech level measurements which could be used to note changes in vocal effort in a time varying noise environment were studied. Knowing the changes in speech level would in turn allow prediction of intelligibility in the presence of aircraft flyover noise. Tests indicated that it is possible to use two second samples of speech to estimate long term root mean square speech levels. Other tests were also performed in which people read out loud during aircraft flyover noise. Results of these tests indicate that people do indeed raise their voice during flyovers at a rate of about 3-1/2 dB for each 10 dB increase in background level. This finding is in agreement with other tests of speech levels in the presence of steady state background noise.

  12. Comparison of different Kalman filter approaches in deriving time varying connectivity from EEG data.

    PubMed

    Ghumare, Eshwar; Schrooten, Maarten; Vandenberghe, Rik; Dupont, Patrick

    2015-08-01

    Kalman filter approaches are widely applied to derive time varying effective connectivity from electroencephalographic (EEG) data. For multi-trial data, a classical Kalman filter (CKF) designed for the estimation of single trial data, can be implemented by trial-averaging the data or by averaging single trial estimates. A general linear Kalman filter (GLKF) provides an extension for multi-trial data. In this work, we studied the performance of the different Kalman filtering approaches for different values of signal-to-noise ratio (SNR), number of trials and number of EEG channels. We used a simulated model from which we calculated scalp recordings. From these recordings, we estimated cortical sources. Multivariate autoregressive model parameters and partial directed coherence was calculated for these estimated sources and compared with the ground-truth. The results showed an overall superior performance of GLKF except for low levels of SNR and number of trials.

  13. Robust formation tracking control of mobile robots via one-to-one time-varying communication

    NASA Astrophysics Data System (ADS)

    Dasdemir, Janset; Loría, Antonio

    2014-09-01

    We solve the formation tracking control problem for mobile robots via linear control, under the assumption that each agent communicates only with one 'leader' robot and with one follower, hence forming a spanning-tree topology. We assume that the communication may be interrupted on intervals of time. As in the classical tracking control problem for non-holonomic systems, the swarm is driven by a fictitious robot which moves about freely and which is a leader to one robot only. Our control approach is decentralised and the control laws are linear with time-varying gains; in particular, this accounts for the case when position measurements may be lost over intervals of time. For both velocity-controlled and force-controlled systems, we establish uniform global exponential stability, hence consensus formation tracking, for the error system under a condition of persistency of excitation on the reference angular velocity of the virtual leader and on the control gains.

  14. Design of a Fat-Based Adaptive Visual Servoing for Robots with Time Varying Uncertainties

    NASA Astrophysics Data System (ADS)

    Chien, Ming-Chih; Huang, An-Chyau

    2010-05-01

    Most present adaptive control strategies for visual servoing of robots have assumed that the unknown camera parameters, kinematics, and dynamics of visual servoing system should be linearly parameterized in the regressor matrix form. This is because the limitation of the traditional adaptive design in which the uncertainties should be time-invariant such that all time varying terms in the visual servoing system are collected inside the regressor matrix. However, derivation of the regressor matrix is tedious. In this article, a FAT (function approximation technique) based adaptive controller is designed for visual servo robots without the need for the regressor matrix. A Lyapunov-like analysis is used to justify the closed-loop stability and boundedness of internal signals. Moreover, the upper bounds of tracking errors in the transient state are also derived. Computer simulation results are presented to demonstrate the usefulness of the proposed scheme.

  15. Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach

    NASA Astrophysics Data System (ADS)

    Gu, Huaying; Liu, Zhixue; Weng, Yingliang

    2017-04-01

    The present study applies the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) with spatial effects approach for the analysis of the time-varying conditional correlations and contagion effects among global real estate markets. A distinguishing feature of the proposed model is that it can simultaneously capture the spatial interactions and the dynamic conditional correlations compared with the traditional MGARCH models. Results reveal that the estimated dynamic conditional correlations have exhibited significant increases during the global financial crisis from 2007 to 2009, thereby suggesting contagion effects among global real estate markets. The analysis further indicates that the returns of the regional real estate markets that are in close geographic and economic proximities exhibit strong co-movement. In addition, evidence of significantly positive leverage effects in global real estate markets is also determined. The findings have significant implications on global portfolio diversification opportunities and risk management practices.

  16. Query-Driven Visualization of Time-Varying Adaptive Mesh Refinement Data

    SciTech Connect

    Gosink, Luke J.; Anderson, John C.; Bethel, E. Wes; Joy, Kenneth I.

    2008-08-01

    The visualization and analysis of AMR-based simulations is integral to the process of obtaining new insight in scientific research. We present a new method for performing query-driven visualization and analysis on AMR data, with specific emphasis on time-varying AMR data. Our work introduces a new method that directly addresses the dynamic spatial and temporal properties of AMR grids which challenge many existing visualization techniques. Further, we present the first implementation of query-driven visualization on the GPU that uses a GPU-based indexing structure to both answer queries and efficiently utilize GPU memory. We apply our method to two different science domains to demonstrate its broad applicability.

  17. Time-varying Entry Heating Profile Replication with a Rotating Arc Jet Test Article

    NASA Technical Reports Server (NTRS)

    Grinstead, Jay Henderson; Venkatapathy, Ethiraj; Noyes, Eric A.; Mach, Jeffrey J.; Empey, Daniel M.; White, Todd R.

    2014-01-01

    A new approach for arc jet testing of thermal protection materials at conditions approximating the time-varying conditions of atmospheric entry was developed and demonstrated. The approach relies upon the spatial variation of heat flux and pressure over a cylindrical test model. By slowly rotating a cylindrical arc jet test model during exposure to an arc jet stream, each point on the test model will experience constantly changing applied heat flux. The predicted temporal profile of heat flux at a point on a vehicle can be replicated by rotating the cylinder at a prescribed speed and direction. An electromechanical test model mechanism was designed, built, and operated during an arc jet test to demonstrate the technique.

  18. On-Line Modal State Monitoring of Slowly Time-Varying Structures

    NASA Technical Reports Server (NTRS)

    Johnson, Erik A.; Bergman, Lawrence A.; Voulgaris, Petros G.

    1997-01-01

    Monitoring the dynamic response of structures is often performed for a variety of reasons. These reasons include condition-based maintenance, health monitoring, performance improvements, and control. In many cases the data analysis that is performed is part of a repetitive decision-making process, and in these cases the development of effective on-line monitoring schemes help to speed the decision-making process and reduce the risk of erroneous decisions. This report investigates the use of spatial modal filters for tracking the dynamics of slowly time-varying linear structures. The report includes an overview of modal filter theory followed by an overview of several structural system identification methods. Included in this discussion and comparison are H-infinity, eigensystem realization, and several time-domain least squares approaches. Finally, a two-stage adaptive on-line monitoring scheme is developed and evaluated.

  19. Accelerating Time-Varying Hardware Volume Rendering Using TSP Trees and Color-Based Error Metrics

    NASA Technical Reports Server (NTRS)

    Ellsworth, David; Chiang, Ling-Jen; Shen, Han-Wei; Kwak, Dochan (Technical Monitor)

    2000-01-01

    This paper describes a new hardware volume rendering algorithm for time-varying data. The algorithm uses the Time-Space Partitioning (TSP) tree data structure to identify regions within the data that have spatial or temporal coherence. By using this coherence, the rendering algorithm can improve performance when the volume data is larger than the texture memory capacity by decreasing the amount of textures required. This coherence can also allow improved speed by appropriately rendering flat-shaded polygons instead of textured polygons, and by not rendering transparent regions. To reduce the polygonization overhead caused by the use of the hierarchical data structure, we introduce an optimization method using polygon templates. The paper also introduces new color-based error metrics, which more accurately identify coherent regions compared to the earlier scalar-based metrics. By showing experimental results from runs using different data sets and error metrics, we demonstrate that the new methods give substantial improvements in volume rendering performance.

  20. Estimating time-varying conditional correlations between stock and foreign exchange markets

    NASA Astrophysics Data System (ADS)

    Tastan, Hüseyin

    2006-02-01

    This study explores the dynamic interaction between stock market returns and changes in nominal exchange rates. Many financial variables are known to exhibit fat tails and autoregressive variance structure. It is well-known that unconditional covariance and correlation coefficients also vary significantly over time and multivariate generalized autoregressive model (MGARCH) is able to capture the time-varying variance-covariance matrix for stock market returns and changes in exchange rates. The model is applied to daily Euro-Dollar exchange rates and two stock market indexes from the US economy: Dow-Jones Industrial Average Index and S&P500 Index. The news impact surfaces are also drawn based on the model estimates to see the effects of idiosyncratic shocks in respective markets.

  1. Flatness-based active disturbance rejection control for linear systems with unknown time-varying coefficients

    NASA Astrophysics Data System (ADS)

    Huang, Congzhi; Sira-Ramírez, Hebertt

    2015-12-01

    A flatness-based active disturbance rejection control approach is proposed to deal with the linear systems with unknown time-varying coefficients and external disturbances. By selecting appropriate nominal values for the parameters of the system, all the deviation between the nominal and actual dynamics of the controlled process, as well as all the external disturbances can be viewed as a total disturbance. Based on the accurately estimated total disturbance with the aid of the proposed extended state observer, a linear proportional derivative feedback control law taking into account the derivatives of the desired output is designed to eliminate the effect of the total disturbance on the system performance. Finally, the load frequency control problem of a single-area power system with non-reheated unit is employed as an illustrative example to demonstrate the effectiveness of the proposed approach.

  2. Nonlinear parametrically excited vibration and active control of gear pair system with time-varying characteristic

    NASA Astrophysics Data System (ADS)

    Liu, Shuang; Wang, Jin-Jin; Liu, Jin-Jie; Li, Ya-Qian

    2015-10-01

    In the present work, we investigate the nonlinear parametrically excited vibration and active control of a gear pair system involving backlash, time-varying meshing stiffness and static transmission error. Firstly, a gear pair model is established in a strongly nonlinear form, and its nonlinear vibration characteristics are systematically investigated through different approaches. Several complicated phenomena such as period doubling bifurcation, anti period doubling bifurcation and chaos can be observed under the internal parametric excitation. Then, an active compensation controller is designed to suppress the vibration, including the chaos. Finally, the effectiveness of the proposed controller is verified numerically. Project supported by the National Natural Science Foundation of China (Grant No. 61104040), the Natural Science Foundation of Hebei Province, China (Grant No. E2012203090), and the University Innovation Team of Hebei Province Leading Talent Cultivation Project, China (Grant No. LJRC013).

  3. Psychophysical Models for Signal Detection with Time Varying Uncertainty. Ph.D. Thesis

    NASA Technical Reports Server (NTRS)

    Gai, E.

    1975-01-01

    Psychophysical models for the behavior of the human operator in detection tasks which include change in detectability, correlation between observations and deferred decisions are developed. Classical Signal Detection Theory (SDT) is discussed and its emphasis on the sensory processes is contrasted to decision strategies. The analysis of decision strategies utilizes detection tasks with time varying signal strength. The classical theory is modified to include such tasks and several optimal decision strategies are explored. Two methods of classifying strategies are suggested. The first method is similar to the analysis of ROC curves, while the second is based on the relation between the criterion level (CL) and the detectability. Experiments to verify the analysis of tasks with changes of signal strength are designed. The results show that subjects are aware of changes in detectability and tend to use strategies that involve changes in the CL's.

  4. Lagrangian Descriptors of Thermalized Transition States on Time-Varying Energy Surfaces

    NASA Astrophysics Data System (ADS)

    Craven, Galen T.; Hernandez, Rigoberto

    2015-10-01

    Thermalized chemical reactions driven under dynamical load are characteristic of activated dynamics for arbitrary nonautonomous systems. Recent generalizations of transition state theory to obtain formally exact rates have required the construction of a time-dependent transition state trajectory. Here, we show that Lagrangian descriptors can be used to obtain this structure directly. By developing a phase space separatrix that is void of recrossings, these constructs allow for the principal criterion in the implementation of modern rate theories to be satisfied. Thus, the reactive flux over a time-varying barrier can be determined without ambiguity in chemical reactions. The generality of the formalism suggests that this approach is applicable to any activated system subjected to arbitrary driving and thermal fluctuations.

  5. Quantification of sound instability in embouchure tremor based on the time-varying fundamental frequency.

    PubMed

    Lee, André; Voget, Jakob; Furuya, Shinichi; Morise, Masanori; Altenmüller, Eckart

    2016-05-01

    Task-specific tremor in musicians is an involuntary oscillating muscular activity mostly of the hand or the embouchure, which predominantly occurs while playing the instrument. In contrast to arm or hand tremors, which have been examined and objectified based on movement kinematics and muscular activity, embouchure tremor has not yet been investigated. To quantify and describe embouchure tremor we analysed sound production and investigated the fluctuation of the time-varying fundamental frequency of sustained notes. A comparison between patients with embouchure tremor and healthy controls showed a significantly higher fluctuation of the fundamental frequency for the patients in the high pitch with a tremor frequency range between 3 and 8 Hz. The present findings firstly provide further information about a scarcely described movement disorder and secondly further evaluate a new quantification method for embouchure tremor, which has recently been established for embouchure dystonia.

  6. Quantifying the line-of-sight mass distributions for time-delay lenses with stellar masses

    NASA Astrophysics Data System (ADS)

    Rusu, Cristian; Fassnacht, Chris; Treu, Tommaso; Suyu, Sherry; Auger, Matt; Koopmans, Leon; Marshall, Phil; Wong, Kenneth; Collett, Thomas; Agnello, Adriano; Blandford, Roger; Courbin, Frederic; Hilbert, Stefan; Meylan, Georges; Sluse, Dominique

    2014-12-01

    Measuring cosmological parameters with a realistic account of systematic uncertainties is currently one of the principal challenges of physical cosmology. Building on our recent successes with two gravitationally lensed systems, we have started a program to achieve accurate cosmographic measurements from five gravitationally lensed quasars. We aim at measuring H_0 with an accuracy better than 4%, comparable to but independent from measurements by current BAO, SN or Cepheid programs. The largest current contributor to the error budget in our sample is uncertainty about the line-of-sight mass distribution and environment of the lens systems. In this proposal, we request wide-field u-band imaging of the only lens in our sample without already available Spitzer/IRCA observations, B1608+656. The proposed observations are critical for reducing these uncertainties by providing accurate redshifts and in particular stellar masses for galaxies in the light cones of the target lens system. This will establish lensing as a powerful and independent tool for determining cosmography, in preparation for the hundreds of time-delay lenses that will be discovered by future surveys.

  7. Critical capacity, travel time delays and travel time distribution of rapid mass transit systems

    NASA Astrophysics Data System (ADS)

    Legara, Erika Fille; Monterola, Christopher; Lee, Kee Khoon; Hung, Gih Guang

    2014-07-01

    We set up a mechanistic agent-based model of a rapid mass transit system. Using empirical data from Singapore's unidentifiable smart fare card, we validate our model by reconstructing actual travel demand and duration of travel statistics. We subsequently use this model to investigate two phenomena that are known to significantly affect the dynamics within the RTS: (1) overloading in trains and (2) overcrowding in the RTS platform. We demonstrate that by varying the loading capacity of trains, a tipping point emerges at which an exponential increase in the duration of travel time delays is observed. We also probe the impact on the rail system dynamics of three types of passenger growth distribution across stations: (i) Dirac delta, (ii) uniform and (iii) geometric, which is reminiscent of the effect of land use on transport. Under the assumption of a fixed loading capacity, we demonstrate the dependence of a given origin-destination (OD) pair on the flow volume of commuters in station platforms.

  8. Using Graphs for Fast Error Term Approximation of Time-varying Datasets

    SciTech Connect

    Nuber, C; LaMar, E C; Pascucci, V; Hamann, B; Joy, K I

    2003-02-27

    We present a method for the efficient computation and storage of approximations of error tables used for error estimation of a region between different time steps in time-varying datasets. The error between two time steps is defined as the distance between the data of these time steps. Error tables are used to look up the error between different time steps of a time-varying dataset, especially when run time error computation is expensive. However, even the generation of error tables itself can be expensive. For n time steps, the exact error look-up table (which stores the error values for all pairs of time steps in a matrix) has a memory complexity and pre-processing time complexity of O(n2), and O(1) for error retrieval. Our approximate error look-up table approach uses trees, where the leaf nodes represent original time steps, and interior nodes contain an average (or best-representative) of the children nodes. The error computed on an edge of a tree describes the distance between the two nodes on that edge. Evaluating the error between two different time steps requires traversing a path between the two leaf nodes, and accumulating the errors on the traversed edges. For n time steps, this scheme has a memory complexity and pre-processing time complexity of O(nlog(n)), a significant improvement over the exact scheme; the error retrieval complexity is O(log(n)). As we do not need to calculate all possible n2 error terms, our approach is a fast way to generate the approximation.

  9. Time-varying wing-twist improves aerodynamic efficiency of forward flight in butterflies.

    PubMed

    Zheng, Lingxiao; Hedrick, Tyson L; Mittal, Rajat

    2013-01-01

    Insect wings can undergo significant chordwise (camber) as well as spanwise (twist) deformation during flapping flight but the effect of these deformations is not well understood. The shape and size of butterfly wings leads to particularly large wing deformations, making them an ideal test case for investigation of these effects. Here we use computational models derived from experiments on free-flying butterflies to understand the effect of time-varying twist and camber on the aerodynamic performance of these insects. High-speed videogrammetry is used to capture the wing kinematics, including deformation, of a Painted Lady butterfly (Vanessa cardui) in untethered, forward flight. These experimental results are then analyzed computationally using a high-fidelity, three-dimensional, unsteady Navier-Stokes flow solver. For comparison to this case, a set of non-deforming, flat-plate wing (FPW) models of wing motion are synthesized and subjected to the same analysis along with a wing model that matches the time-varying wing-twist observed for the butterfly, but has no deformation in camber. The simulations show that the observed butterfly wing (OBW) outperforms all the flat-plate wings in terms of usable force production as well as the ratio of lift to power by at least 29% and 46%, respectively. This increase in efficiency of lift production is at least three-fold greater than reported for other insects. Interestingly, we also find that the twist-only-wing (TOW) model recovers much of the performance of the OBW, demonstrating that wing-twist, and not camber is key to forward flight in these insects. The implications of this on the design of flapping wing micro-aerial vehicles are discussed.

  10. Diagnostics for Confounding of Time-varying and Other Joint Exposures.

    PubMed

    Jackson, John W

    2016-11-01

    The effects of joint exposures (or exposure regimes) include those of adhering to assigned treatment versus placebo in a randomized controlled trial, duration of exposure in a cohort study, interactions between exposures, and direct effects of exposure, among others. Unlike the setting of a single point exposure (e.g., propensity score matching), there are few tools to describe confounding for joint exposures or how well a method resolves it. Investigators need tools that describe confounding in ways that are conceptually grounded and intuitive for those who read, review, and use applied research to guide policy. We revisit the implications of exchangeability conditions that hold in sequentially randomized trials, and the bias structure that motivates the use of g-methods, such as marginal structural models. From these, we develop covariate balance diagnostics for joint exposures that can (1) describe time-varying confounding, (2) assess whether covariates are predicted by prior exposures given their past, the indication for g-methods, and (3) describe residual confounding after inverse probability weighting. For each diagnostic, we present time-specific metrics that encompass a wide class of joint exposures, including regimes of multivariate time-varying exposures in censored data, with multivariate point exposures as a special case. We outline how to estimate these directly or with regression and how to average them over person-time. Using a simulated example, we show how these metrics can be presented graphically. This conceptually grounded framework can potentially aid the transparent design, analysis, and reporting of studies that examine joint exposures. We provide easy-to-use tools to implement it.

  11. Time-Varying Distortions of Binaural Information by Bilateral Hearing Aids

    PubMed Central

    Rodriguez, Francisco A.; Portnuff, Cory D. F.; Goupell, Matthew J.; Tollin, Daniel J.

    2016-01-01

    In patients with bilateral hearing loss, the use of two hearing aids (HAs) offers the potential to restore the benefits of binaural hearing, including sound source localization and segregation. However, existing evidence suggests that bilateral HA users’ access to binaural information, namely interaural time and level differences (ITDs and ILDs), can be compromised by device processing. Our objective was to characterize the nature and magnitude of binaural distortions caused by modern digital behind-the-ear HAs using a variety of stimuli and HA program settings. Of particular interest was a common frequency-lowering algorithm known as nonlinear frequency compression, which has not previously been assessed for its effects on binaural information. A binaural beamforming algorithm was also assessed. Wide dynamic range compression was enabled in all programs. HAs were placed on a binaural manikin, and stimuli were presented from an arc of loudspeakers inside an anechoic chamber. Stimuli were broadband noise bursts, 10-Hz sinusoidally amplitude-modulated noise bursts, or consonant–vowel–consonant speech tokens. Binaural information was analyzed in terms of ITDs, ILDs, and interaural coherence, both for whole stimuli and in a time-varying sense (i.e., within a running temporal window) across four different frequency bands (1, 2, 4, and 6 kHz). Key findings were: (a) Nonlinear frequency compression caused distortions of high-frequency envelope ITDs and significantly reduced interaural coherence. (b) For modulated stimuli, all programs caused time-varying distortion of ILDs. (c) HAs altered the relationship between ITDs and ILDs, introducing large ITD–ILD conflicts in some cases. Potential perceptual consequences of measured distortions are discussed. PMID:27698258

  12. Rate Control for Network-Coded Multipath Relaying with Time-Varying Connectivity

    DTIC Science & Technology

    2010-12-10

    currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE ( DD -MM-YYYY) 2. REPORT TYPE 3. DATES...Retransmission Interval 2.0 sec, and SPF Calculation Delay and Hold Time to 0 sec. For flooding, each of the N relay nodes is able to receive all

  13. Tools for Analysis and Visualization of Large Time-Varying CFD Data Sets

    NASA Technical Reports Server (NTRS)

    Wilhelms, Jane; VanGelder, Allen

    1997-01-01

    In the second year, we continued to built upon and improve our scanline-based direct volume renderer that we developed in the first year of this grant. This extremely general rendering approach can handle regular or irregular grids, including overlapping multiple grids, and polygon mesh surfaces. It runs in parallel on multi-processors. It can also be used in conjunction with a k-d tree hierarchy, where approximate models and error terms are stored in the nodes of the tree, and approximate fast renderings can be created. We have extended our software to handle time-varying data where the data changes but the grid does not. We are now working on extending it to handle more general time-varying data. We have also developed a new extension of our direct volume renderer that uses automatic decimation of the 3D grid, as opposed to an explicit hierarchy. We explored this alternative approach as being more appropriate for very large data sets, where the extra expense of a tree may be unacceptable. We also describe a new approach to direct volume rendering using hardware 3D textures and incorporates lighting effects. Volume rendering using hardware 3D textures is extremely fast, and machines capable of using this technique are becoming more moderately priced. While this technique, at present, is limited to use with regular grids, we are pursuing possible algorithms extending the approach to more general grid types. We have also begun to explore a new method for determining the accuracy of approximate models based on the light field method described at ACM SIGGRAPH '96. In our initial implementation, we automatically image the volume from 32 equi-distant positions on the surface of an enclosing tessellated sphere. We then calculate differences between these images under different conditions of volume approximation or decimation. We are studying whether this will give a quantitative measure of the effects of approximation. We have created new tools for exploring the

  14. Using Kalman Filtering to Predict Time-Varying Parameters in a Model Predicting Baroreflex Regulation During Head-Up Tilt.

    PubMed

    Matzuka, Brett; Mehlsen, Jesper; Tran, Hien; Olufsen, Mette Sofie

    2015-08-01

    The cardiovascular control system is continuously engaged to maintain homeostasis, but it is known to fail in a large cohort of patients suffering from orthostatic intolerance. Numerous clinical studies have been put forward to understand how the system fails, yet noninvasive clinical data are sparse, typical studies only include measurements of heart rate and blood pressure, as a result it is difficult to determine what mechanisms that are impaired. It is known, that blood pressure regulation is mediated by changes in heart rate, vascular resistance, cardiac contractility, and a number of other factors. Given that numerous factors contribute to changing these quantities, it is difficult to devise a physiological model describing how they change in time. One way is to build a model that allows these controlled quantities to change and to compare dynamics between subject groups. To do so, it requires more knowledge of how these quantities change for healthy subjects. This study compares two methods predicting time-varying changes in cardiac contractility and vascular resistance during head-up tilt. Similar to the study by Williams et al. [51], the first method uses piecewise linear splines, while the second uses the ensemble transform Kalman filter (ETKF) [1], [11], [12], [33]. In addition, we show that the delayed rejection adaptive Metropolis (DRAM) algorithm can be used for predicting parameter uncertainties within the spline methodology, which is compared with the variability obtained with the ETKF. While the spline method is easier to set up, this study shows that the ETKF has a significantly shorter computational time. Moreover, while uncertainty of predictions can be augmented to spline predictions using DRAM, these are readily available with the ETKF.

  15. Investigation of the Acoustics of Plucked String Tones Based on the Analysis of Their Time-Varying Spectra.

    NASA Astrophysics Data System (ADS)

    Chen, Kwok-Ping John

    This research investigates two aspects of the time-varying vibration patterns of plucked string tones of classical guitar, Chinese pipa and Chinese ch'in. First, the assumption that horizontal and vertical frequencies and decay rates may be different is used as a basis for classifying the partial amplitude envelopes into four types. It is found that the partial envelopes of the tones produced by the three instruments, using the finger tip excitation method, on a single undamped string, can be described in terms of these four types. The results show that ch'in tones contain Type III, and IV, guitar tones contain Type I, II and III, and pipa tones contain all four types with a higher percentage of Type III and IV. Second, the theories of "missing modes" (Young, 1800), (Benade, 1976) and delayed generation of these modes (Fletcher, 1984), (Hall, 1987) are re-examined experimentally. The edge of a conventional guitar pick is used to excite a single undamped string on a classical guitar at nodal position N which is L/N from the bridge. As a result, it is a consistent feature that any mode whose index n is a multiple of N is attenuated during the attack phase but subsequently rises with a more gradual attack to reach a significant peak amplitude, except for the first multiple of locations L/3 to L/7. This amplitude envelope pattern, Type V, which is only applicable when the pick-edge excitation method is used, is distinct from the other four types mentioned above.

  16. Estimating time-varying nonlinear autoregressive model parameters by minimizing hypersurface distance.

    PubMed

    Yang, Bufan; Chon, Ki H

    2010-08-01

    A nonleast-squares (non-LS) based method is presented for modeling time-varying (TV) nonlinear systems. The proposed method combines basis function technique and minimization of hypersurface distance (MHD) to combat TV and nonlinear dynamics, respectively. The performance of TVMHD is compared to the LS and total LS methods using simulation examples as well as human heart rate data recorded during different body positions. With all data, TVMHD significantly outperforms the two other methods by a factor of one order of magnitude; the LS-based methods require double the number of parameters than TVMHD requires to obtain similar residual error values. The significance of TVMHD is that due to its accurate parameter estimates concomitant with a fewer number of parameters, we now have the possibility of pinpointing parameters that may be of physiological importance, where such application will be especially useful in discriminating diseased conditions. Furthermore, our algorithm allows discrimination of model terms, which are TV or time invariant, by examining those basis function coefficients that are designed to capture TV dynamics. However, it should be noted that the main disadvantage of TVMHD is that it requires significantly greater computational time than the LS-based methods.

  17. Control of the tokamak safety factor profile with time-varying constraints using MPC

    NASA Astrophysics Data System (ADS)

    Maljaars, E.; Felici, F.; de Baar, M. R.; van Dongen, J.; Hogeweij, G. M. D.; Geelen, P. J. M.; Steinbuch, M.

    2015-02-01

    A controller is designed for the tokamak safety factor profile that takes real-time-varying operational and physics limits into account. This so-called model predictive controller (MPC) employs a prediction model in order to compute optimal control inputs that satisfy the given limits. The use of linearized models around a reference trajectory results in a quadratic programming problem that can easily be solved online. The performance of the controller is analysed in a set of ITER L-mode scenarios simulated with the non-linear plasma transport code RAPTOR. It is shown that the controller can reduce the tracking error due to an overestimation or underestimation of the modelled transport, while making a trade-off between residual error and amount of controller action. It is also shown that the controller can account for a sudden decrease in the available actuator power, while providing warnings ahead of time about expected violations of operational and physics limits. This controller can be extended and implemented in existing tokamaks in the near future.

  18. An electric model with time varying resistance for a pneumatic membrane blood pump.

    PubMed

    Jin, Z; Qin, J

    1993-01-01

    To investigate the effects of an artificial heart and cardiac assist device on the cardiovascular system and determine the proper control method, an electrical model is an effective tool. An electric model with time varying resistance is proposed to represent a pneumatic membrane blood pump, by which the resistance of the valves in the pump is a function of time. The model is consistent over the whole cardiac cycle, and the important transitional processes between systole and diastole are considered. The calculated results based on this model are compared with the experimentally measured waveforms of the corresponding state-variables of a loaded pump, and the model parameters estimated using the least-squares criterion are compared with the measured physical values of corresponding functional parts. Results showed that this electric model is capable of representing a pneumatic membrane pump with quite satisfactory accuracy. They also showed that the transitional property of the valve resistance has a significant influence on the output characteristics of the pump.

  19. [Effect of vibration caused by time-varying magnetic fields on diffusion-weighted MRI].

    PubMed

    Ogura, Akio; Maeda, Fumie; Miyai, Akira; Hayashi, Kohji; Hongoh, Takaharu

    2006-04-20

    Diffusion-weighted images (DWIs) with high b-factor in the body are often used to detect and diagnose cancer at MRI. The echo planar imaging (EPI) sequence and high motion probing gradient pulse are used at diffusion weighted imaging, causing high table vibration. The purpose of this study was to assess whether the diffusion signal and apparent diffusion coefficient (ADC) values are influenced by this vibration because of time-varying magnetic fields. Two DWIs were compared. In one, phantoms were fixed on the MRI unit's table transmitting the vibration. In the other, phantoms were supported in air, in the absence of vibration. The phantoms called "solution phantoms" were made from agarose of a particular density. The phantoms called "jelly phantoms" were made from agarose that was heated. The diffusion signal and ADC value of each image were compared. The results showed that the signal of DWI units using the solution phantom was not affected by vibration. However, the signal of DWI and ADC were increased in the low-density jelly phantom as a result of vibration, causing the jelly phantom to vibrate. The DWIs of vibrating regions such as the breast maybe be subject to error. A countermeasure seems to be to support the region adequately.

  20. Modeling Intensive Longitudinal Data With Mixtures of Nonparametric Trajectories and Time-Varying Effects

    PubMed Central

    Dziak, John J.; Li, Runze; Tan, Xianming; Shiffman, Saul; Shiyko, Mariya P.

    2015-01-01

    Behavioral scientists increasingly collect intensive longitudinal data (ILD), in which phenomena are measured at high frequency and in real time. In many such studies, it is of interest to describe the pattern of change over time in important variables as well as the changing nature of the relationship between variables. Individuals' trajectories on variables of interest may be far from linear, and the predictive relationship between variables of interest and related covariates may also change over time in a nonlinear way. Time-varying effect models (TVEMs; see Tan, Shiyko, Li, Li, & Dierker, 2012) address these needs by allowing regression coefficients to be smooth, nonlinear functions of time rather than constants. However, it is possible that not only observed covariates but also unknown, latent variables may be related to the outcome. That is, regression coefficients may change over time and also vary for different kinds of individuals. Therefore, we describe a finite mixture version of TVEM for situations in which the population is heterogeneous and in which a single trajectory would conceal important, inter-individual differences. This extended approach, MixTVEM, combines finite mixture modeling with non- or semi-parametric regression modeling, in order to describe a complex pattern of change over time for distinct latent classes of individuals. The usefulness of the method is demonstrated in an empirical example from a smoking cessation study. We provide a versatile SAS macro and R function for fitting MixTVEMs. PMID:26390169

  1. Coded throughput performance simulations for the time-varying satellite channel. M.S. Thesis

    NASA Technical Reports Server (NTRS)

    Han, LI

    1995-01-01

    The design of a reliable satellite communication link involving the data transfer from a small, low-orbit satellite to a ground station, but through a geostationary satellite, was examined. In such a scenario, the received signal power to noise density ratio increases as the transmitting low-orbit satellite comes into view, and then decreases as it then departs, resulting in a short-duration, time-varying communication link. The optimal values of the small satellite antenna beamwidth, signaling rate, modulation scheme and the theoretical link throughput (in bits per day) have been determined. The goal of this thesis is to choose a practical coding scheme which maximizes the daily link throughput while satisfying a prescribed probability of error requirement. We examine the throughput of both fixed rate and variable rate concatenated forward error correction (FEC) coding schemes for the additive white Gaussian noise (AWGN) channel, and then examine the effect of radio frequency interference (RFI) on the best coding scheme among them. Interleaving is used to mitigate degradation due to RFI. It was found that the variable rate concatenated coding scheme could achieve 74 percent of the theoretical throughput, equivalent to 1.11 Gbits/day based on the cutoff rate R(sub 0). For comparison, 87 percent is achievable for AWGN-only case.

  2. AST: Activity-Security-Trust driven modeling of time varying networks

    PubMed Central

    Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen

    2016-01-01

    Network modeling is a flexible mathematical structure that enables to identify statistical regularities and structural principles hidden in complex systems. The majority of recent driving forces in modeling complex networks are originated from activity, in which an activity potential of a time invariant function is introduced to identify agents’ interactions and to construct an activity-driven model. However, the new-emerging network evolutions are already deeply coupled with not only the explicit factors (e.g. activity) but also the implicit considerations (e.g. security and trust), so more intrinsic driving forces behind should be integrated into the modeling of time varying networks. The agents undoubtedly seek to build a time-dependent trade-off among activity, security, and trust in generating a new connection to another. Thus, we reasonably propose the Activity-Security-Trust (AST) driven model through synthetically considering the explicit and implicit driving forces (e.g. activity, security, and trust) underlying the decision process. AST-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the effects of security and trust in driving network evolution, and improving the biases induced by only involving activity representations in analyzing the dynamical processes. PMID:26888717

  3. Mass Redistribution in the Core and Time-varying Gravity at the Earth's Surface

    NASA Technical Reports Server (NTRS)

    Kuang, Wei-Jia; Chao, Benjamin F.; Fang, Ming

    2003-01-01

    The Earth's liquid outer core is in convection, as suggested by the existence of the geomagnetic field in much of the Earth's history. One consequence of the convection is the redistribution of mass resulting from relative motion among fluid parcels with slightly different densities. This time dependent mass redistribution inside the core produces a small perturbation on the gravity field of the Earth. With our numerical dynamo solutions, we find that the mass redistribution (and the resultant gravity field) symmetric about the equator is much stronger than that anti-symmetric about the equator. In particular, J(sub 2) component is the strongest. In addition, the gravity field variation increases with the Rayleigh number that measures the driving force for the geodynamo in the core. With reasonable scaling from the current dynamo solutions, we could expect that at the surface of the Earth, the J(sub 2) variation from the core is on the order of l0(exp -16)/year relative to the mean (i.e. spherically symmetric) gravity field of the Earth. The possible shielding effect due to core-mantle boundary pressure variation loading is likely much smaller and is therefore negligible. Our results suggest that time-varying gravity field perturbation due to core mass redistribution may be measured with modem space geodetic observations, which will result a new means of detecting dynamical processes in the Earth's deep interior.

  4. Numerical Studies on Time-Varying Stiffness of Disk-Drum Type Rotor with Bolt Loosening

    NASA Astrophysics Data System (ADS)

    Qin, Zhaoye; Chu, Fulei

    2015-07-01

    Disk-drum type rotors are widely used in industry for their high stiffness and low weight properties. In disk-drum type rotors, the adjacent disks and drums are commonly connected by bolted joints. Those rotating joint interfaces are subjected to numerous combinations of loads during normal operation, where loosening of the connecting bolts might occur. The bolt loosening will change the local stiffness of the rotor, which in turn affect the rotor dynamics and even result in structural failures. In this paper, the local stiffness of a disk- drum rotor with bolt loosening is investigated numerically. A three-dimensional (3D) finite element (FE) model for the bolted disk-drum joint is established in ANSYS, where the bolt loosening is simulated by reducing the preloads of certain bolts, and removing those bolts as the limiting case. Simulations are performed on the FE model to evaluate the joint behaviour under static loads. Periodic variations of the joint deflections with respect to the rotation angle of the shaft are obtained, which implies the appearance of the time-varying local stiffness in the rotor system. The studies in this paper help accurate prediction of the rotor dynamics and early detection of bolt loosening.

  5. Mapping transverse capillary flow speed using time-varying OCT speckle signals (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Choi, Woo June; Wang, Ruikang K.

    2016-03-01

    We present an optical coherence tomography (OCT) based method for mapping transverse red blood cell (RBC) flow speed at capillary. This OCT velocimetry utilizes a quantitative laser speckle temporal contrast analysis that estimates reliable speckle decorrelation time from the observed speckle contrast, which is related to microcirculatory flow velocity. For capillary speed measurement, we employ a home-built 1.3 µm MHz swept-source OCT (SS-OCT) system that can acquire OCT B-frames at a rate of 1.7 kHz. From the multiple B-frames obtained at the same location, intensity profiles with time-varying OCT speckle contrast are extracted at single capillaries using a capillary binary mask and then the transverse flow speed is calculated by adapting the profiles to the speckle contrast analytic model. Finally, a 3D speed map can be achieved for OCT volume imaging. To validate this method, we perform a systematic study using both phantom and in vivo rodent models. Result shows that our method is effective to measure transverse capillary flow speed.

  6. Towards damage detection using blind source separation integrated with time-varying auto-regressive modeling

    NASA Astrophysics Data System (ADS)

    Musafere, F.; Sadhu, A.; Liu, K.

    2016-01-01

    In the last few decades, structural health monitoring (SHM) has been an indispensable subject in the field of vibration engineering. With the aid of modern sensing technology, SHM has garnered significant attention towards diagnosis and risk management of large-scale civil structures and mechanical systems. In SHM, system identification is one of major building blocks through which unknown system parameters are extracted from vibration data of the structures. Such system information is then utilized to detect the damage instant, and its severity to rehabilitate and prolong the existing health of the structures. In recent years, blind source separation (BSS) algorithm has become one of the newly emerging advanced signal processing techniques for output-only system identification of civil structures. In this paper, a novel damage detection technique is proposed by integrating BSS with the time-varying auto-regressive modeling to identify the instant and severity of damage. The proposed method is validated using a suite of numerical studies and experimental models followed by a full-scale structure.

  7. Central suboptimal H ∞ controller design for linear time-varying systems with unknown parameters

    NASA Astrophysics Data System (ADS)

    Basin, Michael V.; Soto, Pedro; Calderon-Alvarez, Dario

    2011-05-01

    This article presents the central finite-dimensional H ∞ controller for linear time-varying systems with unknown parameters, that is suboptimal for a given threshold γ with respect to a modified Bolza-Meyer quadratic criterion including the attenuation control term with the opposite sign. In contrast to the previously obtained results, this article reduces the original H ∞ controller problem to the corresponding H 2 controller problem, using the technique proposed in Doyle et al. [Doyle, J.C., Glover, K., Khargonekar, P.P., and Francis, B.A. (1989), 'State-space Solutions to Standard H 2 and H Infinity Control Problems', IEEE Transactions Automatic Control, 34, 831-847]. This article yields the central suboptimal H ∞ controller for linear systems with unknown parameters in a closed finite-dimensional form, based on the corresponding H 2 controller obtained in Basin and Calderon-Alvarez [Basin, M.V., and Calderon-Alvarez, D. (2008), 'Optimal LQG Controller for Linear Systems with Unknown Parameters', Journal of The Franklin Institute, 345, 293-302]. Numerical simulations are conducted to verify performance of the designed central suboptimal controller for uncertain linear systems with unknown parameters against the conventional central suboptimal H ∞ controller for linear systems with exactly known parameter values.

  8. AST: Activity-Security-Trust driven modeling of time varying networks.

    PubMed

    Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen

    2016-02-18

    Network modeling is a flexible mathematical structure that enables to identify statistical regularities and structural principles hidden in complex systems. The majority of recent driving forces in modeling complex networks are originated from activity, in which an activity potential of a time invariant function is introduced to identify agents' interactions and to construct an activity-driven model. However, the new-emerging network evolutions are already deeply coupled with not only the explicit factors (e.g. activity) but also the implicit considerations (e.g. security and trust), so more intrinsic driving forces behind should be integrated into the modeling of time varying networks. The agents undoubtedly seek to build a time-dependent trade-off among activity, security, and trust in generating a new connection to another. Thus, we reasonably propose the Activity-Security-Trust (AST) driven model through synthetically considering the explicit and implicit driving forces (e.g. activity, security, and trust) underlying the decision process. AST-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the effects of security and trust in driving network evolution, and improving the biases induced by only involving activity representations in analyzing the dynamical processes.

  9. Developing and Evaluating Time-Varying Probability Forecasts over an Extended Region

    NASA Astrophysics Data System (ADS)

    Vere-Jones, D.; Harte, D.

    2001-12-01

    We present a methodology that may be useful in estimating and evaluating time-varying forecast probabilities based on an observed predictive signal, when both predictive signal and forecast events are taken from extended spatial regions. This methodology has evolved from our attempts to convert the M8 series to a form which can be used as the basis of 6-monthly forecasts for events in the M 6.5-7 range. The main issues which had to be resolved were: (i) how to subdivide the spatial region into forecasting subregions; (ii) how to quantify the predictive signal within a specified forecasting subregion and convert it into a probability; (iii) how to evaluate the performance of the forecasts, bearing in mind the overlap among the forecasting subregions. A brief account will be given of the problems arising in each of these steps, and of the aproaches taken to deal with them in the case of the M8 series. In fact the results indicate the presence not only of significant predictive information within the M8 series, but also of unexpected links between the deep and shallow events.

  10. Reusable Launch Vehicle Attitude Control Using a Time-Varying Sliding Mode Control Technique

    NASA Technical Reports Server (NTRS)

    Shtessel, Yuri B.; Zhu, J. Jim; Daniels, Dan; Jackson, Scott (Technical Monitor)

    2002-01-01

    In this paper we present a time-varying sliding mode control (TVSMC) technique for reusable launch vehicle (RLV) attitude control in ascent and entry flight phases. In ascent flight the guidance commands Euler roll, pitch and yaw angles, and in entry flight it commands the aerodynamic angles of bank, attack and sideslip. The controller employs a body rate inner loop and the attitude outer loop, which are separated in time-scale by the singular perturbation principle. The novelty of the TVSMC is that both the sliding surface and the boundary layer dynamics can be varied in real time using the PD-eigenvalue assignment technique. This salient feature is used to cope with control command saturation and integrator windup in the presence of severe disturbance or control effector failure, which enhances the robustness and fault tolerance of the controller. The TV-SMC ascent and descent designs are currently being tested with high fidelity, 6-DOF dispersion simulations. The test results will be presented in the final version of this paper.

  11. Time Varying Compensator Design for Reconfigurable Structures Using Non-Collocated Feedback

    NASA Technical Reports Server (NTRS)

    Scott, Michael A.

    1996-01-01

    Analysis and synthesis tools are developed to improved the dynamic performance of reconfigurable nonminimum phase, nonstrictly positive real-time variant systems. A novel Spline Varying Optimal (SVO) controller is developed for the kinematic nonlinear system. There are several advantages to using the SVO controller, in which the spline function approximates the system model, observer, and controller gain. They are: The spline function approximation is simply connected, thus the SVO controller is more continuous than traditional gain scheduled controllers when implemented on a time varying plant; ft is easier for real-time implementations in storage and computational effort; where system identification is required, the spline function requires fewer experiments, namely four experiments; and initial startup estimator transients are eliminated. The SVO compensator was evaluated on a high fidelity simulation of the Shuttle Remote Manipulator System. The SVO controller demonstrated significant improvement over the present arm performance: (1) Damping level was improved by a factor of 3; and (2) Peak joint torque was reduced by a factor of 2 following Shuttle thruster firings.

  12. Exploring vibration control strategies for a footbridge with time-varying modal parameters

    NASA Astrophysics Data System (ADS)

    Soria, Jose M.; Díaz, Ivan M.; Pereira, Emiliano; García-Palacios, Jaime H.; Wang, Xidong

    2016-09-01

    This paper explores different vibration control strategies for the cancellation of human-induced vibration of a structure with time-varying modal parameters. The motivation of this study is an urban stress-ribbon footbridge (Pedro Gomez Bosque, Valladolid, Spain) that, after a whole-year monitoring, it has been obtained that the natural frequency of a vibration mode at approximately 1.8 Hz (within the normal range of walking) changes up to 20%, mainly due to temperature variations. Thus, this paper takes the annual modal parameter estimates (aprox. 14000 estimations) of this mode and designs three control strategies: a) a tuned mass damper (TMD) tuned to the aforementioned mode using its most-repeated modal properties, b) a semi-active TMD with an on-off control law for the TMD damping, and c) an active mass damper designed using the well-known velocity feedback control strategy with a saturation nonlinearity. Illustrative results have been reported from this preliminary study.

  13. Generalized Framework and Algorithms for Illustrative Visualization of Time-Varying Data on Unstructured Meshes

    SciTech Connect

    Alexander S. Rattner; Donna Post Guillen; Alark Joshi

    2012-12-01

    Photo- and physically-realistic techniques are often insufficient for visualization of simulation results, especially for 3D and time-varying datasets. Substantial research efforts have been dedicated to the development of non-photorealistic and illustration-inspired visualization techniques for compact and intuitive presentation of such complex datasets. While these efforts have yielded valuable visualization results, a great deal of work has been reproduced in studies as individual research groups often develop purpose-built platforms. Additionally, interoperability between illustrative visualization software is limited due to specialized processing and rendering architectures employed in different studies. In this investigation, a generalized framework for illustrative visualization is proposed, and implemented in marmotViz, a ParaView plugin, enabling its use on variety of computing platforms with various data file formats and mesh geometries. Detailed descriptions of the region-of-interest identification and feature-tracking algorithms incorporated into this tool are provided. Additionally, implementations of multiple illustrative effect algorithms are presented to demonstrate the use and flexibility of this framework. By providing a framework and useful underlying functionality, the marmotViz tool can act as a springboard for future research in the field of illustrative visualization.

  14. AST: Activity-Security-Trust driven modeling of time varying networks

    NASA Astrophysics Data System (ADS)

    Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen

    2016-02-01

    Network modeling is a flexible mathematical structure that enables to identify statistical regularities and structural principles hidden in complex systems. The majority of recent driving forces in modeling complex networks are originated from activity, in which an activity potential of a time invariant function is introduced to identify agents’ interactions and to construct an activity-driven model. However, the new-emerging network evolutions are already deeply coupled with not only the explicit factors (e.g. activity) but also the implicit considerations (e.g. security and trust), so more intrinsic driving forces behind should be integrated into the modeling of time varying networks. The agents undoubtedly seek to build a time-dependent trade-off among activity, security, and trust in generating a new connection to another. Thus, we reasonably propose the Activity-Security-Trust (AST) driven model through synthetically considering the explicit and implicit driving forces (e.g. activity, security, and trust) underlying the decision process. AST-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the effects of security and trust in driving network evolution, and improving the biases induced by only involving activity representations in analyzing the dynamical processes.

  15. Controlling the interactions between cold Rydberg atoms by a time-varying electric field

    NASA Astrophysics Data System (ADS)

    Ryabtsev, I. I.; Tretyakov, D. B.; Entin, V. M.; Beterov, I. I.; Yakshina, E. A.; Andreeva, C.

    2017-01-01

    Long-range interactions between cold Rydberg atoms are being investigated for neutral-atom quantum computing, quantum simulations, phase transitions in cold Rydberg gases and other applications. Fine tuning of the interaction strength can be implemented using Förster resonances between Rydberg atoms controlled by an electric field. The observation of the Stark-tuned Förster resonances between Rydberg atoms excited by narrowband cw laser radiation requires usage of a Stark-switching technique in order to excite the atoms first in a fixed electric field and then to induce the interactions in a varied electric field, which is scanned across the Förster resonance. The application of the radio-frequency field causes additional Förster resonances between collective states, whose line shape depends on the interaction strengths and time. Spatial averaging over the atom positions in a single interaction volume yields a cusped line shape of the Förster resonance. We present a detailed experimental and theoretical analysis of the line shape and time dynamics of the Stark-tuned Förster resonances Rb(nP 3/2) + Rb(nP 3/2) → Rb(nS 1/2) + Rb([n + 1]S 1/2) for two Rb Rydberg atoms interacting in a time-varying electric field.

  16. Detection of random alterations to time-varying musical instrument spectra

    NASA Astrophysics Data System (ADS)

    Horner, Andrew; Beauchamp, James; So, Richard

    2004-09-01

    The time-varying spectra of eight musical instrument sounds were randomly altered by a time-invariant process to determine how detection of spectral alteration varies with degree of alteration, instrument, musical experience, and spectral variation. Sounds were resynthesized with centroids equalized to the original sounds, with frequencies harmonically flattened, and with average spectral error levels of 8%, 16%, 24%, 32%, and 48%. Listeners were asked to discriminate the randomly altered sounds from reference sounds resynthesized from the original data. For all eight instruments, discrimination was very good for the 32% and 48% error levels, moderate for the 16% and 24% error levels, and poor for the 8% error levels. When the error levels were 16%, 24%, and 32%, the scores of musically experienced listeners were found to be significantly better than the scores of listeners with no musical experience. Also, in this same error level range, discrimination was significantly affected by the instrument tested. For error levels of 16% and 24%, discrimination scores were significantly, but negatively correlated with measures of spectral incoherence and normalized centroid deviation on unaltered instrument spectra, suggesting that the presence of dynamic spectral variations tends to increase the difficulty of detecting spectral alterations. Correlation between discrimination and a measure of spectral irregularity was comparatively low.

  17. Time-varying span efficiency through the wingbeat of desert locusts

    PubMed Central

    Henningsson, Per; Bomphrey, Richard J.

    2012-01-01

    The flight performance of animals depends greatly on the efficacy with which they generate aerodynamic forces. Accordingly, maximum range, load-lifting capacity and peak accelerations during manoeuvres are all constrained by the efficiency of momentum transfer to the wake. Here, we use high-speed particle image velocimetry (1 kHz) to record flow velocities in the near wake of desert locusts (Schistocerca gregaria, Forskål). We use the measured flow fields to calculate time-varying span efficiency throughout the wing stroke cycle. The locusts are found to operate at a maximum span efficiency of 79 per cent, typically at a plateau of about 60 per cent for the majority of the downstroke, but at lower values during the upstroke. Moreover, the calculated span efficiencies are highest when the largest lift forces are being generated (90% of the total lift is generated during the plateau of span efficiency) suggesting that the combination of wing kinematics and morphology in locust flight perform most efficiently when doing the most work. PMID:22112649

  18. Framework and algorithms for illustrative visualizations of time-varying flows on unstructured meshes

    DOE PAGES

    Rattner, Alexander S.; Guillen, Donna Post; Joshi, Alark; ...

    2016-03-17

    Photo- and physically realistic techniques are often insufficient for visualization of fluid flow simulations, especially for 3D and time-varying studies. Substantial research effort has been dedicated to the development of non-photorealistic and illustration-inspired visualization techniques for compact and intuitive presentation of such complex datasets. However, a great deal of work has been reproduced in this field, as many research groups have developed specialized visualization software. Additionally, interoperability between illustrative visualization software is limited due to diverse processing and rendering architectures employed in different studies. In this investigation, a framework for illustrative visualization is proposed, and implemented in MarmotViz, a ParaViewmore » plug-in, enabling its use on a variety of computing platforms with various data file formats and mesh geometries. Region-of-interest identification and feature-tracking algorithms incorporated into this tool are described. Implementations of multiple illustrative effect algorithms are also presented to demonstrate the use and flexibility of this framework. Here, by providing an integrated framework for illustrative visualization of CFD data, MarmotViz can serve as a valuable asset for the interpretation of simulations of ever-growing scale.« less

  19. Framework and algorithms for illustrative visualizations of time-varying flows on unstructured meshes

    SciTech Connect

    Rattner, Alexander S.; Guillen, Donna Post; Joshi, Alark; Garimella, Srinivas

    2016-03-17

    Photo- and physically realistic techniques are often insufficient for visualization of fluid flow simulations, especially for 3D and time-varying studies. Substantial research effort has been dedicated to the development of non-photorealistic and illustration-inspired visualization techniques for compact and intuitive presentation of such complex datasets. However, a great deal of work has been reproduced in this field, as many research groups have developed specialized visualization software. Additionally, interoperability between illustrative visualization software is limited due to diverse processing and rendering architectures employed in different studies. In this investigation, a framework for illustrative visualization is proposed, and implemented in MarmotViz, a ParaView plug-in, enabling its use on a variety of computing platforms with various data file formats and mesh geometries. Region-of-interest identification and feature-tracking algorithms incorporated into this tool are described. Implementations of multiple illustrative effect algorithms are also presented to demonstrate the use and flexibility of this framework. Here, by providing an integrated framework for illustrative visualization of CFD data, MarmotViz can serve as a valuable asset for the interpretation of simulations of ever-growing scale.

  20. Time-varying Risk Factors and Sexual Aggression Perpetration among Male College Students

    PubMed Central

    Thompson, Martie P.; Kingree, J.B. (Kip); Zinzow, Heidi; Swartout, Kevin

    2015-01-01

    Purpose Preventing sexual aggression can be informed by determining if time-varying risk factors differentiate men who follow different sexual aggression risk trajectories. Methods Data are from a longitudinal study with 795 college males surveyed at the end of each of their four years of college in 2008–2011. Repeated measures general linear models tested if changes in risk factors corresponded with sexual aggression trajectory membership. Results Changes in the risk factors corresponded with SA trajectories. Men who came to college with a history of SA but decreased their perpetration likelihood during college showed concurrent decreases in sexual compulsivity, impulsivity, hostile attitudes toward women, rape supportive beliefs, perceptions of peer approval of forced sex, and perceptions of peer pressure to have sex with many different women, and smaller increases in pornography use over their college years. Conversely, men who increased levels of SA over time demonstrated larger increases in risk factors in comparison to other trajectory groups. Conclusions The odds that males engaged in sexual aggression corresponded with changes in key risk factors. Risk factors were not static and interventions designed to alter them may lead to changes in sexual aggression risk. PMID:26592333

  1. SLR Station Recovery, Center of Frame Motion, and Time Varying Gravity

    NASA Technical Reports Server (NTRS)

    Zelensky, Nikita P.; Lemoine, Frank G.; Chinn, Douglas S.; Melachroinos, Stavros; Wiser Beall, Jennifer; Larson, Jordan D.

    2012-01-01

    Weekly station position estimates, beginning with 1993, are derived from the ITRF2008-based SLR processing of up to four satellites: Lageos 1, Lageos2, Starlette, and Stella. Helmert parameters obtained from c omparison of weekly SLR station positions and the a-priori SLRF2008 station complement are evaluated for geocenter motion and scale. Two me thods for modeling time varying gravity are employed in the SLR satel lite POD processing, with GGM03S serving as the static gravity field. Both methods forward model atmosphere gravity derived from 6-hour ECM WF pressure data. The standard approach applies an annual 20x20 field estimated from 4 years of GRACE data, and the IERS2003 recommended linear rates for C20, C30, C40, C21, and S21. The alternate approach us es a new set of low-order/degree 4x4 coefficients estimated weekly fr om SLR & DORIS processing to 10 satellites from 1993-2012. This exper imental tvg4x4 model has been shown to improve the TOPEX, Jason-1, and Jason-2 altimeter satellite orbits,. In this paper we apply the more detailed time-variable gravity modeling to the SLR satellite POD pro cessing and subsequent reference frame analyses. For this study we will evaluate the orbit differences (periodic and secular) for the satel lites concerned, characterize the impact on the station coordinate solutions, and the impact on reference frame parameters (geocenter and s cale).

  2. Long-term prediction of the Arctic ionospheric TEC based on time-varying periodograms.

    PubMed

    Liu, Jingbin; Chen, Ruizhi; Wang, Zemin; An, Jiachun; Hyyppä, Juha

    2014-01-01

    Knowledge of the polar ionospheric total electron content (TEC) and its future variations is of scientific and engineering relevance. In this study, a new method is developed to predict Arctic mean TEC on the scale of a solar cycle using previous data covering 14 years. The Arctic TEC is derived from global positioning system measurements using the spherical cap harmonic analysis mapping method. The study indicates that the variability of the Arctic TEC results in highly time-varying periodograms, which are utilized for prediction in the proposed method. The TEC time series is divided into two components of periodic oscillations and the average TEC. The newly developed method of TEC prediction is based on an extrapolation method that requires no input of physical observations of the time interval of prediction, and it is performed in both temporally backward and forward directions by summing the extrapolation of the two components. The backward prediction indicates that the Arctic TEC variability includes a 9 years period for the study duration, in addition to the well-established periods. The long-term prediction has an uncertainty of 4.8-5.6 TECU for different period sets.

  3. Does dormancy increase fitness of bacterial populations in time-varying environments?

    PubMed

    Malik, Tufail; Smith, Hal L

    2008-05-01

    A simple family of models of a bacterial population in a time varying environment in which cells can transit between dormant and active states is constructed. It consists of a linear system of ordinary differential equations for active and dormant cells with time-dependent coefficients reflecting an environment which may be periodic or random, with alternate periods of low and high resource levels. The focus is on computing/estimating the dominant Lyapunov exponent, the fitness, and determining its dependence on various parameters and the two strategies-responsive and stochastic-by which organisms switch between dormant and active states. A responsive switcher responds to good and bad times by making timely and appropriate transitions while a stochastic switcher switches continuously without regard to the environmental state. The fitness of a responsive switcher is examined and compared with fitness of a stochastic switcher, and with the fitness of a dormancy-incapable organism. Analytical methods show that both switching strategists have higher fitness than a dormancy-incapable organism when good times are rare and that responsive switcher has higher fitness than stochastic switcher when good times are either rare or common. Numerical calculations show that stochastic switcher can be most fit when good times are neither too rare or too common.

  4. Lp-stability (1 less than or equal to p less than or equal to infinity) of multivariable nonlinear time-varying feedback systems that are open-loop unstable. [noting unstable convolution subsystem forward control and time varying nonlinear feedback

    NASA Technical Reports Server (NTRS)

    Callier, F. M.; Desoer, C. A.

    1973-01-01

    A class of multivariable, nonlinear time-varying feedback systems with an unstable convolution subsystem as feedforward and a time-varying nonlinear gain as feedback was considered. The impulse response of the convolution subsystem is the sum of a finite number of increasing exponentials multiplied by nonnegative powers of the time t, a term that is absolutely integrable and an infinite series of delayed impulses. The main result is a theorem. It essentially states that if the unstable convolution subsystem can be stabilized by a constant feedback gain F and if incremental gain of the difference between the nonlinear gain function and F is sufficiently small, then the nonlinear system is L(p)-stable for any p between one and infinity. Furthermore, the solutions of the nonlinear system depend continuously on the inputs in any L(p)-norm. The fixed point theorem is crucial in deriving the above theorem.

  5. Controller design for delay systems via eigenvalue assignment - on a new result in the distribution of quasi-polynomial roots

    NASA Astrophysics Data System (ADS)

    Wang, Honghai; Liu, Jianchang; Yang, Feisheng; Zhang, Yu

    2015-12-01

    This paper considers the eigenvalue distribution of a linear time-invariant (LTI) system with time delays and its application to some controllers design for a delay plant via eigenvalue assignment. First, a new result on the root distribution for a class of quasi-polynomials is developed based on the extension of the Hermite-Biehler theorem. Then, such result is applied to proportional-integral (PI) controller parameter design for a first-order plant with time delay through pole placement. The complete region of PI gains can be obtained so that the rightmost eigenvalues in the infinite eigenspectrum of the closed-loop system with delay plant are assigned to desired positions in the complex plane. Furthermore, on the basis of the previous result, this paper also extended the PI control to the proportional-integral-derivative (PID) control. It is worth pointing out that this work aims to improve the performance of the closed-loop system on the premise of guaranteeing the stability.

  6. An improved stability test and stabilisation of linear time-varying systems governed by second-order vector differential equations

    NASA Astrophysics Data System (ADS)

    Tung, Shen-Lung; Juang, Yau-Tarng; Wu, Wei-Ying; Shieh, Wern-Yarng

    2011-12-01

    In this article, the problems of exponential stability analysis and stabilisation of linear time-varying systems described by a class of second-order vector differential equations are considered. Using bounding techniques on the trajectories of a linear time-varying system, the stability problem of the time-varying system is transformed to that of a time-invariant system and a new sufficient condition for the exponential stability is obtained. Moreover, the new criterion is proven to be superior to a test presented in the recent literature. Finally, the proposed criterion is applied to the exponential stabilisation problem via state feedback. The results are illustrated by several numerical examples.

  7. Time-Varying Upper-Plate Deformation during the Megathrust Subduction Earthquake Cycle

    NASA Astrophysics Data System (ADS)

    Furlong, Kevin P.; Govers, Rob; Herman, Matthew

    2015-04-01

    Over the past several decades of the WEGENER era, our abilities to observe and image the deformational behavior of the upper plate in megathrust subduction zones has dramatically improved. Several intriguing inferences can be made from these observations including apparent lateral variations in locking along subduction zones, which differs from interseismic to coseismic periods; the significant magnitude of post-earthquake deformation (e.g. following the 20U14 Mw Iquique, Chile earthquake, observed on-land GPS post-EQ displacements are comparable to the co-seismic displacements); and incompatibilities between rates of slip deficit accumulation and resulting earthquake co-seismic slip (e.g. pre-Tohoku, inferred rates of slip deficit accumulation on the megathrust significantly exceed slip amounts for the ~ 1000 year recurrence.) Modeling capabilities have grown from fitting simple elastic accumulation/rebound curves to sparse data to having spatially dense continuous time series that allow us to infer details of plate boundary coupling, rheology-driven transient deformation, and partitioning among inter-earthquake and co-seismic displacements. In this research we utilize a 2D numerical modeling to explore the time-varying deformational behavior of subduction zones during the earthquake cycle with an emphasis on upper-plate and plate interface behavior. We have used a simplified model configuration to isolate fundamental processes associated with the earthquake cycle, rather than attempting to fit details of specific megathrust zones. Using a simple subduction geometry, but realistic rheologic layering we are evaluating the time-varying displacement and stress response through a multi-earthquake cycle history. We use a simple model configuration - an elastic subducting slab, an elastic upper plate (shallower than 40 km), and a visco-elastic upper plate (deeper than 40 km). This configuration leads to an upper plate that acts as a deforming elastic beam at inter

  8. The stability analysis of a general viral infection model with distributed delays and multi-staged infected progression

    NASA Astrophysics Data System (ADS)

    Wang, Jinliang; Liu, Shengqiang

    2015-01-01

    We investigate an in-host model with general incidence and removal rate, as well as distributed delays in virus infections and in productions. By employing Lyapunov functionals and LaSalle's invariance principle, we define and prove the basic reproductive number R0 as a threshold quantity for stability of equilibria. It is shown that if R0 > 1 , then the infected equilibrium is globally asymptotically stable, while if R0 ⩽ 1 , then the infection free equilibrium is globally asymptotically stable under some reasonable assumptions. Moreover, n + 1 distributed delays describe (i) the time between viral entry and the transcription of viral RNA, (ii) the n - 1 -stage time needed for activated infected cells between viral RNA transcription and viral release, and (iii) the time necessary for the newly produced viruses to be infectious (maturation), respectively. The model can describe the viral infection dynamics of many viruses such as HIV-1, HCV and HBV.

  9. Time-varying bispectral analysis of visually evoked multi-channel EEG

    NASA Astrophysics Data System (ADS)

    Chandran, Vinod

    2012-12-01

    Theoretical foundations of higher order spectral analysis are revisited to examine the use of time-varying bicoherence on non-stationary signals using a classical short-time Fourier approach. A methodology is developed to apply this to evoked EEG responses where a stimulus-locked time reference is available. Short-time windowed ensembles of the response at the same offset from the reference are considered as ergodic cyclostationary processes within a non-stationary random process. Bicoherence can be estimated reliably with known levels at which it is significantly different from zero and can be tracked as a function of offset from the stimulus. When this methodology is applied to multi-channel EEG, it is possible to obtain information about phase synchronization at different regions of the brain as the neural response develops. The methodology is applied to analyze evoked EEG response to flash visual stimulii to the left and right eye separately. The EEG electrode array is segmented based on bicoherence evolution with time using the mean absolute difference as a measure of dissimilarity. Segment maps confirm the importance of the occipital region in visual processing and demonstrate a link between the frontal and occipital regions during the response. Maps are constructed using bicoherence at bifrequencies that include the alpha band frequency of 8Hz as well as 4 and 20Hz. Differences are observed between responses from the left eye and the right eye, and also between subjects. The methodology shows potential as a neurological functional imaging technique that can be further developed for diagnosis and monitoring using scalp EEG which is less invasive and less expensive than magnetic resonance imaging.

  10. Time-varying spectral characteristics of ENSO over the Last Millennium

    NASA Astrophysics Data System (ADS)

    Hope, Pandora; Henley, Benjamin J.; Gergis, Joelle; Brown, Josephine; Ye, Hua

    2016-10-01

    The characteristics of El Nino-Southern Oscillation (ENSO) spectra over the Last Millennium are examined to characterise variability over past centuries. Seven published palaeo-ENSO reconstructions and Nino3.4 from six Coupled Model Intercomparison Project-Phase 5 and Paleoclimate Modelling Intercomparison Project-Phase 3 (CMIP5-PMIP3) Last Millennium simulations were analysed. The corresponding Historical and pre-industrial Control CMIP5-PMIP3 simulations were also considered. The post-1850 spectrum of each modelled or reconstructed ENSO series captures aspects of the observed spectrum to varying degrees. We note that no single model or ENSO reconstruction completely reproduces the instrumental spectral characteristics. The spectral power across the 2-3 years (near biennial), 3-8 years (classical ENSO) and 8-25 years (decadal) periodicity bands was calculated in a sliding 50 year window, revealing temporal variability in the spectra. There was strong temporal variability in the spectral power of each periodicity band in observed Nino3.4 and SOI and for all reconstructions and simulations of ENSO. Significant peaks in spectral power such as observed in recent decades also occur in some of the reconstructed palaeo-ENSO (around 1600, the early 1700s and 1900) and modelled series (around the major volcanic eruptions of 1258 and 1452). While the recent increase in spectral power might be in response to enhanced greenhouse gas levels, the increase lies within the range of variability across the suite of ENSO reconstructions and simulations examined here. This study demonstrates that the analysis of a suite of ENSO reconstructions and model simulations can build a broader understanding of the time-varying nature of ENSO spectra, and how the nature of the past spectra of ENSO is to some extent dependant on the climate model or palaeo-ENSO reconstruction chosen.

  11. Decomposition Algorithm for Global Reachability on a Time-Varying Graph

    NASA Technical Reports Server (NTRS)

    Kuwata, Yoshiaki

    2010-01-01

    A decomposition algorithm has been developed for global reachability analysis on a space-time grid. By exploiting the upper block-triangular structure, the planning problem is decomposed into smaller subproblems, which is much more scalable than the original approach. Recent studies have proposed the use of a hot-air (Montgolfier) balloon for possible exploration of Titan and Venus because these bodies have thick haze or cloud layers that limit the science return from an orbiter, and the atmospheres would provide enough buoyancy for balloons. One of the important questions that needs to be addressed is what surface locations the balloon can reach from an initial location, and how long it would take. This is referred to as the global reachability problem, where the paths from starting locations to all possible target locations must be computed. The balloon could be driven with its own actuation, but its actuation capability is fairly limited. It would be more efficient to take advantage of the wind field and ride the wind that is much stronger than what the actuator could produce. It is possible to pose the path planning problem as a graph search problem on a directed graph by discretizing the spacetime world and the vehicle actuation. The decomposition algorithm provides reachability analysis of a time-varying graph. Because the balloon only moves in the positive direction in time, the adjacency matrix of the graph can be represented with an upper block-triangular matrix, and this upper block-triangular structure can be exploited to decompose a large graph search problem. The new approach consumes a much smaller amount of memory, which also helps speed up the overall computation when the computing resource has a limited physical memory compared to the problem size.

  12. High-Resolution Gravity and Time-Varying Gravity Field Recovery using GRACE and CHAMP

    NASA Technical Reports Server (NTRS)

    Shum, C. K.

    2002-01-01

    This progress report summarizes the research work conducted under NASA's Solid Earth and Natural Hazards Program 1998 (SENH98) entitled High Resolution Gravity and Time Varying Gravity Field Recovery Using GRACE (Gravity Recovery and Climate Experiment) and CHAMP (Challenging Mini-satellite Package for Geophysical Research and Applications), which included a no-cost extension time period. The investigation has conducted pilot studies to use the simulated GRACE and CHAMP data and other in situ and space geodetic observable, satellite altimeter data, and ocean mass variation data to study the dynamic processes of the Earth which affect climate change. Results from this investigation include: (1) a new method to use the energy approach for expressing gravity mission data as in situ measurements with the possibility to enhance the spatial resolution of the gravity signal; (2) the method was tested using CHAMP and validated with the development of a mean gravity field model using CHAMP data, (3) elaborate simulation to quantify errors of tides and atmosphere and to recover hydrological and oceanic signals using GRACE, results show that there are significant aliasing effect and errors being amplified in the GRACE resonant geopotential and it is not trivial to remove these errors, and (4) quantification of oceanic and ice sheet mass changes in a geophysical constraint study to assess their contributions to global sea level change, while the results improved significant over the use of previous studies using only the SLR (Satellite Laser Ranging)-determined zonal gravity change data, the constraint could be further improved with additional information on mantle rheology, PGR (Post-Glacial Rebound) and ice loading history. A list of relevant presentations and publications is attached, along with a summary of the SENH investigation generated in 2000.

  13. A Loudness Model for Time-Varying Sounds Incorporating Binaural Inhibition

    PubMed Central

    Glasberg, Brian R.; Varathanathan, Ajanth; Schlittenlacher, Josef

    2016-01-01

    This article describes a model of loudness for time-varying sounds that incorporates the concept of binaural inhibition, namely, that the signal applied to one ear can reduce the internal response to a signal at the other ear. For each ear, the model includes the following: a filter to allow for the effects of transfer of sound through the outer and middle ear; a short-term spectral analysis with greater frequency resolution at low than at high frequencies; calculation of an excitation pattern, representing the magnitudes of the outputs of the auditory filters as a function of center frequency; application of a compressive nonlinearity to the output of each auditory filter; and smoothing over time of the resulting instantaneous specific loudness pattern using an averaging process resembling an automatic gain control. The resulting short-term specific loudness patterns are used to calculate broadly tuned binaural inhibition functions, the amount of inhibition depending on the relative short-term specific loudness at the two ears. The inhibited specific loudness patterns are summed across frequency to give an estimate of the short-term loudness for each ear. The overall short-term loudness is calculated as the sum of the short-term loudness values for the two ears. The long-term loudness for each ear is calculated by smoothing the short-term loudness for that ear, again by a process resembling automatic gain control, and the overall loudness impression is obtained by summing the long-term loudness across ears. The predictions of the model are more accurate than those of an earlier model that did not incorporate binaural inhibition. PMID:28215113

  14. Time-Varying Causal Inference From Phosphoproteomic Measurements in Macrophage Cells

    PubMed Central

    Masnadi-Shirazi, Maryam; Maurya, Mano Ram; Subramaniam, Shankar

    2015-01-01

    Cellular signaling circuitry in eukaryotes can be studied by analyzing the regulation of protein phosphorylation and its impact on downstream mechanisms leading to a pheno-type. A primary role of phosphorylation is to act as a switch to turn “on” or “off” a protein activity or a cellular pathway. Specifically, protein phosphorylation is a major leit motif for transducing molecular signals inside the cell. Errors in transferring cellular information can alter the normal function and may lead to diseases such as cancer; an accurate reconstruction of the “true” signaling network is essential for understanding the molecular machinery involved in normal and pathological function. In this study, we have developed a novel framework for time-dependent reconstruction of signaling networks involved in the activation of macrophage cells leading to an inflammatory response. Several signaling pathways have been identified in macrophage cells, but the time-varying causal relationship that can produce a dynamic directed graph of these molecules has not been explored in detail. Here, we use the notion of Granger causality, and apply a vector autoregressive model to phosphoprotein time-course data in RAW 264.7 macrophage cells. Through the reconstruction of the phosphoprotein network, we were able to estimate the directionality and the dynamics of information flow. Significant interactions were selected through statistical hypothesis testing (t-test) of the coefficients of a linear model and were used to reconstruct the phosphoprotein signaling network. Our approach results in a three-stage phosphoprotein network that represents the evolution of the causal interactions in the intracellular signaling pathways. PMID:24681921

  15. Time-varying, serotype-specific force of infection of dengue virus.

    PubMed

    Reiner, Robert C; Stoddard, Steven T; Forshey, Brett M; King, Aaron A; Ellis, Alicia M; Lloyd, Alun L; Long, Kanya C; Rocha, Claudio; Vilcarromero, Stalin; Astete, Helvio; Bazan, Isabel; Lenhart, Audrey; Vazquez-Prokopec, Gonzalo M; Paz-Soldan, Valerie A; McCall, Philip J; Kitron, Uriel; Elder, John P; Halsey, Eric S; Morrison, Amy C; Kochel, Tadeusz J; Scott, Thomas W

    2014-07-01

    Infectious disease models play a key role in public health planning. These models rely on accurate estimates of key transmission parameters such as the force of infection (FoI), which is the per-capita risk of a susceptible person being infected. The FoI captures the fundamental dynamics of transmission and is crucial for gauging control efforts, such as identifying vaccination targets. Dengue virus (DENV) is a mosquito-borne, multiserotype pathogen that currently infects ∼390 million people a year. Existing estimates of the DENV FoI are inaccurate because they rely on the unrealistic assumption that risk is constant over time. Dengue models are thus unreliable for designing vaccine deployment strategies. Here, we present to our knowledge the first time-varying (daily), serotype-specific estimates of DENV FoIs using a spline-based fitting procedure designed to examine a 12-y, longitudinal DENV serological dataset from Iquitos, Peru (11,703 individuals, 38,416 samples, and 22,301 serotype-specific DENV infections from 1999 to 2010). The yearly DENV FoI varied markedly across time and serotypes (0-0.33), as did daily basic reproductive numbers (0.49-4.72). During specific time periods, the FoI fluctuations correlated across serotypes, indicating that different DENV serotypes shared common transmission drivers. The marked variation in transmission intensity that we detected indicates that intervention targets based on one-time estimates of the FoI could underestimate the level of effort needed to prevent disease. Our description of dengue virus transmission dynamics is unprecedented in detail, providing a basis for understanding the persistence of this rapidly emerging pathogen and improving disease prevention programs.

  16. Time-varying motor control of autotomized leopard gecko tails: multiple inputs and behavioral modulation.

    PubMed

    Higham, Timothy E; Russell, Anthony P

    2012-02-01

    Autotomy (voluntary loss of an appendage) is common among diverse groups of vertebrates and invertebrates, and much attention has been given to ecological and developmental aspects of tail autotomy in lizards. Although most studies have focused on the ramifications for the lizard (behavior, biomechanics, energetics, etc.), the tail itself can exhibit interesting behaviors once segregated from the body. For example, recent work highlighted the ability of leopard gecko tails to jump and flip, in addition to being able to swing back and forth. Little is known, however, about the control mechanisms underlying these movements. Using electromyography, we examined the time-varying in vivo motor patterns at four sites (two proximal and two distal) in the tail of the leopard gecko, Eublepharis macularius, following autotomy. Using these data we tested the hypothesis that the disparity in movements results simply from overlapping pattern generators within the tail. We found that burst duration, but not cycle duration, of the rhythmic swings reached a plateau at approximately 150 s following autotomy. This is likely because of physiological changes related to muscle fatigue and ischemia. For flips and jumps, burst and cycle duration exhibited no regular pattern. The coefficient of variation in motor patterns was significantly greater for jumps and flips than for rhythmic swings. This supports the conclusion that the different tail behaviors do not stem from overlapping pattern generators, but that they rely upon independent neural circuits. The signal controlling jumps and flips may be modified by sensory information from the environment. Finally, we found that jumps and flips are initiated using relatively synchronous activity between the two sides of the tail. In contrast, alternating activation of the right and left sides of the tail result in rhythmic swings. The mechanism underlying this change in tail behavior is comparable to locomotor gait changes in vertebrates.

  17. Identifiability of Additive, Time-Varying Actuator and Sensor Faults by State Augmentation

    NASA Technical Reports Server (NTRS)

    Upchurch, Jason M.; Gonzalez, Oscar R.; Joshi, Suresh M.

    2014-01-01

    Recent work has provided a set of necessary and sucient conditions for identifiability of additive step faults (e.g., lock-in-place actuator faults, constant bias in the sensors) using state augmentation. This paper extends these results to an important class of faults which may affect linear, time-invariant systems. In particular, the faults under consideration are those which vary with time and affect the system dynamics additively. Such faults may manifest themselves in aircraft as, for example, control surface oscillations, control surface runaway, and sensor drift. The set of necessary and sucient conditions presented in this paper are general, and apply when a class of time-varying faults affects arbitrary combinations of actuators and sensors. The results in the main theorems are illustrated by two case studies, which provide some insight into how the conditions may be used to check the theoretical identifiability of fault configurations of interest for a given system. It is shown that while state augmentation can be used to identify certain fault configurations, other fault configurations are theoretically impossible to identify using state augmentation, giving practitioners valuable insight into such situations. That is, the limitations of state augmentation for a given system and configuration of faults are made explicit. Another limitation of model-based methods is that there can be large numbers of fault configurations, thus making identification of all possible configurations impractical. However, the theoretical identifiability of known, credible fault configurations can be tested using the theorems presented in this paper, which can then assist the efforts of fault identification practitioners.

  18. Early-Emerging Nicotine Dependence Has Lasting and Time-Varying Effects on Adolescent Smoking Behavior.

    PubMed

    Selya, Arielle S; Dierker, Lisa; Rose, Jennifer S; Hedeker, Donald; Mermelstein, Robin J

    2016-08-01

    Novice and light adolescent smokers can develop symptoms of nicotine dependence, which predicts smoking behavior several years into the future. However, little is known about how the association between these early - emerging symptoms and later smoker behaviors may change across time from early adolescence into young adulthood. Data were drawn from a 7-year longitudinal study of experimental (<100 cigarettes/lifetime; N = 594) and light (100+ cigarettes/lifetime, but ≤5 cigarettes/day; N = 152) adolescent smokers. Time-varying effect models were used to examine the relationship between baseline nicotine dependence (assessed at age 15 ± 2 years) and future smoking frequency through age 24, after controlling for concurrent smoking heaviness. Baseline smoking status, race, and sex were examined as potential moderators of this relationship. Nicotine dependence symptoms assessed at approximately age 15 significantly predicted smoking frequency through age 24, over and above concurrent smoking heaviness, though it showed declining trends at older ages. Predictive validity was weaker among experimenters at young ages (<16), but stronger at older ages (20-23), relative to light smokers. Additionally, nicotine dependence was a stronger predictor of smoking frequency for white smokers around baseline (ages 14.5-16), relative to nonwhite smokers. Nicotine dependence assessed in mid-adolescence predicts smoking frequency well into early adulthood, over and above concurrent smoking heaviness, especially among novice smokers and nonwhite smokers. Early-emerging nicotine dependence is a promising marker for screening and interventions aimed at preventing smoking progression.

  19. Early diagnostic of concurrent gear degradation processes progressing under time-varying loads

    NASA Astrophysics Data System (ADS)

    Guilbault, Raynald; Lalonde, Sébastien

    2016-08-01

    This study develops a gear diagnostic procedure for the detection of multi- and concurrent degradation processes evolving under time-varying loads. Instead of a conventional comparison between a descriptor and an alarm level, this procedure bases its detection strategy on a descriptor evolution tracking; a lasting descriptor increase denotes the presence of ongoing degradation mechanisms. The procedure works from time domain residual signals prepared in the frequency domain, and accepts any gear conditions as reference signature. To extract the load fluctuation repercussions, the procedure integrates a scaling factor. The investigation first examines a simplification assuming a linear connection between the load and the dynamic response amplitudes. However, while generally valuable, the precision losses associated with large load variations may mask the contribution of tiny flaws. To better reflect the real non-linear relation, the paper reformulates the scaling factor; a power law with an exponent value of 0.85 produces noticeable improvements of the load effect extraction. To reduce the consequences of remaining oscillations, the procedure also includes a filtering phase. During the validation program, a synthetic wear progression assuming a commensurate relation between the wear depth and friction assured controlled evolutions of the surface degradation influence, whereas the fillet crack growth remained entirely determined by the operation conditions. Globally, the tested conditions attest that the final strategy provides accurate monitoring of coexisting isolated damages and general surface deterioration, and that its tracking-detection capacities are unaffected by severe time variations of external loads. The procedure promptly detects the presence of evolving abnormal phenomena. The tests show that the descriptor curve shapes virtually describe the constant wear progression superimposed on the crack length evolution. At the tooth fracture, the mean values of

  20. Time-varying causal network of the Korean financial system based on firm-specific risk premiums

    NASA Astrophysics Data System (ADS)

    Song, Jae Wook; Ko, Bonggyun; Cho, Poongjin; Chang, Woojin

    2016-09-01

    The aim of this paper is to investigate the Korean financial system based on time-varying causal network. We discover many stylized facts by utilizing the firm-specific risk premiums for measuring the causality direction from a firm to firm. At first, we discover that the interconnectedness of causal network is affected by the outbreak of financial events; the co-movement of firm-specific risk premium is strengthened after each positive event, and vice versa. Secondly, we find that the major sector of the Korean financial system is the Depositories, and the financial reform in June-2011 achieves its purpose by weakening the power of risk-spillovers of Broker-Dealers. Thirdly, we identify that the causal network is a small-world network with scale-free topology where the power-law exponents of out-Degree and negative event are more significant than those of in-Degree and positive event. Lastly, we discuss that the current aspects of causal network are closely related to the long-term future scenario of the KOSPI Composite index where the direction and stability are significantly affected by the power of risk-spillovers and the power-law exponents of degree distributions, respectively.

  1. Accounting for Unobserved Time-Varying Quality in Recreation Demand: An Application to a Sonoran Desert Wilderness

    EPA Science Inventory

    Environmental variables can be important factors in recreation demand. Analysts wishing to quantify environmental quality impacts face the difficult issue of isolating them from unobserved variables. Quality changes may occur in space, varying between sites, or in time, varying b...

  2. Self-similarity in the chemical evolution of galaxies and the delay-time distribution of SNe Ia

    NASA Astrophysics Data System (ADS)

    Walcher, C. J.; Yates, R. M.; Minchev, I.; Chiappini, C.; Bergemann, M.; Bruzual, G.; Charlot, S.; Coelho, P. R. T.; Gallazzi, A.; Martig, M.

    2016-10-01

    Recent improvements in the age dating of stellar populations and single stars allow us to study the ages and abundance of stars and galaxies with unprecedented accuracy. We here compare the relation between age and α-element abundances for stars in the solar neighborhood to that of local, early-type galaxies. We find these two relations to be very similar. Both fall into two regimes with a shallow slope for ages younger than ~9 Gyr and a steeper slope for ages older than that value. This quantitative similarity seems surprising because of the different types of galaxies and scales involved. For the sample of early-type galaxies we also show that the data are inconsistent with literature delay-time distributions of either single- or double-Gaussian shape. The data are consistent with a power-law delay-time distribution. We thus confirm that the delay-time distribution inferred for the Milky Way from chemical evolution arguments must also apply to massive early-type galaxies. We also offer a tentative explanation for the seeming universality of the age-[α/Fe] relation: it is the manifestation of averaging different stellar populations with varying chemical evolution histories.

  3. Analysis of the Robustness Dynamics of Wireless Mobile Ad Hoc Networks via Time Varying Dual Basis Representation

    DTIC Science & Technology

    2015-01-08

    Analysis of the Robustness Dynamics of Wireless Mobile Ad Hoc Networks via Time Varying Dual Basis Representation Thomas Parker, Jamie Johnson...between nodes to analyze the robustness of a wireless mobile ad hoc network (MANET) with a time-varying wireless channel. This spectral analysis and...a single eigenvalue is evaluated. 1. Introduction Mobile ad hoc networks (MANETs) are complex systems that can be foreseen supporting

  4. THE EFFECT OF A TIME-VARYING ACCRETION DISK SIZE ON QUASAR MICROLENSING LIGHT CURVES

    SciTech Connect

    Blackburne, Jeffrey A.; Kochanek, Christopher S. E-mail: ckochanek@astronomy.ohio-state.ed

    2010-08-01

    Microlensing perturbations to the magnification of gravitationally lensed quasar images are dependent on the angular size of the quasar. If quasar variability at visible wavelengths is caused by a change in the area of the accretion disk, it will affect the microlensing magnification. We derive the expected signal, assuming that the luminosity scales with some power of the disk area, and estimate its amplitude using simulations. We discuss the prospects for detecting the effect in real-world data and for using it to estimate the logarithmic slope of the luminosity's dependence on disk area. Such an estimate would provide a direct test of the standard thin accretion disk model. We tried fitting six seasons of the light curves of the lensed quasar HE 0435-1223 including this effect as a modification to the Kochanek et al. approach to estimating time delays. We find a dramatic improvement in the goodness of fit and relatively plausible parameters, but a robust estimate will require a full numerical calculation in order to correctly model the strong correlations between the structure of the microlensing magnification patterns and the magnitude of the effect. We also comment briefly on the effect of this phenomenon for the stability of time-delay estimates.

  5. Time-varying sodium absorption in the Type Ia supernova 2013gh

    NASA Astrophysics Data System (ADS)

    Ferretti, R.; Amanullah, R.; Goobar, A.; Johansson, J.; Vreeswijk, P. M.; Butler, R. P.; Cao, Y.; Cenko, S. B.; Doran, G.; Filippenko, A. V.; Freeland, E.; Hosseinzadeh, G.; Howell, D. A.; Lundqvist, P.; Mattila, S.; Nordin, J.; Nugent, P. E.; Petrushevska, T.; Valenti, S.; Vogt, S.; Wozniak, P.

    2016-07-01

    Context. Temporal variability of narrow absorption lines in high-resolution spectra of Type Ia supernovae (SNe Ia) is studied to search for circumstellar matter. Time series which resolve the profiles of absorption lines such as Na I D or Ca II H&K are expected to reveal variations due to photoionisation and subsequent recombination of the gases. The presence, composition, and geometry of circumstellar matter may hint at the elusive progenitor system of SNe Ia and could also affect the observed reddening law. Aims: To date, there are few known cases of time-varying Na I D absorption in SNe Ia, all of which occurred during relatively late phases of the supernova (SN) evolution. Photoionisation, however, is predicted to occur during the early phases of SNe Ia, when the supernovae peak in the ultraviolet. We attempt, therefore, to observe early-time absorption-line variations by obtaining high-resolution spectra of SNe before maximum light. Methods: We have obtained photometry and high-resolution spectroscopy of SNe Ia 2013gh and iPTF 13dge, to search for absorption-line variations. Furthermore, we study interstellar absorption features in relation to the observed photometric colours of the SNe. Results: Both SNe display deep Na I D and Ca II H&K absorption features. Furthermore, small but significant variations are detected in a feature of the Na I D profile of SN 2013gh. The variations are consistent with either geometric effects of rapidly moving or patchy gas clouds or photoionisation of Na I gas at R ≈ 1019 cm from the explosion. Conclusions: Our analysis indicates that it is necessary to focus on early phases to detect photoionisation effects of gases in the circumstellar medium of SNe Ia. Different absorbers such as Na I and Ca II can be used to probe for matter at different distances from the SNe. The nondetection of variations during early phases makes it possible to put limits on the abundance of the species at those distances. Full Tables 2 and 3 are only

  6. Time-varying spatial data integration and visualization: 4 Dimensions Environmental Observations Platform (4-DEOS)

    NASA Astrophysics Data System (ADS)

    Paciello, Rossana; Coviello, Irina; Filizzola, Carolina; Genzano, Nicola; Lisi, Mariano; Mazzeo, Giuseppe; Pergola, Nicola; Sileo, Giancanio; Tramutoli, Valerio

    2014-05-01

    In environmental studies the integration of heterogeneous and time-varying data, is a very common requirement for investigating and possibly visualize correlations among physical parameters underlying the dynamics of complex phenomena. Datasets used in such kind of applications has often different spatial and temporal resolutions. In some case superimposition of asynchronous layers is required. Traditionally the platforms used to perform spatio-temporal visual data analyses allow to overlay spatial data, managing the time using 'snapshot' data model, each stack of layers being labeled with different time. But this kind of architecture does not incorporate the temporal indexing neither the third spatial dimension which is usually given as an independent additional layer. Conversely, the full representation of a generic environmental parameter P(x,y,z,t) in the 4D space-time domain could allow to handle asynchronous datasets as well as less traditional data-products (e.g. vertical sections, punctual time-series, etc.) . In this paper we present the 4 Dimensions Environmental Observation Platform (4-DEOS), a system based on a web services architecture Client-Broker-Server. This platform is a new open source solution for both a timely access and an easy integration and visualization of heterogeneous (maps, vertical profiles or sections, punctual time series, etc.) asynchronous, geospatial products. The innovative aspect of the 4-DEOS system is that users can analyze data/products individually moving through time, having also the possibility to stop the display of some data/products and focus on other parameters for better studying their temporal evolution. This platform gives the opportunity to choose between two distinct display modes for time interval or for single instant. Users can choose to visualize data/products in two ways: i) showing each parameter in a dedicated window or ii) visualize all parameters overlapped in a single window. A sliding time bar, allows

  7. Time varying velocity structures in Earth's outer core: Constraints from exotic P-waves

    NASA Astrophysics Data System (ADS)

    Day, E. A.; Irving, J. C.; Deuss, A. F.; Cormier, V. F.

    2011-12-01

    The outer core is one of the most dynamic divisions of our planet. However, despite undergoing vigorous convection, the outer core is not necessarily a uniform, homogeneous layer of the Earth. Accumulation of light element enriched iron at the top of the outer core, below the core-mantle boundary, may lead to the formation of a stably stratified layer, corresponding to the E' layer as defined by Bullen. The E' layer would have different properties to the rest of the outer core and may be a source of scattering. The lowermost outer core, the F layer, may also have different physical properties than the rest of the outer core, either due to the crystallisation of iron or the release of light elements as the inner core grows. Time varying structure in the Earth's core has been observed in some previous studies, particularly using earthquake doublets. The vigorous convection in the outer core may lead to small-scale lateral variations in its velocity structure over time, due to the movement of fluids and slurry near to the core-mantle and inner core boundaries. We investigate the velocity and attenuation structure of the upper 1500 km of the outer core using high frequency PmKP seismic phases. PmKP waves travel as P-waves throughout the Earth, bouncing m-1 times on the underside of the core-mantle boundary. By analysing the relative arrival times and amplitudes of the PmKP waves and other seismic phases, and comparing these to synthetic waveforms, it is possible to constrain the velocity and attenuation characteristics of the upper 1500 km of the outer core. We correct for known mantle structure and explore the effects of core-mantle boundary topography. To investigate the scattering characteristics of the uppermost outer core and the sharpness of any stratified layers we search for precursors to PmKP phases, which are elusive. P4KP-PcP differential travel times suggest that the uppermost 1300 km of the outer core is up to 0.4% slower than PREM. There is some evidence

  8. Time-varying enhancement of human cortical excitability mediated by cutaneous inputs during precision grip.

    PubMed Central

    Johansson, R S; Lemon, R N; Westling, G

    1994-01-01

    1. We have investigated the afferent neurogram, muscular activity and mechanical responses while subjects restrained, with a precision grip, an object subjected to pulling loads directed away from the hand. At unpredictable times 'ramp-and-hold' loads of 1 N were delivered at a rate of ca 80 N s-1. The load ramp produced a sharp increase in multiunit activity recorded from cutaneous afferents of the median nerve. The first response in the EMG of distal hand muscles commenced at 51 +/- 2.4 ms (mean +/- S.D.); a further steep increase in activity began about 20 ms later, and this was associated with a marked augmentation of the grip force increase. 2. In four subjects, transcranial magnetic stimulation (TMS) was delivered to the contralateral motor cortex in 1000 out of a total of 1500 loading trials. The time of the stimulus was randomly selected to occur either at one of nine defined points (separated by 20 ms) before and after the computer command triggering the load force increase, or during steady periods of grip. 3. In most hand and arm muscles, there was a powerful facilitation of the short-latency EMG responses evoked by TMS delivered 40-140 ms after the load force command. The amplitudes of the largest responses (TMS delivered at 80-100 ms) were 850% higher on average than those observed when subjects gripped the unloaded object or when they restrained the statically loaded object. This large modulation was only obtained with stimulus intensities that were subthreshold in the relaxed subject. 4. The modulation was not simply a reflection of the time-varying level of motoneuronal activity during the loading trial. In most muscles, changes in the amplitude of the TMS-evoked responses were disproportionately larger than the corresponding modulation of the background EMG activity. At its maximum, the modulation in the TMS-evoked response was nearly 300% larger. Furthermore, the strength of the TMS-evoked responses did not strictly co-vary with amplitude of

  9. Coalescence computations for large samples drawn from populations of time-varying sizes

    PubMed Central

    Polanski, Andrzej; Szczesna, Agnieszka; Garbulowski, Mateusz; Kimmel, Marek

    2017-01-01

    We present new results concerning probability distributions of times in the coalescence tree and expected allele frequencies for coalescent with large sample size. The obtained results are based on computational methodologies, which involve combining coalescence time scale changes with techniques of integral transformations and using analytical formulae for infinite products. We show applications of the proposed methodologies for computing probability distributions of times in the coalescence tree and their limits, for evaluation of accuracy of approximate expressions for times in the coalescence tree and expected allele frequencies, and for analysis of large human mitochondrial DNA dataset. PMID:28170404

  10. Spatially distributed control of the dynamics of the logistic delay equation

    NASA Astrophysics Data System (ADS)

    Glyzin, D. S.; Kashchenko, S. A.

    2014-06-01

    The influence exerted by a small spatially inhomogeneous control on the dynamics of the logistic delay equation is studied. This paper consists of two parts. The first deals with the case where the logistic delay equation has a stable relaxation cycle. It is shown that a small control function can give rise to complex relaxation objects, namely, to a large number of different attractors. In the second part, the local dynamics of the stability problem is analyzed in a neighborhood of equilibrium in a close-to-critical case of "infinite" dimension. Special quasi-normal forms are constructed whose nonlocal dynamics determine the local behavior of solutions to the original equation. Some results of a numerical analysis are presented.

  11. Benefits of preserving stationary and time-varying formant structure in alternative representations of speech: implications for cochlear implants.

    PubMed

    Nittrouer, Susan; Lowenstein, Joanna H; Wucinich, Taylor; Tarr, Eric

    2014-10-01

    Cochlear implants have improved speech recognition for deaf individuals, but further modifications are required before performance will match that of normal-hearing listeners. In this study, the hypotheses were tested that (1) implant processing would benefit from efforts to preserve the structure of the low-frequency formants and (2) time-varying aspects of that structure would be especially beneficial. Using noise-vocoded and sine-wave stimuli with normal-hearing listeners, two experiments examined placing boundaries between static spectral channels to optimize representation of the first two formants and preserving time-varying formant structure. Another hypothesis tested in this study was that children might benefit more than adults from strategies that preserve formant structure, especially time-varying structure. Sixty listeners provided data to each experiment: 20 adults and 20 children at each of 5 and 7 years old. Materials were consonant-vowel-consonant words, four-word syntactically correct, meaningless sentences, and five-word syntactically correct, meaningful sentences. Results showed that listeners of all ages benefited from having channel boundaries placed to optimize information about the first two formants, and benefited even more from having time-varying structure. Children showed greater gains than adults only for time-varying formant structure. Results suggest that efforts would be well spent trying to design processing strategies that preserve formant structure.

  12. Benefits of preserving stationary and time-varying formant structure in alternative representations of speech: Implications for cochlear implants

    PubMed Central

    Nittrouer, Susan; Lowenstein, Joanna H.; Wucinich, Taylor; Tarr, Eric

    2014-01-01

    Cochlear implants have improved speech recognition for deaf individuals, but further modifications are required before performance will match that of normal-hearing listeners. In this study, the hypotheses were tested that (1) implant processing would benefit from efforts to preserve the structure of the low-frequency formants and (2) time-varying aspects of that structure would be especially beneficial. Using noise-vocoded and sine-wave stimuli with normal-hearing listeners, two experiments examined placing boundaries between static spectral channels to optimize representation of the first two formants and preserving time-varying formant structure. Another hypothesis tested in this study was that children might benefit more than adults from strategies that preserve formant structure, especially time-varying structure. Sixty listeners provided data to each experiment: 20 adults and 20 children at each of 5 and 7 years old. Materials were consonant-vowel-consonant words, four-word syntactically correct, meaningless sentences, and five-word syntactically correct, meaningful sentences. Results showed that listeners of all ages benefited from having channel boundaries placed to optimize information about the first two formants, and benefited even more from having time-varying structure. Children showed greater gains than adults only for time-varying formant structure. Results suggest that efforts would be well spent trying to design processing strategies that preserve formant structure. PMID:25324085

  13. On-line updating Gaussian mixture model for aircraft wing spar damage evaluation under time-varying boundary condition

    NASA Astrophysics Data System (ADS)

    Qiu, Lei; Yuan, Shenfang; Chang, Fu-Kuo; Bao, Qiao; Mei, Hanfei

    2014-12-01

    Structural health monitoring technology for aerospace structures has gradually turned from fundamental research to practical implementations. However, real aerospace structures work under time-varying conditions that introduce uncertainties to signal features that are extracted from sensor signals, giving rise to difficulty in reliably evaluating the damage. This paper proposes an online updating Gaussian Mixture Model (GMM)-based damage evaluation method to improve damage evaluation reliability under time-varying conditions. In this method, Lamb-wave-signal variation indexes and principle component analysis (PCA) are adopted to obtain the signal features. A baseline GMM is constructed on the signal features acquired under time-varying conditions when the structure is in a healthy state. By adopting the online updating mechanism based on a moving feature sample set and inner probability structural reconstruction, the probability structures of the GMM can be updated over time with new monitoring signal features to track the damage progress online continuously under time-varying conditions. This method can be implemented without any physical model of damage or structure. A real aircraft wing spar, which is an important load-bearing structure of an aircraft, is adopted to validate the proposed method. The validation results show that the method is effective for edge crack growth monitoring of the wing spar bolts holes under the time-varying changes in the tightness degree of the bolts.

  14. Structure and composition of the distant lunar exosphere: Constraints from ARTEMIS observations of ion acceleration in time-varying fields

    NASA Astrophysics Data System (ADS)

    Halekas, J. S.; Poppe, A. R.; Farrell, W. M.; McFadden, J. P.

    2016-06-01

    By analyzing the trajectories of ionized constituents of the lunar exosphere in time-varying electromagnetic fields, we can place constraints on the composition, structure, and dynamics of the lunar exosphere. Heavy ions travel slower than light ions in the same fields, so by observing the lag between field rotations and the response of ions from the lunar exosphere, we can place constraints on the composition of the ions. Acceleration, Reconnection, Turbulence, and Electrodynamics of Moon's Interaction with the Sun (ARTEMIS) provides an ideal platform to utilize such an analysis, since its two-probe vantage allows precise timing of the propagation of field discontinuities in the solar wind, and its sensitive plasma instruments can detect the ion response. We demonstrate the utility of this technique by using fully time-dependent charged particle tracing to analyze several minutes of ion observations taken by the two ARTEMIS probes ~3000-5000 km above the dusk terminator on 25 January 2014. The observations from this time period allow us to reach several interesting conclusions. The ion production at altitudes of a few hundred kilometers above the sunlit surface of the Moon has an unexpectedly significant contribution from species with masses of 40 amu or greater. The inferred distribution of the neutral source population has a large scale height, suggesting that micrometeorite impact vaporization and/or sputtering play an important role in the production of neutrals from the surface. Our observations also suggest an asymmetry in ion production, consistent with either a compositional variation in neutral vapor production or a local reduction in solar wind sputtering in magnetic regions of the surface.

  15. Structure and Composition of the Distant Lunar Exosphere: Constraints from ARTEMIS Observations of Ion Acceleration in Time-Varying Fields

    NASA Technical Reports Server (NTRS)

    Halekas, J. S.; Poppe, A. R.; Farrell, W. M.; McFadden, J. P.

    2016-01-01

    By analyzing the trajectories of ionized constituents of the lunar exosphere in time-varying electromagnetic fields, we can place constraints on the composition, structure, and dynamics of the lunar exosphere. Heavy ions travel slower than light ions in the same fields, so by observing the lag between field rotations and the response of ions from the lunar exosphere, we can place constraints on the composition of the ions. Acceleration, Reconnection, Turbulence, and Electrodynamics of Moon's Interaction with the Sun (ARTEMIS) provides an ideal platform to utilize such an analysis, since its two-probe vantage allows precise timing of the propagation of field discontinuities in the solar wind, and its sensitive plasma instruments can detect the ion response. We demonstrate the utility of this technique by using fully time-dependent charged particle tracing to analyze several minutes of ion observations taken by the two ARTEMIS probes 3000-5000 km above the dusk terminator on 25 January 2014. The observations from this time period allow us to reach several interesting conclusions. The ion production at altitudes of a few hundred kilometers above the sunlit surface of the Moon has an unexpectedly significant contribution from species with masses of 40 amu or greater. The inferred distribution of the neutral source population has a large scale height, suggesting that micrometeorite impact vaporization and/or sputtering play an important role in the production of neutrals from the surface. Our observations also suggest an asymmetry in ion production, consistent with either a compositional variation in neutral vapor production or a local reduction in solar wind sputtering in magnetic regions of the surface.

  16. pth moment exponential stochastic synchronization of coupled memristor-based neural networks with mixed delays via delayed impulsive control.

    PubMed

    Yang, Xinsong; Cao, Jinde; Qiu, Jianlong

    2015-05-01

    This paper concerns the pth moment synchronization in an array of generally coupled memristor-based neural networks with time-varying discrete delays, unbounded distributed delays, as well as stochastic perturbations. Hybrid controllers are designed to cope with the uncertainties caused by the state-dependent parameters: (a) state feedback controllers combined with delayed impulsive controller; (b) adaptive controller combined with delayed impulsive controller. Based on an impulsive differential inequality, the properties of random variables, the framework of Filippov solution, and Lyapunov functional method, sufficient conditions are derived to guarantee that the considered coupled memristor-based neural networks can be pth moment globally exponentially synchronized onto an isolated node under both of the two classes of hybrid impulsive controllers. Finally, numerical simulations are given to show the effectiveness of the theoretical results.

  17. Survival trees for left-truncated and right-censored data, with application to time-varying covariate data.

    PubMed

    Fu, Wei; Simonoff, Jeffrey S

    2016-12-26

    SUMMARYTree methods (recursive partitioning) are a popular class of nonparametric methods for analyzing data. One extension of the basic tree methodology is the survival tree, which applies recursive partitioning to censored survival data. There are several existing survival tree methods in the literature, which are mainly designed for right-censored data. We propose two new survival trees for left-truncated and right-censored (LTRC) data, which can be seen as a generalization of the traditional survival tree for right-censored data. Further, we show that such trees can be used to analyze survival data with time-varying covariates, essentially building a time-varying covariates survival tree. Implementation of the methods is easy, and simulations and real data analysis results show that the proposed methods work well for LTRC data and survival data with time-varying covariates, respectively.

  18. Radiative transfer equations in broad-band, time-varying fields

    NASA Technical Reports Server (NTRS)

    Cooper, J.; Zoller, P.

    1984-01-01

    A derivation of the equation of transfer is obtained by starting with Maxwell's equations in the 'slowly varying envelope' form. Particular attention is paid to characterizing the intensity that is 'seen' by the atom (which is found to be related to a Wigner distribution of the electric field). The equation of transfer is found to be valid for 'broad-band' slowly varying radiation fields.

  19. Time frequency chirp-Wigner transform for signals with any nonlinear polynomial time varying instantaneous frequency

    NASA Astrophysics Data System (ADS)

    Gelman, L.; Gould, J. D.

    2007-11-01

    The new technique, the time-frequency chirp-Wigner transform has been proposed recently. This technique is further investigated for the general case of higher order chirps, i.e. non-stationary signals with any nonlinear polynomial variation of the instantaneous frequency in time. Analytical and numerical comparison of the chirp-Wigner transform and the classical Wigner distribution was performed for processing of single-component and multi-component higher order chirps. It is shown for the general case of single component higher order chirps that the chirp-Wigner transform has an essential advantage in comparison with the traditional Wigner distribution: the chirp-Wigner transform ideally follows the nonlinear polynomial frequency variation without amplitude errors. It is shown for multi-component signal where each component is a higher order chirp, that the chirp-Wigner transform adjusted to a single component will follow the instantaneous frequency of the component without amplitude errors. It is also shown that the classical Wigner distribution is unable to estimate component amplitudes of single component and multi-component higher order chirps.

  20. Mendelian randomization analysis of a time-varying exposure for binary disease outcomes using functional data analysis methods.

    PubMed

    Cao, Ying; Rajan, Suja S; Wei, Peng

    2016-12-01

    A Mendelian randomization (MR) analysis is performed to analyze the causal effect of an exposure variable on a disease outcome in observational studies, by using genetic variants that affect the disease outcome only through the exposure variable. This method has recently gained popularity among epidemiologists given the success of genetic association studies. Many exposure variables of interest in epidemiological studies are time varying, for example, body mass index (BMI). Although longitudinal data have been collected in many cohort studies, current MR studies only use one measurement of a time-varying exposure variable, which cannot adequately capture the long-term time-varying information. We propose using the functional principal component analysis method to recover the underlying individual trajectory of the time-varying exposure from the sparsely and irregularly observed longitudinal data, and then conduct MR analysis using the recovered curves. We further propose two MR analysis methods. The first assumes a cumulative effect of the time-varying exposure variable on the disease risk, while the second assumes a time-varying genetic effect and employs functional regression models. We focus on statistical testing for a causal effect. Our simulation studies mimicking the real data show that the proposed functional data analysis based methods incorporating longitudinal data have substantial power gains compared to standard MR analysis using only one measurement. We used the Framingham Heart Study data to demonstrate the promising performance of the new methods as well as inconsistent results produced by the standard MR analysis that relies on a single measurement of the exposure at some arbitrary time point.

  1. Time-varying volatility in Malaysian stock exchange: An empirical study using multiple-volatility-shift fractionally integrated model

    NASA Astrophysics Data System (ADS)

    Cheong, Chin Wen

    2008-02-01

    This article investigated the influences of structural breaks on the fractionally integrated time-varying volatility model in the Malaysian stock markets which included the Kuala Lumpur composite index and four major sectoral indices. A fractionally integrated time-varying volatility model combined with sudden changes is developed to study the possibility of structural change in the empirical data sets. Our empirical results showed substantial reduction in fractional differencing parameters after the inclusion of structural change during the Asian financial and currency crises. Moreover, the fractionally integrated model with sudden change in volatility performed better in the estimation and specification evaluations.

  2. Synchronization of Hierarchical Time-Varying Neural Networks Based on Asynchronous and Intermittent Sampled-Data Control.

    PubMed

    Xiong, Wenjun; Patel, Ragini; Cao, Jinde; Zheng, Wei Xing

    2016-09-22

    In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time t. The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.

  3. The optimal manufacturing batch size with rework under time-varying demand process for a finite time horizon

    NASA Astrophysics Data System (ADS)

    Musa, Sarah; Supadi, Siti Suzlin; Omar, Mohd

    2014-07-01

    Rework is one of the solutions to some of the main issues in reverse logistic and green supply chain as it reduces production cost and environmental problem. Many researchers focus on developing rework model, but to the knowledge of the author, none of them has developed a model for time-varying demand rate. In this paper, we extend previous works and develop multiple batch production system for time-varying demand rate with rework. In this model, the rework is done within the same production cycle.

  4. Combining Meteosat-10 satellite image data with GPS tropospheric path delays to estimate regional integrated water vapor (IWV) distribution

    NASA Astrophysics Data System (ADS)

    Leontiev, Anton; Reuveni, Yuval

    2017-02-01

    Using GPS satellites signals, we can study different processes and coupling mechanisms that can help us understand the physical conditions in the lower atmosphere, which might lead or act as proxies for severe weather events such as extreme storms and flooding. GPS signals received by ground stations are multi-purpose and can also provide estimates of tropospheric zenith delays, which can be converted into accurate integrated water vapor (IWV) observations using collocated pressure and temperature measurements on the ground. Here, we present for the first time the use of Israel's dense regional GPS network for extracting tropospheric zenith path delays combined with near-real-time Meteosat-10 water vapor (WV) and surface temperature pixel intensity values (7.3 and 10.8 µm channels, respectively) in order to assess whether it is possible to obtain absolute IWV (kg m-2) distribution. The results show good agreement between the absolute values obtained from our triangulation strategy based solely on GPS zenith total delays (ZTD) and Meteosat-10 surface temperature data compared with available radiosonde IWV absolute values. The presented strategy can provide high temporal and special IWV resolution, which is needed as part of the accurate and comprehensive observation data integrated in modern data assimilation systems and is required for increasing the accuracy of regional numerical weather prediction systems forecast.

  5. Nonequilibrium Behavior of Carriers in Semiconductors Subjected to Strong Space-Time Varying Fields

    DTIC Science & Technology

    1991-12-01

    over the distribution, and are given by + V. (n,) = , n, v., - , nv,, (2) J-I.loi Jl-j.oi e(n,p,) Anp anp)+ V(n~p, -!s,) =qEn, - V(njkBT. 1) - -~~~- Y ...W. R. Curtice and Y . H. Yun, "A Temperature Model for the GaAs MESFET," IEEE Trans. Elect. Dev., Vol. ED-28, p. 954, 1981. (11] B. Carnez, A. Cppy, A...4571 (1984); Phys. Rev. B 32, 2. H. 1. Lee, J. Basinski, L. Y . Juravel & J. C. Woolley, 2645 (1985). Can. J. Phys. 57, 233 (1979). 28. K. Lee & M. S. Ss

  6. Intensity modulated radiation therapy with field rotation--a time-varying fractionation study.

    PubMed

    Dink, Delal; Langer, Mark P; Rardin, Ronald L; Pekny, Joseph F; Reklaitis, Gintaras V; Saka, Behlul

    2012-06-01

    This paper proposes a novel mathematical approach to the beam selection problem in intensity modulated radiation therapy (IMRT) planning. The approach allows more beams to be used over the course of therapy while limiting the number of beams required in any one session. In the proposed field rotation method, several sets of beams are interchanged throughout the treatment to allow a wider selection of beam angles than would be possible with fixed beam orientations. The choice of beamlet intensities and the number of identical fractions for each set are determined by a mixed integer linear program that controls jointly for the distribution per fraction and the cumulative dose distribution delivered to targets and critical structures. Trials showed the method allowed substantial increases in the dose objective and/or sparing of normal tissues while maintaining cumulative and fraction size limits. Trials for a head and neck site showed gains of 25%-35% in the objective (average tumor dose) and for a thoracic site gains were 7%-13%, depending on how strict the fraction size limits were set. The objective did not rise for a prostate site significantly, but the tolerance limits on normal tissues could be strengthened with the use of multiple beam sets.

  7. Metaheuristics for multi products inventory routing problem with time varying demand

    NASA Astrophysics Data System (ADS)

    Moin, Noor Hasnah; Ab Halim, Huda Zuhrah; Yuliana, Titi

    2014-07-01

    This paper addresses the inventory routing problem (IRP) with a many-to-one distribution network, consisting of a single depot, an assembly plant, and geographically dispersed suppliers where a capacitated homogeneous vehicle delivers a distinct product from the suppliers to fulfill the demand specified by the assembly plant over the planning horizon. The inventory holding cost is assumed to be product specific and only incurred at the assembly plant. Two metaheuristics comprise of artificial bee colony (ABC) and scatter search (SS) algorithms are proposed to solve the problem. Computational testing on instances which represents small, medium, and large data sets show that the ABC algorithm performs slightly better when compared the SS overall except for fifty suppliers problems.

  8. Control-focused, nonlinear and time-varying modelling of dielectric elastomer actuators with frequency response analysis

    NASA Astrophysics Data System (ADS)

    Jacobs, William R.; Wilson, Emma D.; Assaf, Tareq; Rossiter, Jonathan; Dodd, Tony J.; Porrill, John; Anderson, Sean R.

    2015-05-01

    Current models of dielectric elastomer actuators (DEAs) are mostly constrained to first principal descriptions that are not well suited to the application of control design due to their computational complexity. In this work we describe an integrated framework for the identification of control focused, data driven and time-varying DEA models that allow advanced analysis of nonlinear system dynamics in the frequency-domain. Experimentally generated input-output data (voltage-displacement) was used to identify control-focused, nonlinear and time-varying dynamic models of a set of film-type DEAs. The model description used was the nonlinear autoregressive with exogenous input structure. Frequency response analysis of the DEA dynamics was performed using generalized frequency response functions, providing insight and a comparison into the time-varying dynamics across a set of DEA actuators. The results demonstrated that models identified within the presented framework provide a compact and accurate description of the system dynamics. The frequency response analysis revealed variation in the time-varying dynamic behaviour of DEAs fabricated to the same specifications. These results suggest that the modelling and analysis framework presented here is a potentially useful tool for future work in guiding DEA actuator design and fabrication for application domains such as soft robotics.

  9. Evaluation of Influence of Time-Varying Electromagnetic Component in M-EMS on Flow at Free Surface

    NASA Astrophysics Data System (ADS)

    Satou, Shoji; Fujisaki, Keisuke

    In the continuous casting process, surface quality of steel is as important as its productivity. The surface quality is mostly decided in the molten metal flow during initial solidification stage, which progresses at the free surface of the molten steel. To improve the surface quality, this flow must be controlled. M-EMS generates the time-varying electromagnetic force, which helps to control the shape of the free surface. In this paper, we evaluate the possibility of controlling the flow at the free surface by the MHD calculations. The result showed a little possibility of the flow at the free surface being controlled. Though the free surface variation in a pulsed EMC process, which controls the shape of the free surface using the time-varying electromagnetic force component, depends on electromagnetic force, the time-varying component in the M-EMS is decided by the velocity of the molten metal. Since there is a first-order lag between the electromagnetic force and this velocity, free surface variation in M-EMS does not linearly depend on the time-varying electromagnetic component.

  10. Global distribution of polymorphisms associated with delayed Plasmodium falciparum parasite clearance following artemisinin treatment: genotyping of archive blood samples.

    PubMed

    Murai, Kenji; Culleton, Richard; Hisaoka, Teruhiko; Endo, Hiroyoshi; Mita, Toshihiro

    2015-06-01

    The recent emergence and spread of artemisinin-resistant Plasmodium falciparum isolates is a growing concern for global malaria-control efforts. A recent genome-wide analysis study identified two SNPs at genomic positions MAL10-688956 and MAL13-1718319, which are linked to delayed clearance of parasites following artemisinin combination therapy (ACT). It is expected that continuous artemisinin pressure will affect the distribution of these SNPs. Here, we investigate the worldwide distribution of these SNPs using a large number of archived samples in order to generate baseline data from the period before the emergence of ACT resistance. The presence of SNPs in MAL10-688956 and MAL13-1718319 was assessed by nested PCR RFLP and direct DNA sequencing using 653 global P. falciparum samples obtained before the reported emergence of ACT resistance. SNPs at MAL10-688956 and MAL13-1718319 associated with delayed parasite clearance following ACT administration were observed in 8% and 3% of parasites, respectively, mostly in Cambodia and Thailand. Parasites harbouring both SNPs were found in only eight (1%) isolates, all of which were from Cambodia and Thailand. Linkage disequilibrium was detected between MAL10-688956 and MAL13-1718319, suggesting that this SNP combination may have been selected by ACT drug pressure. Neither of the SNPs associated with delayed parasite clearance were observed in samples from Africa or South America. Baseline information of the geographical difference of MAL10-688956 and MAL13-1718319 SNPs provides a solid basis for assessing whether these SNPs are selected by artemisinin-based combination therapies.

  11. Gearbox fault diagnosis using adaptive zero phase time-varying filter based on multi-scale chirplet sparse signal decomposition

    NASA Astrophysics Data System (ADS)

    Wu, Chunyan; Liu, Jian; Peng, Fuqiang; Yu, Dejie; Li, Rong

    2013-07-01

    When used for separating multi-component non-stationary signals, the adaptive time-varying filter(ATF) based on multi-scale chirplet sparse signal decomposition(MCSSD) generates phase shift and signal distortion. To overcome this drawback, the zero phase filter is introduced to the mentioned filter, and a fault diagnosis method for speed-changing gearbox is proposed. Firstly, the gear meshing frequency of each gearbox is estimated by chirplet path pursuit. Then, according to the estimated gear meshing frequencies, an adaptive zero phase time-varying filter(AZPTF) is designed to filter the original signal. Finally, the basis for fault diagnosis is acquired by the envelope order analysis to the filtered signal. The signal consisting of two time-varying amplitude modulation and frequency modulation(AM-FM) signals is respectively analyzed by ATF and AZPTF based on MCSSD. The simulation results show the variances between the original signals and the filtered signals yielded by AZPTF based on MCSSD are 13.67 and 41.14, which are far less than variances (323.45 and 482.86) between the original signals and the filtered signals obtained by ATF based on MCSSD. The experiment results on the vibration signals of gearboxes indicate that the vibration signals of the two speed-changing gearboxes installed on one foundation bed can be separated by AZPTF effectively. Based on the demodulation information of the vibration signal of each gearbox, the fault diagnosis can be implemented. Both simulation and experiment examples prove that the proposed filter can extract a mono-component time-varying AM-FM signal from the multi-component time-varying AM-FM signal without distortion.

  12. Description of time-varying desorption kinetics. Release of naphthalene from contaminated soils

    SciTech Connect

    Connaughton, D.F.; Stedinger, J.R.; Lion, L.W.; Shuler, M.L. )

    1993-11-01

    Release rates of naphthalene from suspensions of freshly contaminated (days to weeks) and aged (approximately 30 years) soil samples were obtained using a gas purge method. A continuously increasing resistance to desorption was observed with increasing purge time. Initial desorption rates were similar to those estimated using available empirical relationships, but subsequent desorption rates were lower by more than 1 order of magnitude. A model incorporating a continuum of compartments with a gamma ([Gamma]) distribution of rate coefficients was postulated to describe the experimental data. An analytical equation with two adjustable parameters was obtained for the mass fraction desorbed. Release profiles with this [open quotes][Gamma] model[close quotes] were able to describe the experimental release profiles for long term desorption experiments. An implication of the gamma model is that increased incubation time will allow organic compounds to be sorbed to compartments or regions in the sorbent that exhibit slow adsorption/desorption kinetics. This has important implications for the fate and remediation of sites that have been contaminated with hydrophobic organic compounds for extended time periods. 31 refs., 6 figs., 3 tabs.

  13. Multiobjective Resource-Constrained Project Scheduling with a Time-Varying Number of Tasks

    PubMed Central

    Abello, Manuel Blanco

    2014-01-01

    In resource-constrained project scheduling (RCPS) problems, ongoing tasks are restricted to utilizing a fixed number of resources. This paper investigates a dynamic version of the RCPS problem where the number of tasks varies in time. Our previous work investigated a technique called mapping of task IDs for centroid-based approach with random immigrants (McBAR) that was used to solve the dynamic problem. However, the solution-searching ability of McBAR was investigated over only a few instances of the dynamic problem. As a consequence, only a small number of characteristics of McBAR, under the dynamics of the RCPS problem, were found. Further, only a few techniques were compared to McBAR with respect to its solution-searching ability for solving the dynamic problem. In this paper, (a) the significance of the subalgorithms of McBAR is investigated by comparing McBAR to several other techniques; and (b) the scope of investigation in the previous work is extended. In particular, McBAR is compared to a technique called, Estimation Distribution Algorithm (EDA). As with McBAR, EDA is applied to solve the dynamic problem, an application that is unique in the literature. PMID:24883398

  14. Multi-Level Anomaly Detection on Time-Varying Graph Data

    SciTech Connect

    Bridges, Robert A; Collins, John P; Ferragut, Erik M; Laska, Jason A; Sullivan, Blair D

    2015-01-01

    This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating probabilities at finer levels, and these closely related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitates intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. To illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.

  15. Individualistic and Time-Varying Tree-Ring Growth to Climate Sensitivity

    PubMed Central

    Carrer, Marco

    2011-01-01

    The development of dendrochronological time series in order to analyze climate-growth relationships usually involves first a rigorous selection of trees and then the computation of the mean tree-growth measurement series. This study suggests a change in the perspective, passing from an analysis of climate-growth relationships that typically focuses on the mean response of a species to investigating the whole range of individual responses among sample trees. Results highlight that this new approach, tested on a larch and stone pine tree-ring dataset, outperforms, in terms of information obtained, the classical one, with significant improvements regarding the strength, distribution and time-variability of the individual tree-ring growth response to climate. Moreover, a significant change over time of the tree sensitivity to climatic variability has been detected. Accordingly, the best-responder trees at any one time may not always have been the best-responders and may not continue to be so. With minor adjustments to current dendroecological protocol and adopting an individualistic approach, we can improve the quality and reliability of the ecological inferences derived from the climate-growth relationships. PMID:21829523

  16. A multi-level anomaly detection algorithm for time-varying graph data with interactive visualization

    DOE PAGES

    Bridges, Robert A.; Collins, John P.; Ferragut, Erik M.; ...

    2016-01-01

    This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating node probabilities, and these related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitatesmore » intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. Furthermore, to illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.« less

  17. A multi-level anomaly detection algorithm for time-varying graph data with interactive visualization

    SciTech Connect

    Bridges, Robert A.; Collins, John P.; Ferragut, Erik M.; Laska, Jason A.; Sullivan, Blair D.

    2016-01-01

    This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating node probabilities, and these related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitates intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. Furthermore, to illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.

  18. GRACE, time-varying gravity, Earth system dynamics and climate change

    NASA Astrophysics Data System (ADS)

    Wouters, B.; Bonin, J. A.; Chambers, D. P.; Riva, R. E. M.; Sasgen, I.; Wahr, J.

    2014-11-01

    Continuous observations of temporal variations in the Earth's gravity field have recently become available at an unprecedented resolution of a few hundreds of kilometers. The gravity field is a product of the Earth's mass distribution, and these data—provided by the satellites of the Gravity Recovery And Climate Experiment (GRACE)—can be used to study the exchange of mass both within the Earth and at its surface. Since the launch of the mission in 2002, GRACE data has evolved from being an experimental measurement needing validation from ground truth, to a respected tool for Earth scientists representing a fixed bound on the total change and is now an important tool to help unravel the complex dynamics of the Earth system and climate change. In this review, we present the mission concept and its theoretical background, discuss the data and give an overview of the major advances GRACE has provided in Earth science, with a focus on hydrology, solid Earth sciences, glaciology and oceanography.

  19. A new framework and software to estimate time-varying reproduction numbers during epidemics.

    PubMed

    Cori, Anne; Ferguson, Neil M; Fraser, Christophe; Cauchemez, Simon

    2013-11-01

    The quantification of transmissibility during epidemics is essential to designing and adjusting public health responses. Transmissibility can be measured by the reproduction number R, the average number of secondary cases caused by an infected individual. Several methods have been proposed to estimate R over the course of an epidemic; however, they are usually difficult to implement for people without a strong background in statistical modeling. Here, we present a ready-to-use tool for estimating R from incidence time series, which is implemented in popular software including Microsoft Excel (Microsoft Corporation, Redmond, Washington). This tool produces novel, statistically robust analytical estimates of R and incorporates uncertainty in the distribution of the serial interval (the time between the onset of symptoms in a primary case and the onset of symptoms in secondary cases). We applied the method to 5 historical outbreaks; the resulting estimates of R are consistent with those presented in the literature. This tool should help epidemiologists quantify temporal changes in the transmission intensity of future epidemics by using surveillance data.

  20. Multiobjective resource-constrained project scheduling with a time-varying number of tasks.

    PubMed

    Abello, Manuel Blanco; Michalewicz, Zbigniew

    2014-01-01

    In resource-constrained project scheduling (RCPS) problems, ongoing tasks are restricted to utilizing a fixed number of resources. This paper investigates a dynamic version of the RCPS problem where the number of tasks varies in time. Our previous work investigated a technique called mapping of task IDs for centroid-based approach with random immigrants (McBAR) that was used to solve the dynamic problem. However, the solution-searching ability of McBAR was investigated over only a few instances of the dynamic problem. As a consequence, only a small number of characteristics of McBAR, under the dynamics of the RCPS problem, were found. Further, only a few techniques were compared to McBAR with respect to its solution-searching ability for solving the dynamic problem. In this paper, (a) the significance of the subalgorithms of McBAR is investigated by comparing McBAR to several other techniques; and (b) the scope of investigation in the previous work is extended. In particular, McBAR is compared to a technique called, Estimation Distribution Algorithm (EDA). As with McBAR, EDA is applied to solve the dynamic problem, an application that is unique in the literature.

  1. Delayed Instantiation Bulk Operations for Management of Distributed, Object-Based Storage Systems

    DTIC Science & Technology

    2009-08-01

    Salmon, R. R. Sambasivan, S. Sinnamohideen, J. D. Strunk , E. Thereska, M. Wachs, and J. J. Wylie. Ursa Minor: versatile cluster-based storage...1980. 9 [3] M. K. Aguilera, S. Spence, and A. Veitch. Olive : distributed point-in-time branching storage for real systems. Symposium on Networked

  2. Iterative solutions for one-dimensional diffusion with time varying surface composition and composition-dependent diffusion coefficient

    NASA Technical Reports Server (NTRS)

    Chow, M.; Houska, C. R.

    1980-01-01

    Solutions are given for one-dimensional diffusion problems with a time varying surface composition and also a composition dependent diffusion coefficient. The most general solution does not require special mathematical functions to fit the variation in surface composition or D(C). In another solution, a series expansion may be used to fit the time dependent surface concentration. These solutions make use of iterative calculations that converge rapidly and are highly stable. Computer times are much shorter than that required for finite difference calculations and can efficiently make use of interactive graphics terminals. Existing gas carburization data were used to provide an illustration of an iterative approach with a time varying carbon composition at the free surface.

  3. Proximal and time-varying effects of cigarette, alcohol, marijuana and other hard drug use on adolescent dating aggression.

    PubMed

    McNaughton Reyes, H Luz; Foshee, Vangie A; Bauer, Daniel J; Ennett, Susan T

    2014-04-01

    Although numerous studies have established a link between substance use and adult partner violence, little research has examined the relationship during adolescence and most extant research has not examined multiple substance use types. The current study used hierarchical growth modeling to simultaneously examine proximal (between-person) and time-varying (within-person) relations between cigarette, alcohol, marijuana and hard drug use and physical dating aggression across grades 8 through 12 while controlling for demographic covariates and shared risk factors. Proximal effects of marijuana use on dating aggression were found for girls and proximal effects of hard drug use on dating aggression were found for boys. Time-varying effects were found for alcohol for both boys and girls and for hard drug use for boys only. Overall, findings suggest that alcohol, marijuana and hard drug use predict whether and when adolescents engage in dating aggression and should be targeted by prevention interventions.

  4. Exposure to time varying magnetic fields associated with magnetic resonance imaging reduces fentanyl-induced analgesia in mice

    SciTech Connect

    Teskey, G.C.; Prato, F.S.; Ossenkopp, K.P.; Kavaliers, M.

    1988-01-01

    The effects of exposure to clinical magnetic resonance imaging (MRI) on analgesia induced by the mu opiate agonist, fentanyl, was examined in mice. During the dark period, adult male mice were exposed for 23.2 min to the time-varying (0.6 T/sec) magnetic field (TVMF) component of the MRI procedure. Following this exposure, the analgesic potency of fentanyl citrate (0.1 mg/kg) was determined at 5, 10, 15, and 30 min post-injection, using a thermal test stimulus (hot-plate 50 degrees C). Exposure to the magnetic-field gradients attenuated the fentanyl-induced analgesia in a manner comparable to that previously observed with morphine. These results indicate that the time-varying magnetic fields associated with MRI have significant inhibitory effects on the analgesic effects of specific mu-opiate-directed ligands.

  5. Inverse synthetic aperture radar imaging of maneuvering target based on cubic chirps model with time-varying amplitudes

    NASA Astrophysics Data System (ADS)

    Wang, Yong; Zhang, Qingxiang; Zhao, Bin

    2016-01-01

    Inverse synthetic aperture radar (ISAR) imaging of maneuvering target is a main topic in the field of radar signal processing, and the received signal in a range bin can usually be characterized as multicomponent cubic chirps with constant amplitudes after motion compensation. In fact, the phenomenon of migration through resolution cell (MTRC) often occurs for the target's complex motion, and this will induce the time-varying character for the amplitudes of cubic chirps. An algorithm for the parameters estimation of multicomponent cubic chirps with time-varying amplitudes based on the extension form of match Fourier transform is proposed, and by using it in ISAR imaging of maneuvering target, the quality of images can be improved significantly compared with the constant amplitudes model. Results of simulated and real data validate the effectiveness of the algorithm in this paper.

  6. Determination of time-varying contact length, friction force, torque and forces at the bearings in a helical gear system

    NASA Astrophysics Data System (ADS)

    Kar, Chinmaya; Mohanty, A. R.

    2008-01-01

    This paper deals with determining various time-varying parameters that are instrumental in introducing noise and vibration in a helical gear system. The most important parameter is the contact line variation, which subsequently induces friction force variation, frictional torque variation and variation in the forces at the bearings. The contact line variation will also give rise to gear mesh stiffness and damping variations. All these parameters are simulated for a defect-free and two defective cases of a helical gear system. The defective cases include one tooth missing and two teeth missing in the helical gear. The algorithm formulated in this paper is found to be simple and effective in determining the time-varying parameters.

  7. The relationship between intimate partner violence and PTSD: an application of Cox regression with time-varying covariates.

    PubMed

    Yoshihama, Mieko; Horrocks, Julie

    2003-08-01

    This study uses Cox regression with time-varying covariates to examine the relationship between intimate partner violence and posttraumatic stress disorder (PTSD) in a random sample of Japanese American women and immigrant women from Japan (N = 211). Because applications of survival analysis in trauma research are scarce, this paper presents the utility of this analytical approach by contrasting it with other common methods of analysis (chi-square tests and Cox regression with covariates that do not change over time).

  8. Harnessing bifurcations in tapping-mode atomic force microscopy to calibrate time-varying tip-sample force measurements.

    PubMed

    Sahin, Ozgur

    2007-10-01

    Torsional harmonic cantilevers allow measurement of time-varying tip-sample forces in tapping-mode atomic force microscopy. Accuracy of these force measurements is important for quantitative nanomechanical measurements. Here we demonstrate a method to convert the torsional deflection signals into a calibrated force wave form with the use of nonlinear dynamical response of the tapping cantilever. Specifically the transitions between steady oscillation regimes are used to calibrate the torsional deflection signals.

  9. High-Performance Consensus Control in Networked Systems With Limited Bandwidth Communication and Time-Varying Directed Topologies.

    PubMed

    Li, Huaqing; Chen, Guo; Huang, Tingwen; Dong, Zhaoyang

    2016-02-08

    Communication data rates and energy constraints are two important factors that have to be considered in the coordination control of multiagent networks. Although some encoder-decoder-based consensus protocols are available, there still exists a fundamental theoretical problem: how can we further reduce the update rate of control input for each agent without the changing consensus performance? In this paper, we consider the problem of average consensus over directed and time-varying digital networks of discrete-time first-order multiagent systems with limited communication data transmission rates. Each agent has a real-valued state but can only exchange binary symbolic sequence with its neighbors due to bandwidth constraints. A class of novel event-triggered dynamic encoding and decoding algorithms is proposed, based on which a kind of consensus protocol is presented. Moreover, we develop a scheme to select the numbers of time-varying quantization levels for each connected communication channel in the time-varying directed topologies at each time step. The analytical relation among system and network parameters is characterized explicitly. It is shown that the asymptotic convergence rate is related to the scale of the network, the number of quantization levels, the system parameter, and the network structure. It is also found that under the designed event-triggered protocol, for a directed and time-varying digital network, which uniformly contains a spanning tree over a time interval, the average consensus can be achieved with an exponential convergence rate based on merely 1-b information exchange between each pair of adjacent agents at each time step.

  10. Dependence of the neutron monitor count rate and time delay distribution on the rigidity spectrum of primary cosmic rays

    NASA Astrophysics Data System (ADS)

    Mangeard, P.-S.; Ruffolo, D.; Sáiz, A.; Nuntiyakul, W.; Bieber, J. W.; Clem, J.; Evenson, P.; Pyle, R.; Duldig, M. L.; Humble, J. E.

    2016-12-01

    Neutron monitors are the premier instruments for precisely tracking time variations in the Galactic cosmic ray flux at GeV-range energies above the geomagnetic cutoff at the location of measurement. Recently, a new capability has been developed to record and analyze the neutron time delay distribution (related to neutron multiplicity) to infer variations in the cosmic ray spectrum as well. In particular, from time delay histograms we can determine the leader fraction L, defined as the fraction of neutrons that did not follow a previous neutron detection in the same tube from the same atmospheric secondary particle. Using data taken during 2000-2007 by a shipborne neutron monitor latitude survey, we observe a strong dependence of the count rate and L on the geomagnetic cutoff. We have modeled this dependence using Monte Carlo simulations of cosmic ray interactions in the atmosphere and in the neutron monitor. We present new yield functions for the count rate of a neutron monitor at sea level. The simulation results show a variation of L with geomagnetic cutoff as observed by the latitude survey, confirming that these changes in L can be attributed to changes in the cosmic ray spectrum arriving at Earth's atmosphere. We also observe a variation in L with time at a fixed cutoff, which reflects the evolution of the cosmic ray spectrum with the sunspot cycle, known as solar modulation.

  11. Exact model reduction with delays: closed-form distributions and extensions to fully bi-directional monomolecular reactions.

    PubMed

    Leier, Andre; Barrio, Manuel; Marquez-Lago, Tatiana T

    2014-06-06

    In order to systematically understand the qualitative and quantitative behaviour of chemical reaction networks, scientists must derive and analyse associated mathematical models. However, biochemical systems are often very large, with reactions occurring at multiple time scales, as evidenced by signalling pathways and gene expression kinetics. Owing to the associated computational costs, it is then many times impractical, if not impossible, to solve or simulate these systems with an appropriate level of detail. By consequence, there is a growing interest in developing techniques for the simplification or reduction of complex biochemical systems. Here, we extend our recently presented methodology on exact reduction of linear chains of reactions with delay distributions in two ways. First, we report that it is now possible to deal with fully bi-directional monomolecular systems, including degradations, synthesis and generalized bypass reactions. Second, we provide all derivations of associated delays in analytical, closed form. Both advances have a major impact on further reducing computational costs, while still retaining full accuracy. Thus, we expect our new methodology to respond to current simulation needs in pharmaceutical, chemical and biological research.

  12. Exploratory time varying lagged regression: modeling association of cognitive and functional trajectories with expected clinic visits in older adults

    PubMed Central

    Şentürk, Damla; Ghosh, Samiran; Nguyen, Danh V.

    2014-01-01

    Motivated by a longitudinal study on factors affecting the frequency of clinic visits of older adults, an exploratory time varying lagged regression analysis is proposed to relate a longitudinal response to multiple cross-sectional and longitudinal predictors from time varying lags. Regression relations are allowed to vary with time through smooth varying coefficient functions. The main goal of the proposal is to detect deviations from a concurrent varying coefficient model potentially in a subset of the longitudinal predictors with nonzero estimated lags. The proposed methodology is geared towards irregular and infrequent data where different longitudinal variables may be observed at different frequencies, possibly at unsynchronized time points and contaminated with additive measurement error. Furthermore, to cope with the curse of dimensionality which limits related current modeling approaches, a sequential model building procedure is proposed to explore and select the time varying lags of the longitudinal predictors. The estimation procedure is based on estimation of the moments of the predictor and response trajectories by pooling information from all subjects. The finite sample properties of the proposed estimation algorithm are studied under various lag structures and correlation levels among the predictor processes in simulation studies. Application to the clinic visits data show the effect of cognitive and functional impairment scores from varying lags on the frequency of the clinic visits throughout the study. PMID:24436504

  13. Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets.

    PubMed

    Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze

    2017-01-01

    This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor's 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model.

  14. Effect of sliding friction on the dynamics of spur gear pair with realistic time-varying stiffness

    NASA Astrophysics Data System (ADS)

    He, Song; Gunda, Rajendra; Singh, Rajendra

    2007-04-01

    The chief objective of this article is to propose a new method of incorporating the sliding friction and realistic time-varying stiffness into an analytical (multi-degree-of-freedom) spur gear model and to evaluate their effects. An accurate finite element/contact mechanics analysis code is employed, in the "static" mode, to compute the mesh stiffness at every time instant under a range of loading conditions. Here, the time-varying stiffness is calculated as an effective function which may also include the effect of profile modifications. The realistic mesh stiffness is then incorporated into the linear time-varying spur gear model with the contributions of sliding friction. Proposed methods are illustrated via two spur gear examples and validated by using the finite element in the "dynamic" mode as experimental results. A key question whether the sliding friction is indeed the source of the off-line-of-action forces and motions is then answered by our analytical model. Finally, the effect of the profile modification on the dynamic transmission error has been analytically examined under the influence of sliding friction. For instance, the linear tip relief introduces an amplification in the off-line-of-action forces and motions due to an out of phase relationship between the normal load and friction forces.

  15. Delayed voluntary exercise does not enhance cognitive performance after hippocampal injury: an investigation of differentially distributed exercise protocols

    PubMed Central

    Wogensen, Elise; Gram, Marie Gajhede; Sommer, Jens Bak; Vilsen, Christina Rytter; Mogensen, Jesper; Malá, Hana

    2016-01-01

    Voluntary exercise has previously been shown to enhance cognitive recovery after acquired brain injury (ABI). The present study evaluated effects of two differentially distributed protocols of delayed, voluntary exercise on cognitive recovery using an allocentric place learning task in an 8-arm radial maze. Fifty-four Wistar rats were subjected to either bilateral transection of the fimbria-fornix (FF) or to sham surgery. Twenty-one days postinjury, the animals started exercising in running wheels either for 14 consecutive days (FF/exercise daily [ExD], sham/ExD) or every other day for 14 days (FF/exercise every second day [ExS], sham/ExS). Additional groups were given no exercise treatment (FF/not exercise [NE], sham/NE). Regardless of how exercise was distributed, we found no cognitively enhancing effects of exercise in the brain injured animals. Design and protocol factors possibly affecting the efficacy of post-ABI exercise are discussed. PMID:27807517

  16. Applications of the Time-Varying Multi-Hazard Index to Armed Conflicts and GDP Growth Rate

    NASA Astrophysics Data System (ADS)

    Isanuk, M.; Skorik, A.; Lerner-Lam, A.

    2004-12-01

    The time-varying Multi-Hazard Index has many potential applications for comparisons against quantitative measures of sustainable development. We have compared the time-varying severity of multiple natural hazards against time-varying socio-economic data for selected countries. Our analysis compares Gross Domestic Product (GDP) growth and armed conflict occurrence against multiple hazard severity as measured by an empirical time-varying multiple hazard index. The purpose of these analyses is to establish and characterize correlations between the Multi-Hazard Index and trends in GDP and conflicts over the past 25 years. To analyze the relationship between natural hazards and armed conflicts, the Multi-Hazard Index was correlated against the number of conflicts at each intensity level for individual countries. A preliminary analysis was performed studying the apparent relationship as well as the possible existence of time lags. In a similar although more quantitative analysis, the GDP data was correlated against the Multi-Hazard Index for a particular country at different time lags. Analysis involving the conflict datasets yielded varying results from country to country. Colombia shows the strongest correlation, with all positive values of the Multi-Hazard Index followed by an escalation in conflict intensity. The results for other countries are more difficult to interpret as certain years show increases in the number of conflicts at one intensity level and a decrease for other intensity levels. Some issues that need to be addressed include the coding of the intensity for the conflict data, the dating for both conflicts and hazards, and the use of national boundaries as geographic extents. The degree of correlation between GDP growth and the Multi-Hazard Index varies from country to country as well. Our calculations for Honduras show an extremely high correlation, for example, implying a strong economic sensitivity to natural hazards, whereas for China no significant

  17. A review of methodological factors in performance assessments of time-varying aircraft noise effects. [with annotated bibliography

    NASA Technical Reports Server (NTRS)

    Coates, G. D.; Alluisi, E. A.; Adkins, C. J., Jr.

    1977-01-01

    Literature on the effects of general noise on human performance is reviewed in an attempt to identify (1) those characteristics of noise that have been found to affect human performance; (2) those characteristics of performance most likely to be affected by the presence of noise, and (3) those characteristics of the performance situation typically associated with noise effects. Based on the characteristics identified, a theoretical framework is proposed that will permit predictions of possible effects of time-varying aircraft-type noise on complex human performance. An annotated bibliography of 50 articles is included.

  18. Time-varying gyrocompass alignment for fiber-optic-gyro inertial navigation system with large misalignment angle

    NASA Astrophysics Data System (ADS)

    Ben, Yueyang; Li, Qian; Zhang, Yi; Huo, Liang

    2014-09-01

    Conventional strapdown gyrocompass alignment methods are based on the assumption that the fiber-optic-gyro inertial navigation system has a small azimuth misalignment angle. A large azimuth misalignment angle would lead to an extension of the alignment duration. A time-varying gyrocompass alignment method to solve this problem is provided. An appropriate parameter setting is given for the gyrocompass alignment with a large misalignment angle. Also, a proper protocol for a parametric switch is derived. Simulation and trail results show that the proposed method has better alignment performance than conventional ones, as the system has large misalignment angles.

  19. Multi-state time-varying reliability evaluation of smart grid with flexible demand resources utilizing Lz transform

    NASA Astrophysics Data System (ADS)

    Jia, Heping; Jin, Wende; Ding, Yi; Song, Yonghua; Yu, Dezhao

    2017-01-01

    With the expanding proportion of renewable energy generation and development of smart grid technologies, flexible demand resources (FDRs) have been utilized as an approach to accommodating renewable energies. However, multiple uncertainties of FDRs may influence reliable and secure operation of smart grid. Multi-state reliability models for a single FDR and aggregating FDRs have been proposed in this paper with regard to responsive abilities for FDRs and random failures for both FDR devices and information system. The proposed reliability evaluation technique is based on Lz transform method which can formulate time-varying reliability indices. A modified IEEE-RTS has been utilized as an illustration of the proposed technique.

  20. Estimating a scale-change effect for time-varying phenotypes in genome-wide association studies

    PubMed Central

    Chen, Ying Qing; Zhang, Xinyi; Zhao, Lue-Ping

    2012-01-01

    Summary The Cox proportional hazards model has been used widely in genome-wide association (GWA) studies of censored time-varying phenotypes to investigate disease association expressed by the relative hazards. In this paper, we instead apply the so-called accelerated hazards model to explore a novel time scale-change genotypic association, which is not necessarily able to be identified by the traditional Cox models. Our application is motivated and demonstrated by a GWA study of hematopoietic stem cell transplantation cohort.

  1. Full-field tracking and measuring of particle motion in capillary vessels by using time-varying laser speckle

    NASA Astrophysics Data System (ADS)

    Zhang, Luying; Wang, Bo; Wang, Yi

    2016-03-01

    We propose a random perturbation model to describe the variation of laser speckle patterns caused by moving particles in capillary vessels. When passing through probing volume, moving particles encode random perturbations into observed laser speckle patterns. We extract the perturbation envelopes of time-varying laser speckles for tracking the motion of single particle. And, the full-field transverse velocities of flowing particles are obtained by using cross-correlation between the perturbation envelopes. The proposed method is experimentally verified by the use of polymer-microsphere suspension in a glass capillary.

  2. Robust sensor fault detection and isolation of gas turbine engines subjected to time-varying parameter uncertainties

    NASA Astrophysics Data System (ADS)

    Pourbabaee, Bahareh; Meskin, Nader; Khorasani, Khashayar

    2016-08-01

    In this paper, a novel robust sensor fault detection and isolation (FDI) strategy using the multiple model-based (MM) approach is proposed that remains robust with respect to both time-varying parameter uncertainties and process and measurement noise in all the channels. The scheme is composed of robust Kalman filters (RKF) that are constructed for multiple piecewise linear (PWL) models that are constructed at various operating points of an uncertain nonlinear system. The parameter uncertainty is modeled by using a time-varying norm bounded admissible structure that affects all the PWL state space matrices. The robust Kalman filter gain matrices are designed by solving two algebraic Riccati equations (AREs) that are expressed as two linear matrix inequality (LMI) feasibility conditions. The proposed multiple RKF-based FDI scheme is simulated for a single spool gas turbine engine to diagnose various sensor faults despite the presence of parameter uncertainties, process and measurement noise. Our comparative studies confirm the superiority of our proposed FDI method when compared to the methods that are available in the literature.

  3. The uncertain role of diversity dependence in species diversification and the need to incorporate time-varying carrying capacities

    PubMed Central

    Marshall, Charles R.; Quental, Tiago B.

    2016-01-01

    There is no agreement among palaeobiologists or biologists as to whether, or to what extent, there are limits on diversification and species numbers. Here, we posit that part of the disagreement stems from: (i) the lack of explicit criteria for defining the relevant species pools, which may be defined phylogenetically, ecologically or geographically; (ii) assumptions that must be made when extrapolating from population-level logistic growth to macro-evolutionary diversification; and (iii) too much emphasis being placed on fixed carrying capacities, rather than taking into account the opportunities for increased species richness on evolutionary timescales, for example, owing to increased biologically available energy, increased habitat complexity and the ability of many clades to better extract resources from the environment, or to broaden their resource base. Thus, we argue that a more effective way of assessing the evidence for and against the ideas of bound versus unbound diversification is through appropriate definition of the relevant species pools, and through explicit modelling of diversity-dependent diversification with time-varying carrying capacities. Here, we show that time-varying carrying capacities, either increases or decreases, can be accommodated through changing intrinsic diversification rates (diversity-independent effects), or changing the effects of crowding (diversity-dependent effects). PMID:26977059

  4. Flocking for multi-agent systems with unknown nonlinear time-varying uncertainties under a fixed undirected graph

    NASA Astrophysics Data System (ADS)

    Luo, Jie; Cao, Chengyu

    2015-05-01

    This paper presents a flocking algorithm for networked multi-agent systems with unknown, nonlinear, time-varying uncertainties by integrating cooperative control and ? adaptive control methods. An ideal multi-agent system without uncertainties is introduced first. The cooperative control law, based on an artificial potential function, is designed to make the ideal multi-agent system achieve flocking under a fixed and connected undirected graph. Information of ideal states, instead of real states, is exchanged among agents through a communication network. The presence of uncertainties will lead to the degeneration of the performance or even destabilize the entire multi-agent system. The ? adaptive control law is therefore introduced to handle unknown, nonlinear, time-varying uncertainties. By integrating the cooperative control law with the adaptive control law, the real multi-agent system stays close to the ideal multi-agent system which achieves flocking asymptotically under a connected graph. Simulation results of two-dimensional flocking with uncertainties are provided to demonstrate the presented flocking algorithm.

  5. Event-Based H∞ State Estimation for Time-Varying Stochastic Dynamical Networks With State- and Disturbance-Dependent Noises.

    PubMed

    Sheng, Li; Wang, Zidong; Zou, Lei; Alsaadi, Fuad E

    2016-07-20

    In this paper, the event-based finite-horizon H∞ state estimation problem is investigated for a class of discrete time-varying stochastic dynamical networks with state- and disturbance-dependent noises [also called (x,v)-dependent noises]. An event-triggered scheme is proposed to decrease the frequency of the data transmission between the sensors and the estimator, where the signal is transmitted only when certain conditions are satisfied. The purpose of the problem addressed is to design a time-varying state estimator in order to estimate the network states through available output measurements. By employing the completing-the-square technique and the stochastic analysis approach, sufficient conditions are established to ensure that the error dynamics of the state estimation satisfies a prescribed H∞ performance constraint over a finite horizon. The desired estimator parameters can be designed via solving coupled backward recursive Riccati difference equations. Finally, a numerical example is exploited to demonstrate the effectiveness of the developed state estimation scheme.

  6. Steady-state response of a geared rotor system with slant cracked shaft and time-varying mesh stiffness

    NASA Astrophysics Data System (ADS)

    Han, Qinkai; Zhao, Jingshan; Lu, Wenxiu; Peng, Zhike; Chu, Fulei

    2014-04-01

    The dynamic behavior of geared rotor system with defects is helpful for the failure diagnosis and state detecting of the system. Extensive efforts have been devoted to study the dynamic behaviors of geared systems with tooth root cracks. When surface cracks (especially for slant cracks) appear on the transmission shaft, the dynamic characteristics of the system have not gained sufficient attentions. Due to the parametric excitations induced by slant crack breathing and time-varying mesh stiffness, the steady-state response of the cracked geared rotor system differs distinctly from that of the uncracked system. Thus, utilizing the direct spectral method (DSM), the forced response spectra of a geared rotor system with slant cracked shaft and time-varying mesh stiffness under transmission error, unbalance force and torsional excitations are, respectively, obtained and discussed in detail. The effects of crack types (straight or slant crack) and crack depth on the forced response spectra of the system without and with torsional excitation are considered in the analysis. In addition, how the frequency response characteristics change after considering the crack is also investigated. It is shown that the torsional excitations have significant influence on the forced response spectra of slant cracked system. Sub-critical resonances are also found in the frequency response curves. The results could be used for shaft crack detection in geared rotor system.

  7. The uncertain role of diversity dependence in species diversification and the need to incorporate time-varying carrying capacities.

    PubMed

    Marshall, Charles R; Quental, Tiago B

    2016-04-05

    There is no agreement among palaeobiologists or biologists as to whether, or to what extent, there are limits on diversification and species numbers. Here, we posit that part of the disagreement stems from: (i) the lack of explicit criteria for defining the relevant species pools, which may be defined phylogenetically, ecologically or geographically; (ii) assumptions that must be made when extrapolating from population-level logistic growth to macro-evolutionary diversification; and (iii) too much emphasis being placed on fixed carrying capacities, rather than taking into account the opportunities for increased species richness on evolutionary timescales, for example, owing to increased biologically available energy, increased habitat complexity and the ability of many clades to better extract resources from the environment, or to broaden their resource base. Thus, we argue that a more effective way of assessing the evidence for and against the ideas of bound versus unbound diversification is through appropriate definition of the relevant species pools, and through explicit modelling of diversity-dependent diversification with time-varying carrying capacities. Here, we show that time-varying carrying capacities, either increases or decreases, can be accommodated through changing intrinsic diversification rates (diversity-independent effects), or changing the effects of crowding (diversity-dependent effects).

  8. Disaggregating the Distal, Proximal, and Time-Varying Effects of Parent Alcoholism on Children’s Internalizing Symptoms

    PubMed Central

    Hussong, Andrea M.; Cai, Li; Curran, Patrick J.; Flora, David B.; Chassin, Laurie; Zucker, Robert A.

    2009-01-01

    We tested whether children show greater internalizing symptoms when their parents are actively abusing alcohol. In an integrative data analysis, we combined observations over ages 2 through 17 from two longitudinal studies of children of alcoholic parents and matched controls recruited from the community. Using a mixed modeling approach, we tested whether children showed elevated mother- and child-reported internalizing symptoms (a) at the same time that parents showed alcohol-related consequences (time-varying effects), (b) if parents showed greater alcohol-related consequences during the study period (proximal effects), and (c) if parents had a lifetime diagnosis of alcoholism that predated the study period (distal effects). No support for time-varying effects was found; proximal effects of mothers’ alcohol-related consequences on child-reported internalizing symptoms were found and distal effects of mother and father alcoholism predicted greater internalizing symptoms among COAs. Implications for the time-embedded relations between parent alcoholism and children’s internalizing symptoms are discussed. PMID:17891557

  9. Moving Kriging shape function modeling of vector TARMA models for modal identification of linear time-varying structural systems

    NASA Astrophysics Data System (ADS)

    Yang, Wu; Liu, Li; Zhou, Si-Da; Ma, Zhi-Sai

    2015-10-01

    This work proposes a Moving Kriging (MK) shape function modeling method for modal identification of linear time-varying (LTV) structural systems based on vector time-dependent autoregressive moving average (VTARMA) models. It aims to avoid the functional subspaces selection of the conventional functional series VTARMA (FS-VTARMA) models. Instead of the common basis functions, it constructs the time-varying coefficients on the time nodes with the MK shape functions in a compact support domain. The merit of the MK shape function is to determine its shape parameters upon vector random vibration signals adaptively. Model identification is effectively dealt with through an optimization scheme that decomposes the identification problem into two subproblems: estimating model parameters via two-stage least squares (2SLS) method and estimating shape function parameters via a discrete-continuous-variable hybrid optimization. In addition, the model order selection is achieved by the optimization scheme. This method has been validated by a Monte Carlo study of simulation case and further by an experimental test case, and the performance and potential advantages are illustrated.

  10. Study on electromagnetic scattering from the time-varying lossy dielectric ocean and a moving conducting plate above it.

    PubMed

    Wang, R; Guo, L-X

    2009-03-01

    The problem of electromagnetic (EM) scattering between the time-varying lossy dielectric ocean and a moving target is always solved by using some numerical algorithm. However, the elements of the impedance matrix and the surface electric and magnetic currents of the lossy dielectric ocean must be determined and evaluated again at different moments due to the varying of the ocean with time, and the numerical algorithm will produce an enormous amount of calculation. To overcome this shortcoming, the reciprocity theorem is used to solve the coupling field between a time-varying lossy dielectric ocean and a moving conducting plate above it. Due to the advantage of the reciprocity theorem, the difficulty in computing the secondary scattered fields is reduced. The polarization currents of the ocean and the first scattered field from the conducting plate are both evaluated by using the physical optics (PO) method. The backscattered field from the ocean is evaluated by using the Kirchhoff approximation (KA) method. The characteristics of the coupling backscattered field and the Doppler spectrum are analyzed in detail for different incident conditions.

  11. Comparison of procedures to assess non-linear and time-varying effects in multivariable models for survival data.

    PubMed

    Buchholz, Anika; Sauerbrei, Willi

    2011-03-01

    The focus of many medical applications is to model the impact of several factors on time to an event. A standard approach for such analyses is the Cox proportional hazards model. It assumes that the factors act linearly on the log hazard function (linearity assumption) and that their effects are constant over time (proportional hazards (PH) assumption). Variable selection is often required to specify a more parsimonious model aiming to include only variables with an influence on the outcome. As follow-up increases the effect of a variable often gets weaker, which means that it varies in time. However, spurious time-varying effects may also be introduced by mismodelling other parts of the multivariable model, such as omission of an important covariate or an incorrect functional form of a continuous covariate. These issues interact. To check whether the effect of a variable varies in time several tests for non-PH have been proposed. However, they are not sufficient to derive a model, as appropriate modelling of the shape of time-varying effects is required. In three examples we will compare five recently published strategies to assess whether and how the effects of covariates from a multivariable model vary in time. For practical use we will give some recommendations.

  12. Distribution of blood derivatives by registered blood establishments that qualify as health care entities; Prescription Drug Marketing Act of 1987; Prescription Drug Amendments of 1992; delay of applicability date. Final rule; delay of applicability date.

    PubMed

    2006-11-13

    The Food and Drug Administration (FDA) is further delaying, until December 1, 2008, the applicability date of a certain requirement of a final rule published in the Federal Register of December 3, 1999 (64 FR 67720) (the final rule). The final rule implements the Prescription Drug Marketing Act of 1987 (PDMA), as modified by the Prescription Drug Amendments of 1992 (PDA), and the Food and Drug Administration Modernization Act of 1997 (the Modernization Act). The provisions of the final rule became effective on December 4, 2000, except for certain provisions whose effective or applicability dates were delayed in five subsequent Federal Register notices, until December 1, 2006. The provision with the delayed applicability date would prohibit wholesale distribution of blood derivatives by registered blood establishments that meet the definition of a "health care entity." In the Federal Register of February 1, 2006 (71 FR 5200), FDA published a proposed rule specific to the distribution of blood derivatives by registered blood establishments that qualify as health care entities (the proposed rule). The proposed rule would amend certain limited provisions of the final rule to allow certain registered blood establishments that qualify as health care entities to distribute blood derivatives. In response to the proposed rule, FDA received substantive comments. As explained in the SUPPLEMENTARY INFORMATION section of this document, further delaying the applicability of Sec. 203.3(q) (21 CFR 203.3(q)) to the wholesale distribution of blood derivatives by health care entities is necessary to give the agency additional time to address comments on the proposed rule, consider whether regulatory changes are appropriate, and, if so, to initiate such changes.

  13. THE SUPERNOVA DELAY TIME DISTRIBUTION IN GALAXY CLUSTERS AND IMPLICATIONS FOR TYPE-Ia PROGENITORS AND METAL ENRICHMENT

    SciTech Connect

    Maoz, Dan; Sharon, Keren; Avishay Gal-Yam

    2010-10-20

    Knowledge of the supernova (SN) delay time distribution (DTD)-the SN rate versus time that would follow a hypothetical brief burst of star formation-can shed light on SN progenitors and physics, as well as on the timescales of chemical enrichment in different environments. We compile recent measurements of the Type-Ia SN (SN Ia) rate in galaxy clusters at redshifts from z = 0 out to z = 1.45, just 2 Gyr after cluster star formation at z {approx} 3. We review the plausible range for the observed total iron-to-stellar mass ratio in clusters, based on the latest data and analyses, and use it to constrain the time-integrated number of SN Ia events in clusters. With these data, we recover the DTD of SNe Ia in cluster environments. The DTD is sharply peaked at the shortest time-delay interval we probe, 0Gyr < t < 2.2 Gyr, with a low tail out to delays of {approx}10 Gyr, and is remarkably consistent with several recent DTD reconstructions based on different methods, applied to different environments. We test DTD models from the literature, requiring that they simultaneously reproduce the observed cluster SN rates and the observed iron-to-stellar mass ratios. A parameterized power-law DTD of the form t {sup -1.2{+-}0.3} from t = 400 Myr to a Hubble time can satisfy both constraints. Shallower power laws such as t {sup -1/2} cannot, assuming a single DTD, and a single star formation burst (either brief or extended) at high z. This implies that 50%-85% of SNe Ia explode within 1 Gyr of star formation. DTDs from double-degenerate (DD) models, which generically have {approx}t {sup -1} shapes over a wide range of timescales, match the data, but only if their predictions are scaled up by factors of 5-10. Single-degenerate (SD) DTDs always give poor fits to the data, due to a lack of delayed SNe and overall low numbers of SNe. The observations can also be reproduced with a combination of two SN Ia populations-a prompt SD population of SNe Ia that explodes within a few Gyr of star

  14. A discrete time-varying internal model-based approach for high precision tracking of a multi-axis servo gantry.

    PubMed

    Zhang, Zhen; Yan, Peng; Jiang, Huan; Ye, Peiqing

    2014-09-01

    In this paper, we consider the discrete time-varying internal model-based control design for high precision tracking of complicated reference trajectories generated by time-varying systems. Based on a novel parallel time-varying internal model structure, asymptotic tracking conditions for the design of internal model units are developed, and a low order robust time-varying stabilizer is further synthesized. In a discrete time setting, the high precision tracking control architecture is deployed on a Voice Coil Motor (VCM) actuated servo gantry system, where numerical simulations and real time experimental results are provided, achieving the tracking errors around 3.5‰ for frequency-varying signals.

  15. Isosurface extraction and view-dependent filtering from time-varying fields using Persistent Time-Octree (PTOT).

    PubMed

    Wang, Cong; Chiang, Yi-Jen

    2009-01-01

    We develop a new algorithm for isosurface extraction and view-dependent filtering from large time-varying fields, by using a novel Persistent Time-Octree (PTOT) indexing structure. Previously, the Persistent Octree (POT) was proposed to perform isosurface extraction and view-dependent filtering, which combines the advantages of the interval tree (for optimal searches of active cells) and of the Branch-On-Need Octree (BONO, forview-dependent filtering), but it only works for steady-state(i.e., single time step) data. For time-varying fields, a 4D version of POT, 4D-POT, was proposed for 4D isocontour slicing, where slicing on the time domain gives all active cells in the queried timestep and isovalue. However, such slicing is not output sensitive and thus the searching is sub-optimal. Moreover, it was not known how to support view-dependent filtering in addition to time-domain slicing.In this paper, we develop a novel Persistent Time-Octree (PTOT) indexing structure, which has the advantages of POT and performs 4D isocontour slicing on the time domain with an output-sensitive and optimal searching. In addition, when we query the same isovalue q over m consecutive time steps, there is no additional searching overhead (except for reporting the additionalactive cells) compared to querying just the first time step. Such searching performance for finding active cells is asymptotically optimal, with asymptotically optimal space and preprocessing time as well. Moreover, our PTOT supports view-dependent filtering in addition to time-domain slicing. We propose a simple and effective out-of-core scheme, where we integrate our PTOT with implicit occluders, batched occlusion queries and batched CUDA computing tasks, so that we can greatly reduce the I/O cost as well as increase the amount of data being concurrently computed in GPU.This results in an efficient algorithm for isosurface extraction with view-dependent filtering utilizing a state-of-the-art programmable GPUfor time-varying

  16. Visualizing time: how linguistic metaphors are incorporated into displaying instruments in the process of interpreting time-varying signals

    NASA Astrophysics Data System (ADS)

    Garcia-Belmonte, Germà

    2016-04-01

    Spatial visualization is a well-established topic of education research that has allowed improving science and engineering students' skills on spatial relations. Connections have been established between visualization as a comprehension tool and instruction in several scientific fields. Learning about dynamic processes mainly relies upon static spatial representations or images. Visualization of time is inherently problematic because time can be conceptualized in terms of two opposite conceptual metaphors based on spatial relations as inferred from conventional linguistic patterns. The situation is particularly demanding when time-varying signals are recorded using displaying electronic instruments, and the image should be properly interpreted. This work deals with the interplay between linguistic metaphors, visual thinking and scientific instrument mediation in the process of interpreting time-varying signals displayed by electronic instruments. The analysis draws on a simplified version of a communication system as example of practical signal recording and image visualization in a physics and engineering laboratory experience. Instrumentation delivers meaningful signal representations because it is designed to incorporate a specific and culturally favored time view. It is suggested that difficulties in interpreting time-varying signals are linked with the existing dual perception of conflicting time metaphors. The activation of specific space-time conceptual mapping might allow for a proper signal interpretation. Instruments play then a central role as visualization mediators by yielding an image that matches specific perception abilities and practical purposes. Here I have identified two ways of understanding time as used in different trajectories through which students are located. Interestingly specific displaying instruments belonging to different cultural traditions incorporate contrasting time views. One of them sees time in terms of a dynamic metaphor

  17. Time delay occultation data of the Helios spacecraft for probing the electron density distribution in the solar corona

    NASA Technical Reports Server (NTRS)

    Edenhofer, P.; Lueneburg, E.; Esposito, P. B.; Martin, W. L.; Zygielbaum, A. I.; Hansen, R. T.; Hansen, S. F.

    1978-01-01

    S-band time delay measurements were collected from the spacecraft Helios A and B during three solar occultations in 1975/76 within heliocentric distances of about 3 and 215 earth radius in terms of range, Doppler frequency shift, and electron content. Characteristic features of measurement and data processing are described. Typical data sets are discussed to probe the electron density distribution near the sun (west and east limb as well) including the outer and extended corona. Steady-state and dynamical aspects of the solar corona are presented and compared with earth-bound-K-coronagraph measurements. Using a weighted least squares estimation, parameters of an average coronal electron density profile are derived in a preliminary analysis to yield electron densities at r = 3, 65, 215 earth radius. Transient phenomena are discussed and a velocity of propagation v is nearly equal to 900 km/s is determined for plasma ejecta from a solar flare observed during an extraordinary set of Helios B electron content measurements.

  18. Periodicity and global exponential stability of generalized Cohen-Grossberg neural networks with discontinuous activations and mixed delays.

    PubMed

    Wang, Dongshu; Huang, Lihong

    2014-03-01

    In this paper, we investigate the periodic dynamical behaviors for a class of general Cohen-Grossberg neural networks with discontinuous right-hand sides, time-varying and distributed delays. By means of retarded differential inclusions theory and the fixed point theorem of multi-valued maps, the existence of periodic solutions for the neural networks is obtained. After that, we derive some sufficient conditions for the global exponential stability and convergence of the neural networks, in terms of nonsmooth analysis theory with generalized Lyapunov approach. Without assuming the boundedness (or the growth condition) and monotonicity of the discontinuous neuron activation functions, our results will also be valid. Moreover, our results extend previous works not only on discrete time-varying and distributed delayed neural networks with continuous or even Lipschitz continuous activations, but also on discrete time-varying and distributed delayed neural networks with discontinuous activations. We give some numerical examples to show the applicability and effectiveness of our main results.

  19. Motivating Action and Maintaining Change: The Time-Varying Role of Homework Following a Brief Couples' Intervention.

    PubMed

    Hawrilenko, Matt; Eubanks Fleming, C J; Goldstein, Alana S; Cordova, James V

    2016-07-01

    Studies regarding the effectiveness of homework assignments in cognitive-behavioral treatments have demonstrated mixed results. This study investigated predictors of compliance with homework recommendations and the time-varying relationship of recommendation completion with treatment response in a brief couples' intervention (N = 108). More satisfied couples and couples with more motivation to change completed more recommendations, whereas couples with children completed fewer. The association between recommendation completion and treatment response varied with the passage of time, with the strongest effect observed 6 months after the intervention, but no discernible differences at 1 year postintervention. Couples that completed more recommendations experienced more rapid treatment gains, but even those couples doing substantially fewer recommendations ultimately realized equivalent treatment effects, although they progressed more slowly. Implications are discussed.

  20. Regime Switching Modeling of Substance Use: Time-Varying and Second-Order Markov Models and Individual Probability Plots

    PubMed Central

    Neale, Michael C.; Clark, Shaunna L.; Dolan, Conor V.; Hunter, Michael D.

    2015-01-01

    A linear latent growth curve mixture model with regime switching is extended in 2 ways. Previously, the matrix of first-order Markov switching probabilities was specified to be time-invariant, regardless of the pair of occasions being considered. The first extension, time-varying transitions, specifies different Markov transition matrices between each pair of occasions. The second extension is second-order time-invariant Markov transition probabilities, such that the probability of switching depends on the states at the 2 previous occasions. The models are implemented using the R package OpenMx, which facilitates data handling, parallel computation, and further model development. It also enables the extraction and display of relative likelihoods for every individual in the sample. The models are illustrated with previously published data on alcohol use observed on 4 occasions as part of the National Longitudinal Survey of Youth, and demonstrate improved fit to the data. PMID:26924921