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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. Stability analysis of Markovian jumping stochastic Cohen—Grossberg neural networks with discrete and distributed time varying delays

    NASA Astrophysics Data System (ADS)

    M. Syed, Ali

    2014-06-01

    In this paper, the global asymptotic stability problem of Markovian jumping stochastic Cohen—Grossberg neural networks with discrete and distributed time-varying delays (MJSCGNNs) is considered. A novel LMI-based stability criterion is obtained by constructing a new Lyapunov functional to guarantee the asymptotic stability of MJSCGNNs. Our results can be easily verified and they are also less restrictive than previously known criteria and can be applied to Cohen—Grossberg neural networks, recurrent neural networks, and cellular neural networks. Finally, the proposed stability conditions are demonstrated with numerical examples.

  3. 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.

  4. New stability conditions for nonlinear time varying delay systems

    NASA Astrophysics Data System (ADS)

    Elmadssia, S.; Saadaoui, K.; Benrejeb, M.

    2016-07-01

    In this paper, new practical stability conditions for a class of nonlinear time varying delay systems are proposed. The study is based on the use of a specific state space description, known as the Benrejeb characteristic arrow form matrix, and aggregation techniques to obtain delay-dependent stability conditions. Application of this method to delayed Lurie-Postnikov nonlinear systems is given. Illustrative examples are presented to show the effectiveness of the proposed approach.

  5. Interval estimation for uncertain systems with time-varying delays

    NASA Astrophysics Data System (ADS)

    Efimov, Denis; Perruquetti, Wilfrid; Richard, Jean-Pierre

    2013-10-01

    The estimation problem for uncertain time-delay systems is addressed. A design method of reduced-order interval observers is proposed. The observer estimates the set of admissible values (the interval) for the state at each instant of time. The cases of known fixed delays and uncertain time-varying delays are analysed. The proposed approach can be applied to linear delay systems and nonlinear time-delay systems in the output canonical form. It involves the properties of quasi-monotone/Metzler/cooperative systems. In this framework, it is shown that if under a suitable coordinate transformation the delay-free subsystem is cooperative, then the delayed estimation error dynamics inherits this property. The conditions to find the observer gains are formulated in the form of LMI. The framework efficiency is demonstrated on examples of nonlinear systems.

  6. Exponential Synchronization of Coupled Stochastic Memristor-Based Neural Networks With Time-Varying Probabilistic Delay Coupling and Impulsive Delay.

    PubMed

    Bao, Haibo; Park, Ju H; Cao, Jinde

    2016-01-01

    This paper deals with the exponential synchronization of coupled stochastic memristor-based neural networks with probabilistic time-varying delay coupling and time-varying impulsive delay. There is one probabilistic transmittal delay in the delayed coupling that is translated by a Bernoulli stochastic variable satisfying a conditional probability distribution. The disturbance is described by a Wiener process. Based on Lyapunov functions, Halanay inequality, and linear matrix inequalities, sufficient conditions that depend on the probability distribution of the delay coupling and the impulsive delay were obtained. Numerical simulations are used to show the effectiveness of the theoretical results.

  7. Global dissipativity analysis on uncertain neural networks with mixed time-varying delays.

    PubMed

    Song, Qiankun; Cao, Jinde

    2008-12-01

    In this paper, the problems of global dissipativity and global exponential dissipativity are investigated for uncertain neural networks with discrete time-varying delay and distributed time-varying delay as well as general activation functions. By constructing appropriate Lyapunov-Krasovskii functionals and employing Newton-Leibniz formulation and linear matrix inequality (LMI) technique, several new criteria for checking the global dissipativity and global exponential dissipativity of the addressed neural networks are established in terms of LMI, which can be checked numerically using the effective LMI toolbox in MATLAB. Illustrated examples are given to show the effectiveness and decreased conservatism of the proposed criteria in comparison with some existing results. It is noteworthy that the traditional assumptions on the differentiability of the time-varying delays and the boundedness of its derivative are removed.

  8. New delay dependent stability criteria for recurrent neural networks with interval time-varying delay.

    PubMed

    Yang, Qiongfen; Ren, Quanhong; Xie, Xuemei

    2014-07-01

    This paper is concerned with the delay dependent stability criteria for a class of static recurrent neural networks with interval time-varying delay. By choosing an appropriate Lyapunov-Krasovskii functional and employing a delay partitioning method, the less conservative condition is obtained. Furthermore, the LMIs-based condition depend on the lower and upper bounds of time delay. Finally, a numerical example is also designated to verify the reduced conservatism of developed criteria. PMID:24908560

  9. A delay decomposition approach to robust stability analysis of uncertain systems with time-varying delay.

    PubMed

    Liu, Pin-Lin

    2012-11-01

    This paper is concerned with delay-dependent robust stability for uncertain systems with time-varying delays. The proposed method employs a suitable Lyapunov-Krasovskii's functional for new augmented system. Then, based on the Lyapunov method, a delay-dependent robust criterion is devised by taking the relationship between the terms in the Leibniz-Newton formula into account. By developing a delay decomposition approach, the information of the delayed plant states can be taken into full consideration, and new delay-dependent sufficient stability criteria are obtained in terms of linear matrix inequalities (LMIs) which can be easily solved by various optimization algorithms. Numerical examples are included to show that the proposed method is effective and can provide less conservative results.

  10. Further results on delay-range-dependent stability with additive time-varying delay systems.

    PubMed

    Liu, Pin-Lin

    2014-03-01

    In this paper, new conditions for the delay-range-dependent stability analysis of time-varying delay systems are proposed in a Lyapunov-Krasovskii framework. Time delay is considered to be time-varying and has lower and upper bounds. A new method is first presented for a system with two time delays, integral inequality approach (IIA) used to express relationships among terms of Leibniz-Newton formula. Constructing a novel Lyapunov-Krasovskii functional includes information belonging to a given range; new delay-range-dependent criterion is established in term of linear matrix inequality (LMI). The advantage of that criterion lies in its simplicity and less conservative. This paper also presents a new result of stability analysis for continuous systems with two additive time-variant components representing a general class of delay with strong application background in network-based control systems. Resulting criteria are then expressed in terms of convex optimization with LMI constraints, allowing for use of efficient solvers. Finally, three numerical examples show these methods reducing conservatism and improving maximal allowable delay.

  11. Stability analysis of neural networks with interval time-varying delays.

    PubMed

    Hou, Yi-You; Liao, Teh-Lu; Lien, Chang-Hua; Yan, Jun-Juh

    2007-09-01

    The global exponential stability is investigated for neural networks with interval time-varying delays. Based on the Leibniz-Newton formula and linear matrix inequality technique, delay-dependent stability criteria are proposed to guarantee the exponential stability of neural networks with interval time-varying delays. Some numerical examples and comparisons are provided to show that the proposed results significantly improve the allowable upper and lower bounds of delays over some existing ones in the literature.

  12. Synchronization of Memristor-Based Coupling Recurrent Neural Networks With Time-Varying Delays and Impulses.

    PubMed

    Zhang, Wei; Li, Chuandong; Huang, Tingwen; He, Xing

    2015-12-01

    Synchronization of an array of linearly coupled memristor-based recurrent neural networks with impulses and time-varying delays is investigated in this brief. Based on the Lyapunov function method, an extended Halanay differential inequality and a new delay impulsive differential inequality, some sufficient conditions are derived, which depend on impulsive and coupling delays to guarantee the exponential synchronization of the memristor-based recurrent neural networks. Impulses with and without delay and time-varying delay are considered for modeling the coupled neural networks simultaneously, which renders more practical significance of our current research. Finally, numerical simulations are given to verify the effectiveness of the theoretical results.

  13. Admissibility analysis for linear singular systems with time-varying delays via neutral system approach.

    PubMed

    Liu, Zhou-Yang; Lin, Chong; Chen, Bing

    2016-03-01

    This paper studies the admissibility problem for a class of linear singular systems with time-varying delays. In order to highlight the relations between the delay and the state, the singular system is transformed into a neutral form. Then, an appropriate type of Lyapunov-Krasovskii functionals is proposed to develop a delay-derivative-dependent admissibility condition in terms of linear matrix inequalities. The derivation combines the Wirtinger-based inequality and reciprocally convex combination method. The present criterion is also for the stability test of retarded and neutral systems with time-varying delays. Some examples are provided to illustrate the effectiveness and the benefits of the proposed method.

  14. Receding Horizon Stabilization and Disturbance Attenuation for Neural Networks With Time-Varying Delay.

    PubMed

    Ahn, Choon Ki; Shi, Peng; Wu, Ligang

    2015-12-01

    This paper is concerned with the problems of receding horizon stabilization and disturbance attenuation for neural networks with time-varying delay. New delay-dependent conditions on the terminal weighting matrices of a new finite horizon cost functional for receding horizon stabilization are established for neural networks with time-varying or time-invariant delays using single- and double-integral Wirtinger-type inequalities. Based on the results, delay-dependent sufficient conditions for the receding horizon disturbance attenuation are given to guarantee the infinite horizon H∞ performance of neural networks with time-varying or time-invariant delays. Three numerical examples are provided to illustrate the effectiveness of the proposed approach.

  15. Periodicity and dissipativity for memristor-based mixed time-varying delayed neural networks via differential inclusions.

    PubMed

    Duan, Lian; Huang, Lihong

    2014-09-01

    In this paper, we investigate a class of memristor-based neural networks with general mixed delays involving both time-varying delays and distributed delays. By using the Mawhin-like coincidence theorem, together with the differential inclusion theory, M-matrix properties and differential inequality techniques, some novel criteria are established for ensuring the periodicity and dissipativity for the addressed neural networks. Finally, two numerical examples with simulations are presented to demonstrate the effectiveness of the theoretical results.

  16. H ∞ synchronization of the coronary artery system with input time-varying delay

    NASA Astrophysics Data System (ADS)

    Xiao-Meng, Li; Zhan-Shan, Zhao; Jing, Zhang; Lian-Kun, Sun

    2016-06-01

    This paper investigates the H ∞ synchronization of the coronary artery system with input delay and disturbance. We focus on reducing the conservatism of existing synchronization strategies. Base on the triple integral forms of the Lyapunov-Krasovskii functional (LKF), we utilize single and double integral forms of Wirtinger-based inequality to guarantee that the synchronization feedback controller has good performance against time-varying delay and external disturbance. The effectiveness of our strategy can be exhibited by simulations under the different time-varying delays and different disturbances. Project supported by the National Natural Science Foundation of China (Grant Nos. 61503280, 61403278, and 61272006).

  17. New robust passivity criteria for stochastic fuzzy BAM neural networks with time-varying delays

    NASA Astrophysics Data System (ADS)

    Mathiyalagan, Kalidass; Sakthivel, Rathinasamy; Marshal Anthoni, Selvaraj

    2012-03-01

    In this paper, we consider the problem of passivity analysis issue for a class of stochastic fuzzy BAM neural networks with time varying delays. By employing the idea of delay-fractioning technique and Lyapunov stability theory, a new set of sufficient conditions are derived in terms of linear matrix inequalities for obtaining the passivity condition of the considered neural network model. First, we derive the passivity condition for stochastic fuzzy BAM neural networks with time varying delays and then the result is extended to the case with uncertainties. Two numerical examples are given to illustrate the effectiveness and conservatism of the obtained results.

  18. H ∞ synchronization of the coronary artery system with input time-varying delay

    NASA Astrophysics Data System (ADS)

    Xiao-Meng, Li; Zhan-Shan, Zhao; Jing, Zhang; Lian-Kun, Sun

    2016-06-01

    This paper investigates the H ∞ synchronization of the coronary artery system with input delay and disturbance. We focus on reducing the conservatism of existing synchronization strategies. Base on the triple integral forms of the Lyapunov–Krasovskii functional (LKF), we utilize single and double integral forms of Wirtinger-based inequality to guarantee that the synchronization feedback controller has good performance against time-varying delay and external disturbance. The effectiveness of our strategy can be exhibited by simulations under the different time-varying delays and different disturbances. Project supported by the National Natural Science Foundation of China (Grant Nos. 61503280, 61403278, and 61272006).

  19. 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.

  20. Passivity and Passification of Memristor-Based Recurrent Neural Networks With Additive Time-Varying Delays.

    PubMed

    Rakkiyappan, Rajan; Chandrasekar, Arunachalam; Cao, Jinde

    2015-09-01

    This paper presents a new design scheme for the passivity and passification of a class of memristor-based recurrent neural networks (MRNNs) with additive time-varying delays. The predictable assumptions on the boundedness and Lipschitz continuity of activation functions are formulated. The systems considered here are based on a different time-delay model suggested recently, which includes additive time-varying delay components in the state. The connection between the time-varying delay and its upper bound is considered when estimating the upper bound of the derivative of Lyapunov functional. It is recognized that the passivity condition can be expressed in a linear matrix inequality (LMI) format and by using characteristic function method. For state feedback passification, it is verified that it is apathetic to use immediate or delayed state feedback. By constructing a Lyapunov-Krasovskii functional and employing Jensen's inequality and reciprocal convex combination technique together with a tighter estimation of the upper bound of the cross-product terms derived from the derivatives of the Lyapunov functional, less conventional delay-dependent passivity criteria are established in terms of LMIs. Moreover, second-order reciprocally convex approach is employed for deriving the upper bound for terms with inverses of squared convex parameters. The model based on the memristor with additive time-varying delays widens the application scope for the design of neural networks. Finally, pertinent examples are given to show the advantages of the derived passivity criteria and the significant improvement of the theoretical approaches.

  1. 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

  2. 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.

  3. On ℓ∞ and L∞ gains for positive systems with bounded time-varying delays

    NASA Astrophysics Data System (ADS)

    Shen, Jun; Lam, James

    2015-08-01

    This paper is devoted to the analysis of the ℓ∞ and L∞ gains for positive linear systems with interval time-varying delays. Through exploiting the monotonicity of the state trajectory, we first prove that for positive systems with constant delays, the ℓ∞ and L∞ gains are fully governed by the system matrices but independent of the delay size. Moreover, for positive systems with bounded time-varying delays, by comparing with the nominal systems with constant delays, it turns out that the ℓ∞ and L∞ gains are exactly the same as that of the constant delay systems. The results in this paper reveal that the ℓ∞ and L∞ gains of positive linear systems are not sensitive to the magnitude of time delays and hence the computation of ℓ∞ and L∞ gains of positive systems with bounded time-varying delays can be reduced to computing the ℓ∞ and L∞ gains of the corresponding delay-free systems. Both continuous-time and discrete-time cases are considered in this paper.

  4. New results on stability analysis for time-varying delay systems with non-linear perturbations.

    PubMed

    Liu, Pin-Lin

    2013-05-01

    The problem of stability for linear time-varying delay systems under nonlinear perturbation is discussed, with delay assumed as time-varying. Delay decomposition approach allows information of the delayed plant states to be fully considered. A less conservative delay-dependent robust stability condition is derived, using integral inequality approach to express the relationship of Leibniz-Newton formula terms in the within the framework of linear matrix inequalities (LMIs). Merits of the proposed results lie in lesser conservatism, which are realized by choosing different Lyapunov matrices in the decomposed integral intervals and estimating the upper bound of some cross term more exactly. Numerical examples are given to illustrate the effectiveness and lesser conservatism of the proposed method.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Power-rate synchronization of coupled genetic oscillators with unbounded time-varying delay.

    PubMed

    Alofi, Abdulaziz; Ren, Fengli; Al-Mazrooei, Abdullah; Elaiw, Ahmed; Cao, Jinde

    2015-10-01

    In this paper, a new synchronization problem for the collective dynamics among genetic oscillators with unbounded time-varying delay is investigated. The dynamical system under consideration consists of an array of linearly coupled identical genetic oscillators with each oscillators having unbounded time-delays. A new concept called power-rate synchronization, which is different from both the asymptotical synchronization and the exponential synchronization, is put forward to facilitate handling the unbounded time-varying delays. By using a combination of the Lyapunov functional method, matrix inequality techniques and properties of Kronecker product, we derive several sufficient conditions that ensure the coupled genetic oscillators to be power-rate synchronized. The criteria obtained in this paper are in the form of matrix inequalities. Illustrative example is presented to show the effectiveness of the obtained results.

  10. Generalized Halanay inequalities and their applications to neural networks with unbounded time-varying delays.

    PubMed

    Liu, Bo; Lu, Wenlian; Chen, Tianping

    2011-09-01

    In this brief, we discuss some variants of generalized Halanay inequalities that are useful in the discussion of dissipativity and stability of delayed neural networks, integro-differential systems, and Volterra functional differential equations. We provide some generalizations of the Halanay inequality, which is more accurate than the existing results. As applications, we discuss invariant set, dissipative synchronization, and global asymptotic stability for the Hopfield neural networks with infinite delays. We also prove that the dynamical systems with unbounded time-varying delays are globally asymptotically stable.

  11. 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.

  12. 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.

  13. 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. PMID:27164266

  14. Passivity and passification of memristor-based recurrent neural networks with time-varying delays.

    PubMed

    Guo, Zhenyuan; Wang, Jun; Yan, Zheng

    2014-11-01

    This paper presents new theoretical results on the passivity and passification of a class of memristor-based recurrent neural networks (MRNNs) with time-varying delays. The casual assumptions on the boundedness and Lipschitz continuity of neuronal activation functions are relaxed. By constructing appropriate Lyapunov-Krasovskii functionals and using the characteristic function technique, passivity conditions are cast in the form of linear matrix inequalities (LMIs), which can be checked numerically using an LMI toolbox. Based on these conditions, two procedures for designing passification controllers are proposed, which guarantee that MRNNs with time-varying delays are passive. Finally, two illustrative examples are presented to show the characteristics of the main results in detail.

  15. Attractivity analysis of memristor-based cellular neural networks with time-varying delays.

    PubMed

    Guo, Zhenyuan; Wang, Jun; Yan, Zheng

    2014-04-01

    This paper presents new theoretical results on the invariance and attractivity of memristor-based cellular neural networks (MCNNs) with time-varying delays. First, sufficient conditions to assure the boundedness and global attractivity of the networks are derived. Using state-space decomposition and some analytic techniques, it is shown that the number of equilibria located in the saturation regions of the piecewise-linear activation functions of an n-neuron MCNN with time-varying delays increases significantly from 2(n) to 2(2n2)+n) (2(2n2) times) compared with that without a memristor. In addition, sufficient conditions for the invariance and local or global attractivity of equilibria or attractive sets in any designated region are derived. Finally, two illustrative examples are given to elaborate the characteristics of the results in detail.

  16. 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.

  17. Global output feedback stabilisation of high-order nonlinear systems with multiple time-varying delays

    NASA Astrophysics Data System (ADS)

    Gao, Fangzheng; Wu, Yuqiang; Yuan, Fushun

    2016-07-01

    This paper investigates the problem of global output feedback stabilisation for a class of high-order nonlinear systems with multiple time-varying delays. By using backstepping recursive technique and the homogeneous domination approach, a continuous output feedback controller is successfully designed, and the global asymptotic stability of the resulting closed-loop system is proven with the help of an appropriate Lyapunov- Krasovskii functional. Two simulation examples are given to illustrate the effectiveness of the proposed approach.

  18. Dynamic behaviors of memristor-based recurrent neural networks with time-varying delays.

    PubMed

    Wu, Ailong; Zeng, Zhigang

    2012-12-01

    The paper introduces a general class of memristor-based recurrent neural networks with time-varying delays. Conditions on the nondivergence and global attractivity are established by using local inhibition, respectively. Moreover, exponential convergence of the networks is studied by using local invariant sets. The analysis in the paper employs results from the theory of differential equations with discontinuous right-hand sides as introduced by Filippov. The obtained results extend some previous works on conventional recurrent neural networks.

  19. Global robust dissipativity of interval recurrent neural networks with time-varying delay and discontinuous activations.

    PubMed

    Duan, Lian; Huang, Lihong; Guo, Zhenyuan

    2016-07-01

    In this paper, the problems of robust dissipativity and robust exponential dissipativity are discussed for a class of recurrent neural networks with time-varying delay and discontinuous activations. We extend an invariance principle for the study of the dissipativity problem of delay systems to the discontinuous case. Based on the developed theory, some novel criteria for checking the global robust dissipativity and global robust exponential dissipativity of the addressed neural network model are established by constructing appropriate Lyapunov functionals and employing the theory of Filippov systems and matrix inequality techniques. The effectiveness of the theoretical results is shown by two examples with numerical simulations. PMID:27475061

  20. Global robust dissipativity of interval recurrent neural networks with time-varying delay and discontinuous activations.

    PubMed

    Duan, Lian; Huang, Lihong; Guo, Zhenyuan

    2016-07-01

    In this paper, the problems of robust dissipativity and robust exponential dissipativity are discussed for a class of recurrent neural networks with time-varying delay and discontinuous activations. We extend an invariance principle for the study of the dissipativity problem of delay systems to the discontinuous case. Based on the developed theory, some novel criteria for checking the global robust dissipativity and global robust exponential dissipativity of the addressed neural network model are established by constructing appropriate Lyapunov functionals and employing the theory of Filippov systems and matrix inequality techniques. The effectiveness of the theoretical results is shown by two examples with numerical simulations.

  1. Global robust dissipativity of interval recurrent neural networks with time-varying delay and discontinuous activations

    NASA Astrophysics Data System (ADS)

    Duan, Lian; Huang, Lihong; Guo, Zhenyuan

    2016-07-01

    In this paper, the problems of robust dissipativity and robust exponential dissipativity are discussed for a class of recurrent neural networks with time-varying delay and discontinuous activations. We extend an invariance principle for the study of the dissipativity problem of delay systems to the discontinuous case. Based on the developed theory, some novel criteria for checking the global robust dissipativity and global robust exponential dissipativity of the addressed neural network model are established by constructing appropriate Lyapunov functionals and employing the theory of Filippov systems and matrix inequality techniques. The effectiveness of the theoretical results is shown by two examples with numerical simulations.

  2. Design of a robust controller on stabilization of stochastic neural networks with time varying delays

    NASA Astrophysics Data System (ADS)

    Sakthivel, R.; Karthik Raja, U.; Mathiyalagan, K.; Leelamani, A.

    2012-03-01

    This paper is concerned with the problem of robust stabilization and H∞ control for a class of uncertain stochastic neural networks with time-varying delays and time-varying norm-bounded parameter uncertainties. The delay is of a time-varying nature, and the activation functions are assumed to be neither differentiable nor strictly monotonic. Moreover, the description of the activation functions is more general than the commonly used Lipschitz conditions. By using the Lyapunov function approach together with the linear matrix inequality (LMI) technique, for the robust stabilization we propose a state feedback controller to ensure that the closed loop system is robustly asymptotically stable in the mean square for all admissible parameter uncertainties. For the robust H∞ control problem, a state feedback controller is designed such that in addition to the requirement of robust stability, a prescribed H∞ performance level is to be satisfied. The results obtained are formulated in terms of LMIs which can be easily checked by the MATLAB LMI control toolbox. Numerical examples are presented to illustrate the effectiveness of the obtained method and the improvement over some existing results.

  3. 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.

  4. Improved stability conditions for uncertain neutral-type systems with time-varying delays

    NASA Astrophysics Data System (ADS)

    Ren, Yu; Feng, Zhiguang; Sun, Guanghui

    2016-06-01

    This paper investigates the robust stability problem for a class of uncertain neutral-type delayed systems. The systems under consideration contain parameter uncertainties and time-varying delays. We aim at designing less conservative robust stability criteria for such systems. A new second-order reciprocally convex inequality is first proposed in order to deal with double integral terms. Then, by constructing a new Lyapunov- Krasovskii functional and employing the improved Wirtinger-based integral inequality and the reciprocally convex combination approaches, novel stability criteria are obtained. Moreover, the stability conditions for standard time-delay system are obtained as by-product results. Comparisons in three numerical examples illustrate the effectiveness of our results.

  5. Minimum-energy control for time-varying systems with multiple state and input delays

    NASA Astrophysics Data System (ADS)

    Liu, Hai-Lin; Tang, Gong-You; Yang, Xue

    2016-09-01

    This paper considers the minimum-energy control problem for a class of time-varying systems with multiple state and input delays. First, a state transform matrix is presented. By using the transform matrix, a system with multiple state and input delays is converted to a formal equivalent one without delay. Then, the optimal problem of the novel system is solved by using the maximum principle. Analytical expressions of the optimal control law and optimal performance are given by two formulas with respect to the state transform matrix. At last, an algorithm is given to solve the analytical expression of the state transform matrix. Simulation results show that the design algorithm is efficient and easy to implement.

  6. Comments on 'Improved delay-dependent stability criteria for continuous systems with two additive time-varying delay components'

    NASA Astrophysics Data System (ADS)

    Ramakrishnan, K.; Venkatachalam, V.; Ray, G.

    2015-07-01

    In this write-up, comments on the omission of few important inequality conditions (or constraints) in the LMI optimization problem stated as delay-dependent stability criterion for a class of linear systems with two additive time-varying state-delays in Cheng et al. (2014) is reported. The omission paves way to incorrectness of the published result. The consequence of the omission, and the revised result are presented in the sequel.

  7. Robust Adaptive Control for a Class of Uncertain Nonlinear Systems with Time-Varying Delay

    PubMed Central

    Wang, Ruliang; Li, Jie; Zhang, Shanshan; Gao, Dongmei; Sun, Huanlong

    2013-01-01

    We present adaptive neural control design for a class of perturbed nonlinear MIMO time-varying delay systems in a block-triangular form. Based on a neural controller, it is obtained by constructing a quadratic-type Lyapunov-Krasovskii functional, which efficiently avoids the controller singularity. The proposed control guarantees that all closed-loop signals remain bounded, while the output tracking error dynamics converge to a neighborhood of the desired trajectories. The simulation results demonstrate the effectiveness of the proposed control scheme. PMID:23853544

  8. Adaptive Synchronization of Memristor-Based Neural Networks with Time-Varying Delays.

    PubMed

    Wang, Leimin; Shen, Yi; Yin, Quan; Zhang, Guodong

    2015-09-01

    In this paper, adaptive synchronization of memristor-based neural networks (MNNs) with time-varying delays is investigated. The dynamical analysis here employs results from the theory of differential equations with discontinuous right-hand sides as introduced by Filippov. Sufficient conditions for the global synchronization of MNNs are established with a general adaptive controller. The update gain of the controller can be adjusted to control the synchronization speed. The obtained results complement and improve the previously known results. Finally, numerical simulations are carried out to demonstrate the effectiveness of the obtained results.

  9. Design of a passification controller for uncertain fuzzy Hopfield neural networks with time-varying delays

    NASA Astrophysics Data System (ADS)

    Sakthivel, R.; Mathiyalagan, K.; Anthoni, S. Marshal

    2011-10-01

    This paper addresses the problem of controller design for passivity of uncertain fuzzy Hopfield neural networks with time-varying delays. The main purpose of this paper is to design a state feedback fuzzy controller such that the resulting closed-loop system is passive. A new set of sufficient conditions are derived for achieving the required result by employing the Lyapunov functional method and matrix analysis technique. The derived criteria are expressed in terms of linear matrix inequalities that can be easily checked using standard numerical software. Two numerical examples with simulation results are given to illustrate the effectiveness and conservatism of the obtained results.

  10. 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.

  11. 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.

  12. Adaptive Synchronization of Memristor-Based Neural Networks with Time-Varying Delays.

    PubMed

    Wang, Leimin; Shen, Yi; Yin, Quan; Zhang, Guodong

    2015-09-01

    In this paper, adaptive synchronization of memristor-based neural networks (MNNs) with time-varying delays is investigated. The dynamical analysis here employs results from the theory of differential equations with discontinuous right-hand sides as introduced by Filippov. Sufficient conditions for the global synchronization of MNNs are established with a general adaptive controller. The update gain of the controller can be adjusted to control the synchronization speed. The obtained results complement and improve the previously known results. Finally, numerical simulations are carried out to demonstrate the effectiveness of the obtained results. PMID:25389244

  13. Finite-time stability and stabilisation for a class of nonlinear systems with time-varying delay

    NASA Astrophysics Data System (ADS)

    Liu, Hao; Shi, Peng; Karimi, Hamid Reza; Chadli, Mohammed

    2016-04-01

    This paper is concerned with the problems of finite-time stability (FTS) and finite-time stabilisation for a class of nonlinear systems with time-varying delay, which can be represented by Takagi-Sugeno fuzzy system. Some new delay-dependent FTS conditions are provided and applied to the design problem of finite-time fuzzy controllers. First, based on an integral inequality and a fuzzy Lyapunov-Krasovskii functional, a delay-dependent FTS criterion is proposed for open-loop fuzzy system by introducing some free fuzzy weighting matrices, which are less conservative than other existing ones. Then, the parallel distributed compensation controller is designed to ensure FTS of the time-delay fuzzy system. Finally, an example is given to illustrate the effectiveness of the proposed design approach.

  14. Delay-dependent criteria for global robust periodicity of uncertain switched recurrent neural networks with time-varying delay.

    PubMed

    Lou, X; Cui, B

    2008-04-01

    In this paper, we introduce some ideas of switched systems into the field of neural networks and a large class of switched recurrent neural networks (SRNNs) with time-varying structured uncertainties and time-varying delay is investigated. Some delay-dependent robust periodicity criteria guaranteeing the existence, uniqueness, and global asymptotic stability of periodic solution for all admissible parametric uncertainties are devised by taking the relationship between the terms in the Leibniz-Newton formula into account. Because free weighting matrices are used to express this relationship and the appropriate ones are selected by means of linear matrix inequalities (LMIs), the criteria are less conservative than existing ones reported in the literature for delayed neural networks with parameter uncertainties. Some examples are given to show that the proposed criteria are effective and are an improvement over previous ones.

  15. 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

  16. Adaptive Q-S (lag, anticipated, and complete) time-varying synchronization and parameters identification of uncertain delayed neural networks

    NASA Astrophysics Data System (ADS)

    Yu, Wenwu; Cao, Jinde

    2006-06-01

    In this paper, a new type of generalized Q-S (lag, anticipated, and complete) time-varying synchronization is defined. Adaptive Q-S (lag, anticipated, and complete) time-varying synchronization and parameters identification of uncertain delayed neural networks have been considered, where the delays are multiple time-varying delays. A novel control method is given by using the Lyapunov functional method. With this new and effective method, parameters identification and Q-S (lag, anticipated, and complete) time-varying synchronization can be achieved simultaneously. Simulation results are given to justify the theoretical analysis in this paper.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. 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.

  2. L2-Stable Bilateral Control System with Time-Varying Communication Delay

    NASA Astrophysics Data System (ADS)

    Yashiro, Daisuke; Natori, Kenji; Ohnishi, Kouhei

    Passivity theory is a very useful tool for the stability analysis of bilateral teleoperation with communication delay. Many researchers use passivity-based stabilization method such as those based on scattering theory or wave variables. However, passivity-based stabilization is too conservative for the design of a high-performance teleoperation system. The term “high-performance” implies that people who operate this system can experience a highly accurate reaction force from environments. In this study, we analyze the L2-stability of some bilateral control systems with time-varying communication delay by using the small-gain theorem. The small-gain theorem is known to be a stability condition for multi-input multi-output feedback systems. Additionally, a novel control structure for the bilateral control system with communication delay is proposed. The bilateral control system with the proposed structure satisfies the L2-stability condition of the small-gain theorem. The experimental results show the utility of the proposed control structure.

  3. 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. PMID:26434415

  4. Finite-time synchronization for memristor-based neural networks with time-varying delays.

    PubMed

    Abdurahman, Abdujelil; Jiang, Haijun; Teng, Zhidong

    2015-09-01

    Memristive network exhibits state-dependent switching behaviors due to the physical properties of memristor, which is an ideal tool to mimic the functionalities of the human brain. In this paper, finite-time synchronization is considered for a class of memristor-based neural networks with time-varying delays. Based on the theory of differential equations with discontinuous right-hand side, several new sufficient conditions ensuring the finite-time synchronization of memristor-based chaotic neural networks are obtained by using analysis technique, finite time stability theorem and adding a suitable feedback controller. Besides, the upper bounds of the settling time of synchronization are estimated. Finally, a numerical example is given to show the effectiveness and feasibility of the obtained results.

  5. 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.

  6. 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

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

    PubMed

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

    2016-04-26

    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.

  8. Delay decomposition approach to [Formula: see text] filtering analysis of genetic oscillator networks with time-varying delays.

    PubMed

    Revathi, V M; Balasubramaniam, P

    2016-04-01

    In this paper, the [Formula: see text] filtering problem is treated for N coupled genetic oscillator networks with time-varying delays and extrinsic molecular noises. Each individual genetic oscillator is a complex dynamical network that represents the genetic oscillations in terms of complicated biological functions with inner or outer couplings denote the biochemical interactions of mRNAs, proteins and other small molecules. Throughout the paper, first, by constructing appropriate delay decomposition dependent Lyapunov-Krasovskii functional combined with reciprocal convex approach, improved delay-dependent sufficient conditions are obtained to ensure the asymptotic stability of the filtering error system with a prescribed [Formula: see text] performance. Second, based on the above analysis, the existence of the designed [Formula: see text] filters are established in terms of linear matrix inequalities with Kronecker product. Finally, numerical examples including a coupled Goodwin oscillator model are inferred to illustrate the effectiveness and less conservatism of the proposed techniques.

  9. Adaptive iterative learning control for nonlinearly parameterised systems with unknown time-varying delays and input saturations

    NASA Astrophysics Data System (ADS)

    Zhang, Ruikun; Hou, Zhongsheng; Chi, Ronghu; Ji, Honghai

    2015-06-01

    In this work, an adaptive iterative learning control (AILC) scheme is proposed to address a class of nonlinearly parameterised systems with both unknown time-varying delays and input saturations. By incorporating a saturation function, a novel iterative learning control mechanism is constructed with a feedback term in the time domain and a fully saturated adaptive learning term in the iteration domain, which is used to estimate the unknown time-varying system uncertainty. A new time-weighted Lyapunov-Krasovskii-like composite energy function (LKL-CEF) is designed for the convergence analysis where time-weighted inputs, states and estimates of system uncertainty are all considered. Despite the existence of time-varying parametric uncertainties, time-varying delays, input saturations and local Lipschitz nonlinearities, the learning convergence is guaranteed with rigorous mathematical analysis. Simulation results verify the correctness and effectiveness of the proposed method further.

  10. Delay-dependent stability of neutral system with mixed time-varying delays and nonlinear perturbations using delay-dividing approach.

    PubMed

    Qiu, Fang; Cao, Jinde; Hayat, Tasawar

    2015-02-01

    This paper studies delay-dependent robust stability problem for neutral system with mixed time-varying delays and nonlinear perturbations. Based on the delay-dividing approach, a novel Lyapunov functional is constructed, and a novel delay-dependent stability criterion is derived to guarantee the robust stability of the neutral system. Expressed in terms of linear matrix inequalities, the stability condition can be checked using the numerically efficient Matlab LMI Control Toolbox. Two numerical examples are provided to demonstrate the effectiveness and the reduced conservatism of the analysis result.

  11. A new reduction-based LQ control for dynamic systems with a slowly time-varying delay

    NASA Astrophysics Data System (ADS)

    Liu, Bo; Haraguchi, Masakazu; Hu, Haiyan

    2009-08-01

    Time delays in the feedback control often deteriorate the control performance or even cause the instability of a dynamic system. This paper presents a control strategy for the dynamic system with a constant or a slowly time-varying input delay based on a transformation, which simplifies the time-delay system into a delay-free one. Firstly, the relation is discussed for two existing reduction-based linear quadratic controls. One is continuous and the other is discrete. By extending the relation, a new reduction-based control is then developed with a numerical algorithm presented for practical control implementation. The controller suggested by the proposed method has such a promising property that it can be used for the cases of different values of an input time delay without redesign of controller. This property provides the potential for stabilizing the dynamic system with a time-varying input delay. Consequently, the application of the proposed method to the dynamic system with a slowly time-varying delay is discussed. Finally, numerical simulations are given to show the efficacy and the applicability of the method.

  12. Adaptive NN backstepping output-feedback control for stochastic nonlinear strict-feedback systems with time-varying delays.

    PubMed

    Chen, Weisheng; Jiao, Licheng; Li, Jing; Li, Ruihong

    2010-06-01

    For the first time, this paper addresses the problem of adaptive output-feedback control for a class of uncertain stochastic nonlinear strict-feedback systems with time-varying delays using neural networks (NNs). The circle criterion is applied to designing a nonlinear observer, and no linear growth condition is imposed on nonlinear functions depending on system states. Under the assumption that time-varying delays exist in the system output, only an NN is employed to compensate for all unknown nonlinear terms depending on the delayed output, and thus, the proposed control algorithm is more simple even than the existing NN backstepping control schemes for uncertain systems described by ordinary differential equations. Three examples are given to demonstrate the effectiveness of the control scheme proposed in this paper.

  13. H∞ approach to monotonically convergent ILC for uncertain time-varying delay systems

    NASA Astrophysics Data System (ADS)

    Meng, Deyuan; Jia, Yingmin; Du, Junping

    2015-01-01

    This paper deals with iterative learning control (ILC) design for uncertain time-delay systems. Monotonic convergence of the resulting ILC process is studied, and a sufficient condition within an H∞-based framework is developed. It is shown that under this framework, delay-dependent conditions can be obtained in terms of linear matrix inequalities (LMIs), together with formulas for gain matrices design. A numerical example is provided to illustrate the effectiveness of the robust H∞-based approach to ILC designed via LMIs.

  14. Exponential synchronization for fuzzy cellular neural networks with time-varying delays and nonlinear impulsive effects.

    PubMed

    Pu, Hao; Liu, Yanmin; Jiang, Haijun; Hu, Cheng

    2015-08-01

    In this paper, the globally exponential synchronization of delayed fuzzy cellular neural networks with nonlinear impulsive effects are concerned. By utilizing inequality techniques and Lyapunov functional method, some sufficient conditions on the exponential synchronization are obtained based on [Formula: see text]-norm. Finally, a simulation example is given to illustrate the effectiveness of the theoretical results.

  15. Global exponential dissipativity and stabilization of memristor-based recurrent neural networks with time-varying delays.

    PubMed

    Guo, Zhenyuan; Wang, Jun; Yan, Zheng

    2013-12-01

    This paper addresses the global exponential dissipativity of memristor-based recurrent neural networks with time-varying delays. By constructing proper Lyapunov functionals and using M-matrix theory and LaSalle invariant principle, the sets of global exponentially dissipativity are characterized parametrically. It is proven herein that there are 2(2n(2)-n) equilibria for an n-neuron memristor-based neural network and they are located in the derived globally attractive sets. It is also shown that memristor-based recurrent neural networks with time-varying delays are stabilizable at the origin of the state space by using a linear state feedback control law with appropriate gains. Finally, two numerical examples are discussed in detail to illustrate the characteristics of the results.

  16. M-matrix-based stability conditions for genetic regulatory networks with time-varying delays and noise perturbations.

    PubMed

    Tian, Li-Ping; Shi, Zhong-Ke; Liu, Li-Zhi; Wu, Fang-Xiang

    2013-10-01

    Stability is essential for designing and controlling any dynamic systems. Recently, the stability of genetic regulatory networks has been widely studied by employing linear matrix inequality (LMI) approach, which results in checking the existence of feasible solutions to high-dimensional LMIs. In the previous study, the authors present several stability conditions for genetic regulatory networks with time-varying delays, based on M-matrix theory and using the non-smooth Lyapunov function, which results in determining whether a low-dimensional matrix is a non-singular M-matrix. However, the previous approach cannot be applied to analyse the stability of genetic regulatory networks with noise perturbations. Here, the authors design a smooth Lyapunov function quadratic in state variables and employ M-matrix theory to derive new stability conditions for genetic regulatory networks with time-varying delays. Theoretically, these conditions are less conservative than existing ones in some genetic regulatory networks. Then the results are extended to genetic regulatory networks with time-varying delays and noise perturbations. For genetic regulatory networks with n genes and n proteins, the derived conditions are to check if an n × n matrix is a non-singular M-matrix. To further present the new theories proposed in this study, three example regulatory networks are analysed.

  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. Robust synchronization analysis in nonlinear stochastic cellular networks with time-varying delays, intracellular perturbations and intercellular noise.

    PubMed

    Chen, Po-Wei; Chen, Bor-Sen

    2011-08-01

    Naturally, a cellular network consisted of a large amount of interacting cells is complex. These cells have to be synchronized in order to emerge their phenomena for some biological purposes. However, the inherently stochastic intra and intercellular interactions are noisy and delayed from biochemical processes. In this study, a robust synchronization scheme is proposed for a nonlinear stochastic time-delay coupled cellular network (TdCCN) in spite of the time-varying process delay and intracellular parameter perturbations. Furthermore, a nonlinear stochastic noise filtering ability is also investigated for this synchronized TdCCN against stochastic intercellular and environmental disturbances. Since it is very difficult to solve a robust synchronization problem with the Hamilton-Jacobi inequality (HJI) matrix, a linear matrix inequality (LMI) is employed to solve this problem via the help of a global linearization method. Through this robust synchronization analysis, we can gain a more systemic insight into not only the robust synchronizability but also the noise filtering ability of TdCCN under time-varying process delays, intracellular perturbations and intercellular disturbances. The measures of robustness and noise filtering ability of a synchronized TdCCN have potential application to the designs of neuron transmitters, on-time mass production of biochemical molecules, and synthetic biology. Finally, a benchmark of robust synchronization design in Escherichia coli repressilators is given to confirm the effectiveness of the proposed methods. PMID:21624379

  19. 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.

  20. New results on anti-synchronization of switched neural networks with time-varying delays and lag signals.

    PubMed

    Cao, Yuting; Wen, Shiping; Chen, Michael Z Q; Huang, Tingwen; Zeng, Zhigang

    2016-09-01

    This paper investigates the problem of global exponential anti-synchronization of a class of switched neural networks with time-varying delays and lag signals. Considering the packed circuits, the controller is dependent on the output of the system as the inner states are very hard to measure. Therefore, it is necessary to investigate the controller based on the output of the neuron cell. Through theoretical analysis, it is obvious that the obtained ones improve and generalize the results derived in the previous literature. To illustrate the effectiveness, a simulation example with applications in image encryptions is also presented in the paper.

  1. Global exponential stability of complex-valued neural networks with both time-varying delays and impulsive effects.

    PubMed

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

    2016-07-01

    In this paper, the global exponential stability of complex-valued neural networks with both time-varying delays and impulsive effects is discussed. By employing Lyapunov functional method and using matrix inequality technique, several sufficient conditions in complex-valued linear matrix inequality form are obtained to ensure the existence, uniqueness and global exponential stability of equilibrium point for the considered neural networks. Moreover, the exponential convergence rate index is estimated, which depends on the system parameters. The proposed stability results are less conservative than some recently known ones in the literatures, which is demonstrated via two examples with simulations.

  2. New results on anti-synchronization of switched neural networks with time-varying delays and lag signals.

    PubMed

    Cao, Yuting; Wen, Shiping; Chen, Michael Z Q; Huang, Tingwen; Zeng, Zhigang

    2016-09-01

    This paper investigates the problem of global exponential anti-synchronization of a class of switched neural networks with time-varying delays and lag signals. Considering the packed circuits, the controller is dependent on the output of the system as the inner states are very hard to measure. Therefore, it is necessary to investigate the controller based on the output of the neuron cell. Through theoretical analysis, it is obvious that the obtained ones improve and generalize the results derived in the previous literature. To illustrate the effectiveness, a simulation example with applications in image encryptions is also presented in the paper. PMID:27295505

  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. Function projective synchronization of memristor-based Cohen-Grossberg neural networks with time-varying delays.

    PubMed

    Abdurahman, Abdujelil; Jiang, Haijun; Rahman, Kaysar

    2015-12-01

    This paper deals with the problem of function projective synchronization for a class of memristor-based Cohen-Grossberg neural networks with time-varying delays. Based on the theory of differential equations with discontinuous right-hand side, some novel criteria are obtained to realize the function projective synchronization of addressed networks by combining open loop control and linear feedback control. As some special cases, several control strategies are given to ensure the realization of complete synchronization, anti-synchronization and the stabilization of the considered memristor-based Cohen-Grossberg neural network. Finally, a numerical example and its simulations are provided to demonstrate the effectiveness of the obtained results.

  5. 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.

  6. 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.

  7. New results on delay-range-dependent stability analysis for interval time-varying delay systems with non-linear perturbations.

    PubMed

    Liu, Pin-Lin

    2015-07-01

    This paper studies the problem of the stability analysis of interval time-varying delay systems with nonlinear perturbations. Based on the Lyapunov-Krasovskii functional (LKF), a sufficient delay-range-dependent criterion for asymptotic stability is derived in terms of linear matrix inequality (LMI) and integral inequality approach (IIA) and delayed decomposition approach (DDA). Further, the delay range is divided into two equal segments for stability analysis. Both theoretical and numerical comparisons have been provided to show the effectiveness and efficiency of the present method. Two well-known examples are given to show less conservatism of our obtained results and the effectiveness of the proposed method.

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

    PubMed

    Wesolowski, Carl A; Wesolowski, Michal J; Babyn, Paul S; Wanasundara, Surajith N

    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.

  9. 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

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

    PubMed

    Wesolowski, Carl A; Wesolowski, Michal J; Babyn, Paul S; Wanasundara, Surajith N

    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

  11. Fault detection for singular switched linear systems with multiple time-varying delay in finite frequency domain

    NASA Astrophysics Data System (ADS)

    Zhai, Ding; Lu, Anyang; Li, Jinghao; Zhang, Qingling

    2016-10-01

    This paper deals with the problem of the fault detection (FD) for continuous-time singular switched linear systems with multiple time-varying delay. In this paper, the actuator fault is considered. Besides, the systems faults and unknown disturbances are assumed in known frequency domains. Some finite frequency performance indices are initially introduced to design the switched FD filters which ensure that the filtering augmented systems under switching signal with average dwell time are exponentially admissible and guarantee the fault input sensitivity and disturbance robustness. By developing generalised Kalman-Yakubovic-Popov lemma and using Parseval's theorem and Fourier transform, finite frequency delay-dependent sufficient conditions for the existence of such a filter which can guarantee the finite-frequency H- and H∞ performance are derived and formulated in terms of linear matrix inequalities. Four examples are provided to illustrate the effectiveness of the proposed finite frequency method.

  12. 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.

  13. Further improved stability criteria for uncertain T-S fuzzy systems with time-varying delay by (m,N)-delay-partitioning approach.

    PubMed

    Yang, Jun; Luo, Wen-Pin; Wang, Yong-Hu; Cheng, Jun

    2015-11-01

    This paper mainly focuses on the robust stability criteria for uncertain T-S fuzzy systems with time-varying delay by (m,N)-delay-partitioning approach. A modified augmented LKF is established by partitioning the delay in all integral terms. Via taking into account of (i) the relationship between each subinterval and time-varying delay and (ii) the independent upper bounds of the delay derivative in the various delay intervals, some new results on tighter bounding inequalities such as Peng-Park׳s integral inequality and Free-Matrix-based integral inequality are introduced to effectively reduce the enlargement in bounding the derivative of LKF as much as possible, therefore, significant less conservative results can be expected in terms of es and LMIs, which can be solved efficiently with the Matlab LMI toolbox. Furthermore, it is worth mentioning that, when the delay-partitioning number m is fixed, the conservatism is gradually reduced with the increase of another delay-partitioning number N, but without increasing any computing burden. Finally, two numerical examples are included to show that the proposed method is less conservative than existing ones. PMID:26365365

  14. 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.

  15. Global and robust stability analysis of genetic regulatory networks with time-varying delays and parameter uncertainties.

    PubMed

    Fang-Xiang Wu

    2011-08-01

    The study of stability is essential for designing or controlling genetic regulatory networks. This paper addresses global and robust stability of genetic regulatory networks with time delays and parameter uncertainties. Most existing results on this issue are based on the linear matrix inequalities (LMIs) approach, which results in checking the existence of a feasible solution to high dimensional LMIs. Based on M-matrix theory, we will present several novel global stability conditions for genetic regulatory networks with time-varying and time-invariant delays. All of these stability conditions are given in terms of M-matrices, for which there are many and very easy ways to be verified. Then, we extend these results to genetic regulatory networks with time delays and parameter uncertainties. To illustrate the effectiveness of our theoretical results, several genetic regulatory networks are analyzed. Compared with existing results in the literature, we also show that our results are less conservative than existing ones with these illustrative genetic regulatory networks.

  16. Non-fragile H∞ dynamic output feedback control for uncertain Takagi-Sugeno fuzzy systems with time-varying delay

    NASA Astrophysics Data System (ADS)

    Huang, Sheng-Juan; Yang, Guang-Hong

    2016-09-01

    This paper mainly focuses on the problem of non-fragile H∞ dynamic output feedback control for a class of uncertain Takagi-Sugeno fuzzy systems with time-varying state delay. Based on a new type of Lyapunov-Krasovskii functional without ignoring any subtle integral terms in the derivatives, a less conservative dynamic output feedback controller with additive gain variations is designed, which guarantees that the closed-loop fuzzy system is asymptotically stable and satisfies a prescribed H∞-performance level. Furthermore, the obtained parameter-dependent conditions are given in terms of solution to a set of linear matrix inequalities, which improve some existing relevant results. Finally, numerical examples are given to illustrate the effectiveness and merits of the proposed method.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. Stability criteria for T-S fuzzy systems with interval time-varying delays and nonlinear perturbations based on geometric progression delay partitioning method.

    PubMed

    Chen, Hao; Zhong, Shouming; Li, Min; Liu, Xingwen; Adu-Gyamfi, Fehrs

    2016-07-01

    In this paper, a novel delay partitioning method is proposed by introducing the theory of geometric progression for the stability analysis of T-S fuzzy systems with interval time-varying delays and nonlinear perturbations. Based on the common ratio α, the delay interval is unequally separated into multiple subintervals. A newly modified Lyapunov-Krasovskii functional (LKF) is established which includes triple-integral terms and augmented factors with respect to the length of every related proportional subintervals. In addition, a recently developed free-matrix-based integral inequality is employed to avoid the overabundance of the enlargement when dealing with the derivative of the LKF. This innovative development can dramatically enhance the efficiency of obtaining the maximum upper bound of the time delay. Finally, much less conservative stability criteria are presented. Numerical examples are conducted to demonstrate the significant improvements of this proposed approach. PMID:27138648

  2. Input-Output Approach to Control for Fuzzy Markov Jump Systems With Time-Varying Delays and Uncertain Packet Dropout Rate.

    PubMed

    Zhang, Lixian; Ning, Zepeng; Shi, Peng

    2015-11-01

    This paper is concerned with H∞ control problem for a class of discrete-time Takagi-Sugeno fuzzy Markov jump systems with time-varying delays under unreliable communication links. It is assumed that the data transmission between the plant and the controller are subject to randomly occurred packet dropouts satisfying Bernoulli distribution and the dropout rate is uncertain. Based on a fuzzy-basis-dependent and mode-dependent Lyapunov function, the existence conditions of the desired H∞ state-feedback controllers are derived by employing the scaled small gain theorem such that the closed-loop system is stochastically stable and achieves a guaranteed H∞ performance. The gains of the controllers are constructed by solving a set of linear matrix inequalities. Finally, a practical example of robot arm is provided to illustrate the performance of the proposed approach.

  3. 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.

  4. 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. PMID:26996925

  5. Improved results on nonlinear perturbed T-S fuzzy systems with interval time-varying delays using a geometric sequence division method.

    PubMed

    Chen, Hao

    2016-01-01

    This paper presents improved stability results by introducing a new delay partitioning method based on the theory of geometric progression to deal with T-S fuzzy systems in the appearance of interval time-varying delays and nonlinear perturbations. A common ratio [Formula: see text] is applied to split the delay interval into multiple unequal subintervals. A modified Lyapunov-Krasovskii functional (LKF) is constructed with triple-integral terms and augmented factors including the length of every subintervals. In addition, the recently developed free-matrix-based integral inequality is employed to combine with the extended reciprocal convex combination and free weight matrices techniques for avoiding the overabundance of the enlargement when deducing the derivative of the LKF. Eventually, this developed research work can efficiently obtain the maximum upper bound of the time-varying delay with much less conservatism. Numerical results are conducted to illustrate the remarkable improvements of this proposed method. PMID:27429885

  6. 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.

  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. 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. PMID:24808577

  9. 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.

  10. Multistability analysis of a general class of recurrent neural networks with non-monotonic activation functions and time-varying delays.

    PubMed

    Liu, Peng; Zeng, Zhigang; Wang, Jun

    2016-07-01

    This paper addresses the multistability for a general class of recurrent neural networks with time-varying delays. Without assuming the linearity or monotonicity of the activation functions, several new sufficient conditions are obtained to ensure the existence of (2K+1)(n) equilibrium points and the exponential stability of (K+1)(n) equilibrium points among them for n-neuron neural networks, where K is a positive integer and determined by the type of activation functions and the parameters of neural network jointly. The obtained results generalize and improve the earlier publications. Furthermore, the attraction basins of these exponentially stable equilibrium points are estimated. It is revealed that the attraction basins of these exponentially stable equilibrium points can be larger than their originally partitioned subsets. Finally, three illustrative numerical examples show the effectiveness of theoretical results.

  11. Multistability analysis of a general class of recurrent neural networks with non-monotonic activation functions and time-varying delays.

    PubMed

    Liu, Peng; Zeng, Zhigang; Wang, Jun

    2016-07-01

    This paper addresses the multistability for a general class of recurrent neural networks with time-varying delays. Without assuming the linearity or monotonicity of the activation functions, several new sufficient conditions are obtained to ensure the existence of (2K+1)(n) equilibrium points and the exponential stability of (K+1)(n) equilibrium points among them for n-neuron neural networks, where K is a positive integer and determined by the type of activation functions and the parameters of neural network jointly. The obtained results generalize and improve the earlier publications. Furthermore, the attraction basins of these exponentially stable equilibrium points are estimated. It is revealed that the attraction basins of these exponentially stable equilibrium points can be larger than their originally partitioned subsets. Finally, three illustrative numerical examples show the effectiveness of theoretical results. PMID:27136665

  12. 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.

  13. Observer-based robust finite time H∞ sliding mode control for Markovian switching systems with mode-dependent time-varying delay and incomplete transition rate.

    PubMed

    Gao, Lijun; Jiang, Xiaoxiao; Wang, Dandan

    2016-03-01

    This paper investigates the problem of robust finite time H∞ sliding mode control for a class of Markovian switching systems. The system is subjected to the mode-dependent time-varying delay, partly unknown transition rate and unmeasurable state. The main difficulty is that, a sliding mode surface cannot be designed based on the unknown transition rate and unmeasurable state directly. To overcome this obstacle, the set of modes is firstly divided into two subsets standing for known transition rate subset and unknown one, based on which a state observer is established. A component robust finite-time sliding mode controller is also designed to cope with the effect of partially unknown transition rate. It is illustrated that the reachability, finite-time stability, finite-time boundedness, finite-time H∞ state feedback stabilization of sliding mode dynamics can be ensured despite the unknown transition rate. Finally, the simulation results verify the effectiveness of robust finite time control problem.

  14. The Modeling of Time-Varying Stream Water Age Distributions: Preliminary Investigations with Non-Conservative Solutes

    NASA Astrophysics Data System (ADS)

    Wilusz, D. C.; Harman, C. J.; Ball, W. P.

    2014-12-01

    Modeling the dynamics of chemical transport from the landscape to streams is necessary for water quality management. Previous work has shown that estimates of the distribution of water age in streams, the transit time distribution (TTD), can improve prediction of the concentration of conservative tracers (i.e., ones that "follow the water") based on upstream watershed inputs. A major challenge however has been accounting for climate and transport variability when estimating TDDs at the catchment scale. In this regard, Harman (2014, in review) proposed the Omega modeling framework capable of using watershed hydraulic fluxes to approximate the time-varying TTD. The approach was previously applied to the Plynlimon research watershed in Wales to simulate stream concentration dynamics of a conservative tracer (chloride) including 1/f attenuation of the power spectra density. In this study we explore the extent to which TTDs estimated by the Omega model vary with the concentration of non-conservative tracers (i.e., ones whose concentrations are also affected by transformations and interactions with other phases). First we test the hypothesis that the TTD calibrated in Plynlimon can explain a large part of the variation in non-conservative stream water constituents associated with storm flow (acidity, Al, DOC, Fe) and base flow (Ca, Si). While controlling for discharge, we show a correlation between the percentage of water of different ages and constituent concentration. Second, we test the hypothesis that TTDs help explain variation in stream nitrate concentration, which is of particular interest for pollution control but can be highly non-conservative. We compare simulation runs from Plynlimon and the agricultural Choptank watershed in Maryland, USA. Following a top-down approach, we estimate nitrate concentration as if it were a conservative tracer and examine the structure of residuals at different temporal resolutions. Finally, we consider model modifications to

  15. 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

  16. Characterization and correction of system delays and eddy currents for MR imaging with ultrashort echo-time and time-varying gradients.

    PubMed

    Atkinson, Ian C; Lu, Aiming; Thulborn, Keith R

    2009-08-01

    Reconstruction of high-quality MR images requires precise knowledge of the dynamic gradient magnetic fields used to perform spatial encoding. System delays and eddy currents can perturb the gradient fields in both time and space and significantly degrade the image quality for acquisitions with an ultrashort echo time or with rapidly varying readout gradient waveforms. A technique for simultaneously characterizing and correcting the system delay and linear- and zero-order eddy currents of an MR system is proposed. A single set of calibration scans were used to compute a set of system constants that describe the effects of system delays and eddy currents to enable accurate reconstruction of data collected before uncorrected eddy currents have decayed. The ability of the proposed technique to reproducibly characterize small fixed delays (<50 micros) and short-time constant (<1 ms) eddy currents is demonstrated.

  17. H∞ mode-dependent fault detection filter design for stochastic Markovian jump systems with time-varying delays and parameter uncertainties.

    PubMed

    Zhuang, Guangming; Xia, Jianwei; Chu, Yuming; Chen, Fu

    2014-07-01

    This paper deals with the problem of robust H∞ fault detection for a class of stochastic Markovian jump systems (SMJSs) The aim is to design a linear mode-dependent fault detection filter such that the fault detection system is not only stochastically asymptotically stable in the large, but also satisfies a prescribed H∞-norm level for all admissible uncertainties. By using Lyapunov stability theory and generalized Itô formula, some novel mode-dependent and delay-dependent sufficient conditions in terms of linear matrix inequality (LMI) are proposed to insure the existence of the desired fault detection filter. A simulation example and an industrial nonisothermal continuous stirred tank reactor (CSTR) system are employed to show the effectiveness of the proposed method.

  18. 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.

  19. Characterization of the startup transient electrokinetic flow in rectangular channels of arbitrary dimensions, zeta potential distribution, and time-varying pressure gradient.

    PubMed

    Miller, Andrew; Villegas, Arturo; Diez, F Javier

    2015-03-01

    The solution to the startup transient EOF in an arbitrary rectangular microchannel is derived analytically and validated experimentally. This full 2D transient solution describes the evolution of the flow through five distinct periods until reaching a final steady state. The derived analytical velocity solution is validated experimentally for different channel sizes and aspect ratios under time-varying pressure gradients. The experiments used a time resolved micro particle image velocimetry technique to calculate the startup transient velocity profiles. The measurements captured the effect of time-varying pressure gradient fields derived in the analytical solutions. This is tested by using small reservoirs at both ends of the channel which allowed a time-varying pressure gradient to develop with a time scale on the order of the transient EOF. Results showed that under these common conditions, the effect of the pressure build up in the reservoirs on the temporal development of the transient startup EOF in the channels cannot be neglected. The measurements also captured the analytical predictions for channel walls made of different materials (i.e., zeta potentials). This was tested in channels that had three PDMS and one quartz wall, resulting in a flow with an asymmetric velocity profile due to variations in the zeta potential between the walls. PMID:25502599

  20. Delay-distribution-dependent state estimation for discrete-time stochastic neural networks with random delay.

    PubMed

    Bao, Haibo; Cao, Jinde

    2011-01-01

    This paper is concerned with the state estimation problem for a class of discrete-time stochastic neural networks (DSNNs) with random delays. The effect of both variation range and distribution probability of the time delay are taken into account in the proposed approach. The stochastic disturbances are described in terms of a Brownian motion and the time-varying delay is characterized by introducing a Bernoulli stochastic variable. By employing a Lyapunov-Krasovskii functional, sufficient delay-distribution-dependent conditions are established in terms of linear matrix inequalities (LMIs) that guarantee the existence of the state estimator which can be checked readily by the Matlab toolbox. The main feature of the results obtained in this paper is that they are dependent on not only the bound but also the distribution probability of the time delay, and we obtain a larger allowance variation range of the delay, hence our results are less conservative than the traditional delay-independent ones. One example is given to illustrate the effectiveness of the proposed result. PMID:20950998

  1. Time-varying cosmological term

    NASA Astrophysics Data System (ADS)

    Socorro, J.; D'oleire, M.; Pimentel, Luis O.

    2015-11-01

    We present the case of time-varying cosmological term using the Lagrangian formalism characterized by a scalar field ϕ with standard kinetic energy and arbitrary potential V(ϕ). This model is applied to Friedmann-Robertson-Walker (FRW)cosmology. Exact solutions of the field equations are obtained by a special ansats to solve the Einstein-Klein-Gordon equation and a particular potential for the scalar field and barotropic perfect fluid. We present the evolution on this cosmological term with different scenarios.

  2. Parameter identification in periodic delay differential equations with distributed delay

    NASA Astrophysics Data System (ADS)

    Torkamani, Shahab; Butcher, Eric A.; Khasawneh, Firas A.

    2013-04-01

    In this study, a parameter identification approach for identifying the parameters of a periodic delayed system with distributed delay is introduced based on time series analysis and spectral element analysis. Using this approach the parameters of the distributed delayed system can be identified from the time series of the response of the system. The experimental or numerical data of the response is examined with Floquet theory and time series analysis techniques to estimate a reduced order dynamics, or truncated state space to identify the Floquet multipliers. Parameter identification is then completed using a dynamic map developed for the assumed model of the system which can relate the Floquet multipliers to the unknown parameters in the model. The parameter identification technique is validated numerically for first and second order delay differential equations with distributed delay.

  3. Audio Effects Based on Biorthogonal Time-Varying Frequency Warping

    NASA Astrophysics Data System (ADS)

    Evangelista, Gianpaolo; Cavaliere, Sergio

    2001-12-01

    We illustrate the mathematical background and musical use of a class of audio effects based on frequency warping. These effects alter the frequency content of a signal via spectral mapping. They can be implemented in dispersive tapped delay lines based on a chain of all-pass filters. In a homogeneous line with first-order all-pass sections, the signal formed by the output samples at a given time is related to the input via the Laguerre transform. However, most musical signals require a time-varying frequency modification in order to be properly processed. Vibrato in musical instruments or voice intonation in the case of vocal sounds may be modeled as small and slow pitch variations. Simulation of these effects requires techniques for time-varying pitch and/or brightness modification that are very useful for sound processing. The basis for time-varying frequency warping is a time-varying version of the Laguerre transformation. The corresponding implementation structure is obtained as a dispersive tapped delay line, where each of the frequency dependent delay element has its own phase response. Thus, time-varying warping results in a space-varying, inhomogeneous, propagation structure. We show that time-varying frequency warping is associated to an expansion over biorthogonal sets generalizing the discrete Laguerre basis. Slow time-varying characteristics lead to slowly varying parameter sequences. The corresponding sound transformation does not suffer from discontinuities typical of delay lines based on unit delays.

  4. 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.

  5. 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.

  6. 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.

  7. Components in time-varying graphs

    NASA Astrophysics Data System (ADS)

    Nicosia, Vincenzo; Tang, John; Musolesi, Mirco; Russo, Giovanni; Mascolo, Cecilia; Latora, Vito

    2012-06-01

    Real complex systems are inherently time-varying. Thanks to new communication systems and novel technologies, today it is possible to produce and analyze social and biological networks with detailed information on the time of occurrence and duration of each link. However, standard graph metrics introduced so far in complex network theory are mainly suited for static graphs, i.e., graphs in which the links do not change over time, or graphs built from time-varying systems by aggregating all the links as if they were concurrent in time. In this paper, we extend the notion of connectedness, and the definitions of node and graph components, to the case of time-varying graphs, which are represented as time-ordered sequences of graphs defined over a fixed set of nodes. We show that the problem of finding strongly connected components in a time-varying graph can be mapped into the problem of discovering the maximal-cliques in an opportunely constructed static graph, which we name the affine graph. It is, therefore, an NP-complete problem. As a practical example, we have performed a temporal component analysis of time-varying graphs constructed from three data sets of human interactions. The results show that taking time into account in the definition of graph components allows to capture important features of real systems. In particular, we observe a large variability in the size of node temporal in- and out-components. This is due to intrinsic fluctuations in the activity patterns of individuals, which cannot be detected by static graph analysis.

  8. Components in time-varying graphs.

    PubMed

    Nicosia, Vincenzo; Tang, John; Musolesi, Mirco; Russo, Giovanni; Mascolo, Cecilia; Latora, Vito

    2012-06-01

    Real complex systems are inherently time-varying. Thanks to new communication systems and novel technologies, today it is possible to produce and analyze social and biological networks with detailed information on the time of occurrence and duration of each link. However, standard graph metrics introduced so far in complex network theory are mainly suited for static graphs, i.e., graphs in which the links do not change over time, or graphs built from time-varying systems by aggregating all the links as if they were concurrent in time. In this paper, we extend the notion of connectedness, and the definitions of node and graph components, to the case of time-varying graphs, which are represented as time-ordered sequences of graphs defined over a fixed set of nodes. We show that the problem of finding strongly connected components in a time-varying graph can be mapped into the problem of discovering the maximal-cliques in an opportunely constructed static graph, which we name the affine graph. It is, therefore, an NP-complete problem. As a practical example, we have performed a temporal component analysis of time-varying graphs constructed from three data sets of human interactions. The results show that taking time into account in the definition of graph components allows to capture important features of real systems. In particular, we observe a large variability in the size of node temporal in- and out-components. This is due to intrinsic fluctuations in the activity patterns of individuals, which cannot be detected by static graph analysis. PMID:22757508

  9. 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

  10. 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. PMID:25215786

  11. Modeling distributed axonal delays in mean-field brain dynamics

    NASA Astrophysics Data System (ADS)

    Roberts, J. A.; Robinson, P. A.

    2008-11-01

    The range of conduction delays between connected neuronal populations is often modeled as a single discrete delay, assumed to be an effective value averaging over all fiber velocities. This paper shows the effects of distributed delays on signal propagation. A distribution acts as a linear filter, imposing an upper frequency cutoff that is inversely proportional to the delay width. Distributed thalamocortical and corticothalamic delays are incorporated into a physiologically based mean-field model of the cortex and thalamus to illustrate their effects on the electroencephalogram (EEG). The power spectrum is acutely sensitive to the width of the thalamocortical delay distribution, and more so than the corticothalamic distribution, because all input signals must travel along the thalamocortical pathway. This imposes a cutoff frequency above which the spectrum is overly damped. The positions of spectral peaks in the resting EEG depend primarily on the distribution mean, with only weak dependences on distribution width. Increasing distribution width increases the stability of fixed point solutions. A single discrete delay successfully approximates a distribution for frequencies below a cutoff that is inversely proportional to the delay width, provided that other model parameters are moderately adjusted. A pair of discrete delays together having the same mean, variance, and skewness as the distribution approximates the distribution over the same frequency range without needing parameter adjustment. Delay distributions with large fractional widths are well approximated by low-order differential equations.

  12. 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.

  13. Randomly Distributed Delayed Communication and Coherent Swarm Patterns

    PubMed Central

    Lindley, Brandon; Mier-y-Teran-Romero, Luis; Schwartz, Ira B.

    2013-01-01

    Previously we showed how delay communication between globally coupled self-propelled agents causes new spatio-temporal patterns to arise when the delay coupling is fixed among all agents [1]. In this paper, we show how discrete, randomly distributed delays affect the dynamical patterns. In particular, we investigate how the standard deviation of the time delay distribution affects the stability of the different patterns as well as the switching probability between coherent states. PMID:24309679

  14. Randomly Distributed Delayed Communication and Coherent Swarm Patterns.

    PubMed

    Lindley, Brandon; Mier-Y-Teran-Romero, Luis; Schwartz, Ira B

    2012-01-01

    Previously we showed how delay communication between globally coupled self-propelled agents causes new spatio-temporal patterns to arise when the delay coupling is fixed among all agents [1]. In this paper, we show how discrete, randomly distributed delays affect the dynamical patterns. In particular, we investigate how the standard deviation of the time delay distribution affects the stability of the different patterns as well as the switching probability between coherent states. PMID:24309679

  15. Motion Editing for Time-Varying Mesh

    NASA Astrophysics Data System (ADS)

    Xu, Jianfeng; Yamasaki, Toshihiko; Aizawa, Kiyoharu

    2008-12-01

    Recently, time-varying mesh (TVM), which is composed of a sequence of mesh models, has received considerable interest due to its new and attractive functions such as free viewpoint and interactivity. TVM captures the dynamic scene of the real world from multiple synchronized cameras. However, it is expensive and time consuming to generate a TVM sequence. In this paper, an editing system is presented to reuse the original data, which reorganizes the motions to obtain a new sequence based on the user requirements. Hierarchical motion structure is observed and parsed in TVM sequences. Then, the representative motions are chosen into a motion database, where a motion graph is constructed to connect those motions with smooth transitions. After the user selects some desired motions from the motion database, the best paths are searched by a modified Dijkstra algorithm to achieve a new sequence. Our experimental results demonstrate that the edited sequences are natural and smooth.

  16. 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

  17. 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.

  18. TIME DELAY SYSTEMS WITH DISTRIBUTION DEPENDENT DYNAMICS

    PubMed Central

    Banks, H. T.; Dediu, Sava; Nguyen, Hoan K.

    2009-01-01

    General delay dynamical systems in which uncertainty is present in the form of probability measure dependent dynamics are considered. Several motivating examples arising in biology are discussed. A functional analytic framework for investigating well–posedness (existence, uniqueness and continuous dependence of solutions), inverse problems, sensitivity analysis and approximations of the measures for computational purposes is surveyed. PMID:19865602

  19. TIME DELAY SYSTEMS WITH DISTRIBUTION DEPENDENT DYNAMICS.

    PubMed

    Banks, H T; Dediu, Sava; Nguyen, Hoan K

    2007-01-01

    General delay dynamical systems in which uncertainty is present in the form of probability measure dependent dynamics are considered. Several motivating examples arising in biology are discussed. A functional analytic framework for investigating well-posedness (existence, uniqueness and continuous dependence of solutions), inverse problems, sensitivity analysis and approximations of the measures for computational purposes is surveyed.

  20. Reaching a consensus: a discrete nonlinear time-varying case

    NASA Astrophysics Data System (ADS)

    Saburov, M.; Saburov, K.

    2016-07-01

    In this paper, we have considered a nonlinear protocol for a structured time-varying and synchronous multi-agent system. By means of cubic triple stochastic matrices, we present an opinion sharing dynamics of the multi-agent system as a trajectory of a non-homogeneous system of cubic triple stochastic matrices. We show that the multi-agent system eventually reaches to a consensus if either of the following two conditions is satisfied: (1) every member of the group people has a positive subjective distribution on the given task after some revision steps or (2) all entries of some cubic triple stochastic matrix are positive.

  1. 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.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. Noise Induced Pattern Switching in Randomly Distributed Delayed Swarms.

    PubMed

    Lindley, Brandon; Mier-Y-Teran-Romero, Luis; Schwartz, Ira B

    2013-01-01

    We study the effects of noise on the dynamics of a system of coupled self-propelling particles in the case where the coupling is time-delayed, and the delays are discrete and randomly generated. Previous work has demonstrated that the stability of a class of emerging patterns depends upon all moments of the time delay distribution, and predicts their bifurcation parameter ranges. Near the bifurcations of these patterns, noise may induce a transition from one type of pattern to another. We study the onset of these noise-induced swarm re-organizations by numerically simulating the system over a range of noise intensities and for various distributions of the delays. Interestingly, there is a critical noise threshold above which the system is forced to transition from a less organized state to a more organized one. We explore this phenomenon by quantifying this critical noise threshold, and note that transition time between states varies as a function of both the noise intensity and delay distribution. PMID:25382931

  8. Noise Induced Pattern Switching in Randomly Distributed Delayed Swarms

    PubMed Central

    Lindley, Brandon; Mier-y-Teran-Romero, Luis; Schwartz, Ira B.

    2013-01-01

    We study the effects of noise on the dynamics of a system of coupled self-propelling particles in the case where the coupling is time-delayed, and the delays are discrete and randomly generated. Previous work has demonstrated that the stability of a class of emerging patterns depends upon all moments of the time delay distribution, and predicts their bifurcation parameter ranges. Near the bifurcations of these patterns, noise may induce a transition from one type of pattern to another. We study the onset of these noise-induced swarm re-organizations by numerically simulating the system over a range of noise intensities and for various distributions of the delays. Interestingly, there is a critical noise threshold above which the system is forced to transition from a less organized state to a more organized one. We explore this phenomenon by quantifying this critical noise threshold, and note that transition time between states varies as a function of both the noise intensity and delay distribution. PMID:25382931

  9. 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.

  10. 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 model…

  11. 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.

  12. 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.

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. Stabilizing model predictive control for constrained nonlinear distributed delay systems.

    PubMed

    Mahboobi Esfanjani, R; Nikravesh, S K Y

    2011-04-01

    In this paper, a model predictive control scheme with guaranteed closed-loop asymptotic stability is proposed for a class of constrained nonlinear time-delay systems with discrete and distributed delays. A suitable terminal cost functional and also an appropriate terminal region are utilized to achieve asymptotic stability. To determine the terminal cost, a locally asymptotically stabilizing controller is designed and an appropriate Lyapunov-Krasoskii functional of the locally stabilized system is employed as the terminal cost. Furthermore, an invariant set for locally stabilized system which is established by using the Razumikhin Theorem is used as the terminal region. Simple conditions are derived to obtain terminal cost and terminal region in terms of Bilinear Matrix Inequalities. The method is illustrated by a numerical example.

  18. Time varying networks and the weakness of strong ties.

    PubMed

    Karsai, Márton; Perra, Nicola; Vespignani, Alessandro

    2014-01-01

    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.

  19. Reduction of chemical reaction networks through delay distributions.

    PubMed

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

    2013-03-14

    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.

  20. 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.

  1. Comparative Analysis of Instruments Measuring Time Varying Harmonics

    NASA Astrophysics Data System (ADS)

    Belchior, Fernando Nunes; Ribeiro, Paulo Fernando; Carvalho, Frederico Marques

    2016-08-01

    This paper aims to evaluate the performance of commercial class A and class S power quality (PQ) instruments when measuring time-varying harmonics. By using a high precision programmable voltage and current source, two meters from different manufacturers are analyzed and compared. Three-phase voltage signals are applied to PQ instruments, considering 3 situations of time-varying harmonic distortions, whose harmonic distortion values are in accordance with typical values found in power systems. This work is relevant considering that international standardization documents do not pay much attention to this aspect of harmonic distortion.

  2. Linear photonic technique for fixed and time varying RF phase shifts of radar signals.

    PubMed

    Attygalle, Manik; Stepanov, Dmitrii

    2012-07-30

    A simple linear photonic technique is proposed to achieve fixed or time varying radio-frequency (RF) phase shifts which can be used in applications such as radar signal manipulation. The technique is based on fixing or tuning the wavelength of an RF modulated optical signal within the reflection band of a fiber Bragg grating (FBG) filter with a step group delay profile. The scheme is verified in a realistic simulation to achieve a Doppler shift in a pulsed CW signal return.

  3. 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.

  4. 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

  5. A dynamic p53-mdm2 model with distributed delay

    NASA Astrophysics Data System (ADS)

    Horhat, Raluca; Horhat, Raul Florin

    2014-12-01

    Specific activator and repressor transcription factors which bind to specific regulator DNA sequences, play an important role in gene activity control. Interactions between genes coding such transcripion factors should explain the different stable or sometimes oscillatory gene activities characteristic for different tissues. In this paper, the dynamic P53-Mdm2 interaction model with distributed delays is investigated. Both weak and Dirac kernels are taken into consideration. For Dirac case, the Hopf bifurcation is investigated. Some numerical examples are finally given for justifying the theoretical results.

  6. 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.

  7. Neuronal Mechanisms and Transformations Encoding Time-Varying Signals.

    PubMed

    Petkov, Christopher I; Bendor, Daniel

    2016-08-17

    Sensation in natural environments requires the analysis of time-varying signals. While previous work has uncovered how a signal's temporal rate is represented by neurons in sensory cortex, in this issue of Neuron, new evidence from Gao et al. (2016) provides insights on the underlying mechanisms. PMID:27537481

  8. Mining Graphs for Understanding Time-Varying Volumetric Data.

    PubMed

    Gu, Yi; Wang, Chaoli; Peterka, Tom; Jacob, Robert; Kim, Seung Hyun

    2016-01-01

    A notable recent trend in time-varying volumetric data analysis and visualization is to extract data relationships and represent them in a low-dimensional abstract graph view for visual understanding and making connections to the underlying data. Nevertheless, the ever-growing size and complexity of data demands novel techniques that go beyond standard brushing and linking to allow significant reduction of cognition overhead and interaction cost. In this paper, we present a mining approach that automatically extracts meaningful features from a graph-based representation for exploring time-varying volumetric data. This is achieved through the utilization of a series of graph analysis techniques including graph simplification, community detection, and visual recommendation. We investigate the most important transition relationships for time-varying data and evaluate our solution with several time-varying data sets of different sizes and characteristics. For gaining insights from the data, we show that our solution is more efficient and effective than simply asking users to extract relationships via standard interaction techniques, especially when the data set is large and the relationships are complex. We also collect expert feedback to confirm the usefulness of our approach.

  9. Bayesian classification in a time-varying environment

    NASA Technical Reports Server (NTRS)

    Swain, P. H.

    1978-01-01

    The problem of classifying a pattern based on multiple observation made in a time-varying environment is analyzed. The identity of the pattern may itself change. A Bayesian solution is derived, after which the conditions of the physical situation are invoked to produce a cascade classifier model. Experimental results based on remote sensing data demonstrate the effectiveness of the classifier.

  10. 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.

  11. Holographic flow visualization of time-varying shock waves

    NASA Technical Reports Server (NTRS)

    Decker, A. J.

    1981-01-01

    Rapid-double-exposure, diffuse-illumination holography is evaluated analytically and experimentally as a flow visualization method for time-varying shock waves. Conditions are determined that minimize the distance (localization error) between the surface or curve of interference-fringe localization and the shock surface. Treated specifically are the cases of shock waves in a transonic compressor rotor for which there is laser anemometer data for comparison and shock waves in a flutter cascade.

  12. 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.

  13. 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. PMID:26529462

  14. 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

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

    PubMed Central

    Marathe, A R.; Taylor, D M

    2015-01-01

    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 here also

  16. Contagion dynamics in time-varying metapopulation networks

    NASA Astrophysics Data System (ADS)

    Liu, Su-Yu; Baronchelli, Andrea; Perra, Nicola

    2013-03-01

    The metapopulation framework is adopted in a wide array of disciplines to describe systems of well separated yet connected subpopulations. The subgroups or patches are often represented as nodes in a network whose links represent the migration routes among them. The connections have been so far mostly considered as static, but in general evolve in time. Here we address this case by investigating simple contagion processes on time-varying metapopulation networks. We focus on the SIR process and determine analytically the mobility threshold for the onset of an epidemic spreading in the framework of activity-driven network models. We find profound differences from the case of static networks. The threshold is entirely described by the dynamical parameters defining the average number of instantaneously migrating individuals and does not depend on the properties of the static network representation. Remarkably, the diffusion and contagion processes are slower in time-varying graphs than in their aggregated static counterparts, the mobility threshold being even two orders of magnitude larger in the first case. The presented results confirm the importance of considering the time-varying nature of complex networks.

  17. Contagion dynamics in time-varying metapopulation networks

    NASA Astrophysics Data System (ADS)

    Perra, Nicola; Liu, Suyu; Baronchelli, Andrea

    2014-03-01

    The metapopulation framework is adopted in a wide array of disciplines to describe systems of well separated yet connected subpopulations. The subgroups/patches are often represented as nodes in a network whose links represent the migration routes among them. The connections has been so far mostly considered as static, but in general evolve in time. Here we address this case by investigating simple contagion processes on time-varying metapopulation networks. We focus on the SIR process, and determine analytically the mobility threshold for the onset of an epidemic spreading in the framework of activity-driven network models. We find profound differences from the case of static networks. The threshold is entirely described by the dynamical parameters defining the average number of instantaneously migrating individuals, and does not depend on the properties of the static network representation. Remarkably, the diffusion and contagion processes are slower in time-varying graphs than in their aggregated static counterparts, the mobility threshold been even two orders of magnitude larger in the first case. The presented results confirm the importance of considering the time-varying nature of complex networks.

  18. Energy harvesting under excitations of time-varying frequency

    NASA Astrophysics Data System (ADS)

    Seuaciuc-Osório, Thiago; Daqaq, Mohammed F.

    2010-06-01

    The design and optimization of energy harvesters capable of scavenging energy efficiently from realistic environments require a deep understanding of their transduction under non-stationary and random excitations. Otherwise, their small energy outputs can be further decreased lowering their efficiency and rendering many critical and possibly life saving technologies inefficient. As a first step towards this critical understanding, this effort investigates the response of energy harvesters to harmonic excitations of time-varying frequency. Such excitations can be used to represent the behavior of realistic vibratory environments whose frequency varies or drifts with time. Specifically, we consider a piezoelectric stack-type harvester subjected to a harmonic excitation of constant amplitude and a sinusoidally varying frequency. We analyze the response of the harvester in the fixed-frequency scenario then use the Jacobi-Anger's expansion to analyze the response in the time-varying case. We obtain analytical expressions for the harvester's response, output voltage, and power. In-depth analysis of the attained results reveals that the solution to the more complex time-varying frequency can be understood through a process which "samples" the fixed-frequency response curve at a discrete and fixed frequency interval then multiplies the response by proper weights. Extensive discussions addressing the effect of the excitation parameters on the output power is presented leading to some initial suggestions pertinent to the harvester's design and optimization in the sinusoidally varying frequency case.

  19. 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.

  20. Almost periodic solutions for Lotka-Volterra systems with delays

    NASA Astrophysics Data System (ADS)

    Liang, Yanlai; Li, Lijie; Chen, Lansun

    2009-09-01

    This paper studies a general class of delayed almost periodic Lotka-Volterra system with time-varying delays and distributed delays. By using the definition of almost periodic function, the sufficient conditions for the existence and uniqueness of globally exponentially stable almost periodic solution are obtained. The conditions can be easily reduced to special cases of cooperative systems and competitive systems.

  1. Adaptive probabilistic neural networks for pattern classification in time-varying environment.

    PubMed

    Rutkowski, Leszek

    2004-07-01

    In this paper, we propose a new class of probabilistic neural networks (PNNs) working in nonstationary environment. The novelty is summarized as follows: 1) We formulate the problem of pattern classification in nonstationary environment as the prediction problem and design a probabilistic neural network to classify patterns having time-varying probability distributions. We note that the problem of pattern classification in the nonstationary case is closely connected with the problem of prediction because on the basis of a learning sequence of the length n, a pattern in the moment n + k, k > or = 1 should be classified. 2) We present, for the first time in literature, definitions of optimality of PNNs in time-varying environment. Moreover, we prove that our PNNs asymptotically approach the Bayes-optimal (time-varying) decision surface. 3) We investigate the speed of convergence of constructed PNNs. 4) We design in detail PNNs based on Parzen kernels and multivariate Hermite series.

  2. 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.

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

    PubMed

    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 P(ij)∼r(ij)(-α), where r(ij) is the Manhattan distance. By assigning each shortcut an activity rate subjected to its geometric distance τ(ij)∼r(ij)(-C), long-range links become active intermittently, leading to the time-varying dynamics. We show that for 0time-varying transportation networks. Empirical studies on British Airways and Austrian Airlines provide consistent evidence with our conclusion. PMID:27078380

  4. Stochastic analysis of epidemics on adaptive time varying networks

    NASA Astrophysics Data System (ADS)

    Kotnis, Bhushan; Kuri, Joy

    2013-06-01

    Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an “adaptive threshold,” i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.

  5. Image Cross-Correlation Analysis of Time Varying Flows.

    PubMed

    Marquezin, Cassia A; Ceffa, Nicolò G; Cotelli, Franco; Collini, Maddalena; Sironi, Laura; Chirico, Giuseppe

    2016-07-19

    In vivo studies of blood circulation pathologies have great medical relevance and need methods for the characterization of time varying flows at high spatial and time resolution in small animal models. We test here the efficacy of the combination of image correlation techniques and single plane illumination microscopy (SPIM) in characterizing time varying flows in vitro and in vivo. As indicated by numerical simulations and by in vitro experiments on straight capillaries, the complex analytical form of the cross-correlation function for SPIM detection can be simplified, in conditions of interest for hemodynamics, to a superposition of Gaussian components, easily amenable to the analysis of variable flows. The possibility to select a wide field of view with a good spatial resolution along the collection optical axis and to compute the cross-correlation between regions of interest at varying distances on a single time stack of images allows one to single out periodic flow components from spurious peaks on the cross-correlation functions and to infer the duration of each flow component. We apply this cross-correlation analysis to the blood flow in Zebrafish embryos at 4 days after fertilization, measuring the average speed and the duration of the systolic and diastolic phases.

  6. Evaluating multivariate visualizations on time-varying data

    NASA Astrophysics Data System (ADS)

    Livingston, Mark A.; Decker, Jonathan W.; Ai, Zhuming

    2013-01-01

    Multivariate visualization techniques have been applied to a wide variety of visual analysis tasks and a broad range of data types and sources. Their utility has been evaluated in a modest range of simple analysis tasks. In this work, we extend our previous task to a case of time-varying data. We implemented ve visualizations of our synthetic test data: three previously evaluated techniques (Data-driven Spots, Oriented Slivers, and Attribute Blocks), one hybrid of the rst two that we call Oriented Data-driven Spots, and an implementation of Attribute Blocks that merges the temporal slices. We conducted a user study of these ve techniques. Our previous nding (with static data) was that users performed best when the density of the target (as encoded in the visualization) was either highest or had the highest ratio to non-target features. The time-varying presentations gave us a wider range of density and density gains from which to draw conclusions; we now see evidence for the density gain as the perceptual measure, rather than the absolute density.

  7. 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.

  8. A Time-Varying Effect Model for Intensive Longitudinal Data

    PubMed Central

    Tan, Xianming; Shiyko, Mariya P.; Li, Runze; Li, Yuelin; Dierker, Lisa

    2011-01-01

    Understanding temporal change in human behavior and psychological processes is a central issue in the behavioral sciences. With technological advances, intensive longitudinal data (ILD) are increasingly generated by studies of human behavior that repeatedly administer assessments over time. ILD offer unique opportunities to describe temporal behavioral changes in detail and identify related environmental and psychosocial antecedents and consequences. Traditional analytical approaches impose strong parametric assumptions about the nature of change in the relationship between time-varying covariates and outcomes of interest. This paper introduces time-varying effect models (TVEM) that explicitly model changes in the association between ILD covariates and ILD outcomes over time in a flexible manner. In this article, we describes unique research questions that the TVEM addresses, outline the model-estimation procedure, share a SAS macro for implementing the model, demonstrate model utility with a simulated example, and illustrate model applications in ILD collected as part of a smoking-cessation study to explore the relationship between smoking urges and self-efficacy during the course of the pre- and post- cessation period. PMID:22103434

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

    PubMed

    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 P(ij)∼r(ij)(-α), where r(ij) is the Manhattan distance. By assigning each shortcut an activity rate subjected to its geometric distance τ(ij)∼r(ij)(-C), long-range links become active intermittently, leading to the time-varying dynamics. We show that for 0time-varying transportation networks. Empirical studies on British Airways and Austrian Airlines provide consistent evidence with our conclusion.

  10. Estimation of Time-Varying Coherence and Its Application in Understanding Brain Functional Connectivity

    NASA Astrophysics Data System (ADS)

    Liu, Cheng; Gaetz, William; Zhu, Hongmei

    2010-12-01

    Time-varying coherence is a powerful tool for revealing functional dynamics between different regions in the brain. In this paper, we address ways of estimating evolutionary spectrum and coherence using the general Cohen's class distributions. We show that the intimate connection between the Cohen's class-based spectra and the evolutionary spectra defined on the locally stationary time series can be linked by the kernel functions of the Cohen's class distributions. The time-varying spectra and coherence are further generalized with the Stockwell transform, a multiscale time-frequency representation. The Stockwell measures can be studied in the framework of the Cohen's class distributions with a generalized frequency-dependent kernel function. A magnetoencephalography study using the Stockwell coherence reveals an interesting temporal interaction between contralateral and ipsilateral motor cortices under the multisource interference task.

  11. Linear photonic technique for fixed and time varying RF phase shifts of radar signals.

    PubMed

    Attygalle, Manik; Stepanov, Dmitrii

    2012-07-30

    A simple linear photonic technique is proposed to achieve fixed or time varying radio-frequency (RF) phase shifts which can be used in applications such as radar signal manipulation. The technique is based on fixing or tuning the wavelength of an RF modulated optical signal within the reflection band of a fiber Bragg grating (FBG) filter with a step group delay profile. The scheme is verified in a realistic simulation to achieve a Doppler shift in a pulsed CW signal return. PMID:23038350

  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. Time-varying deconvolution of GPR data in civil engineering

    NASA Astrophysics Data System (ADS)

    Economou, Nikos; Vafidis, Antonis; Hamdan, Hamdan; Kritikakis, George; Andronikidis, Nikos; Dimitriadis, Kleisthenis

    2012-09-01

    Ground Penetrating Radar (GPR) profiles are often used in civil engineering problems. Overlapping reflections from thin subgrade layers are observed when a relatively low frequency antenna is used. An efficient GPR data processing method, which increases the dominant frequency of GPR data and the temporal resolution, is proposed. It is implemented in the t-f domain. The proposed time-varying deconvolution technique avoids the need for both the calculation of an inverse zero-phase whitening operator and subsequently the application of a band-pass filtering. The user must select the dominant frequency of the Ricker wavelet and use the phase of a reference electromagnetic wavelet, which is acquired experimentally, for stationary dephasing. Apart from delineating thin layers, this method reduces the number of antennas for imaging both shallow and deeper layers in civil engineering. The effectiveness of the proposed method is demonstrated through four civil engineering applications.

  14. Chimera states in time-varying complex networks

    NASA Astrophysics Data System (ADS)

    Buscarino, Arturo; Frasca, Mattia; Gambuzza, Lucia Valentina; Hövel, Philipp

    2015-02-01

    Chimera states have been recently found in a variety of different coupling schemes and geometries. In most cases, the underlying coupling structure is considered to be static, while many realistic systems display significant temporal changes in the pattern of connectivity. In this work we investigate a time-varying network made of two coupled populations of Kuramoto oscillators, where the links between the two groups are considered to vary over time. As a main result we find that the network may support stable, breathing, and alternating chimera states. We also find that, when the rate of connectivity changes is fast, compared to the oscillator dynamics, the network may be described by a low-dimensional system of equations. Unlike in the static heterogeneous case, the onset of alternating chimera states is due to the presence of fluctuations, which may be induced either by the finite size of the network or by large switching times.

  15. Review of patient safety in time-varying gradient fields.

    PubMed

    Schaefer, D J; Bourland, J D; Nyenhuis, J A

    2000-07-01

    In magnetic resonance, time-varying gradient magnetic fields (dB/dt) may stimulate nerves or muscles by inducing electric fields in patients. Models predicted mean peripheral nerve and cardiac stimulation thresholds. For gradient ramp durations of less than a few milliseconds, mean peripheral nerve stimulation is a safe indicator of high dB/dt. At sufficient amplitudes, peripheral nerve stimulation is perceptible (i.e., tingling or tapping sensations). Magnetic fields from simultaneous gradient axes combine almost as a vector sum to produce stimulation. Patients may become uncomfortable at amplitudes 50%-100% above perception thresholds. In dogs, respiratory stimulation has been induced at about 300% of mean peripheral nerve thresholds. Cardiac stimulation has been induced in dogs by small gradient coils at thresholds near Reilly's predictions. Cardiac stimulation required nearly 80 times the energy needed to produce nerve stimulation in dogs. Nerve and cardiac stimulation thresholds for dogs were unaffected by 1.5-T magnetic fields.

  16. 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.

  17. 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.

  18. 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.

  19. Time-Varying Ankle Mechanical Impedance During Human Locomotion.

    PubMed

    Lee, Hyunglae; Hogan, Neville

    2015-09-01

    In human locomotion, we continuously modulate joint mechanical impedance of the lower limb (hip, knee, and ankle) either voluntarily or reflexively to accommodate environmental changes and maintain stable interaction. Ankle mechanical impedance plays a pivotal role at the interface between the neuro-mechanical system and the physical world. This paper reports, for the first time, a characterization of human ankle mechanical impedance in two degrees-of-freedom simultaneously as it varies with time during walking. Ensemble-based linear time-varying system identification methods implemented with a wearable ankle robot, Anklebot, enabled reliable estimation of ankle mechanical impedance from the pre-swing phase through the entire swing phase to the early-stance phase. This included heel-strike and toe-off, key events in the transition from the swing to stance phase or vice versa. Time-varying ankle mechanical impedance was accurately approximated by a second order model consisting of inertia, viscosity, and stiffness in both inversion-eversion and dorsiflexion-plantarflexion directions, as observed in our previous steady-state dynamic studies. We found that viscosity and stiffness of the ankle significantly decreased at the end of the stance phase before toe-off, remained relatively constant across the swing phase, and increased around heel-strike. Closer investigation around heel-strike revealed that viscosity and stiffness in both planes increased before heel-strike occurred. This finding is important evidence of "pretuning" by the central nervous system. In addition, viscosity and stiffness were greater in the sagittal plane than in the frontal plane across all subgait phases, except the early stance phase. Comparison with previous studies and implications for clinical study of neurologically impaired patients are provided.

  20. 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. PMID:26489699

  1. The delay time distribution of massive double compact star mergers

    NASA Astrophysics Data System (ADS)

    Mennekens, N.; Vanbeveren, D.

    2016-05-01

    To investigate the temporal evolution of binary populations, in general, and double compact-star binaries and mergers, in particular, within a galactic evolution context, a very straightforward method is obviously to implement a detailed binary evolutionary model in a galactic chemical evolution code. To our knowledge, the Brussels galactic chemical evolution code is the only one that fully and consistently accounts for the important effects of interacting binaries on the predictions of chemical evolution. With a galactic code that does not explicitly include binaries, the temporal evolution of the population of double compact star binaries and mergers can be estimated with reasonable accuracy if the delay time distribution (DTD) for these mergers is available. The DTD for supernovae type Ia has been studied extensively in the past decade. In the present paper we present the DTD for merging double neutron-star binaries and mixed systems consisting of a neutron star and a black hole. The latter mergers are very promising sites for producing r-process elements, and the DTDs can be used to study the galactic evolution of these elements with a code that does not explicitly account for binaries.

  2. Acoustic thermometric reconstruction of a time-varying temperature profile

    NASA Astrophysics Data System (ADS)

    Anosov, A. A.; Kazanskii, A. S.; Mansfel'd, A. D.; Sharakshane, A. S.

    2016-03-01

    The time-varying temperature profiles were reconstructed in an experiment using a thermal acoustic radiation receiving array containing 14 sensors. The temperature was recovered by performing similar experiments using plasticine, as well as in vivo with a human hand. Plasticine preliminarily heated up to 36.5°C and a human hand were placed into water for 50 s at a temperature of 20°C. The core temperature of the plasticine was independently measured using thermocouples. The spatial resolution of the reconstruction in the lateral direction was determined by the distance between neighboring sensors and was equal to10 mm; the averaging time was 10 s. The error in reconstructing the core temperature determined in the experiment with plasticine was 0.5 K. The core temperature of the hand changed with time (in 50 s it decreased from 35 to 34°C) and space (the mean square deviation was 1.5 K). The experiment with the hand revealed that multichannel detection of thermal acoustic radiation using a compact 45 × 36 mm array to reconstruct the temperature profile could be performed during medical procedures.

  3. 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.

  4. 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.

  5. Robust algorithm for estimation of time-varying transfer functions.

    PubMed

    Zou, Rui; Chon, Ki H

    2004-02-01

    We introduce a new method to estimate reliable time-varying (TV) transfer functions (TFs) and TV impulse response functions. The method is based on TV autoregressive moving average models in which the TV parameters are accurately obtained using the optimal parameter search method which we have previously developed. The new method is more accurate than the recursive least-squares (RLS), and remains robust even in the case of significant noise contamination. Furthermore, the new method is able to track dynamics that change abruptly, which is certainly a deficiency of the RLS. Application of the new method to renal blood pressure and flow revealed that hypertensive rats undergo more complex and TV autoregulation in maintaining stable blood flow than do normotensive rats. This observation has not been previously revealed using time-invariant TF analyses. The newly developed approach may promote the broader use of TV system identification in studies of physiological systems and makes linear and nonlinear TV modeling possible in certain cases previously thought intractable. PMID:14765694

  6. 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.

  7. Delay-dependent exponential state estimators for stochastic neural networks of neutral type with both discrete and distributed delays

    NASA Astrophysics Data System (ADS)

    Wang, Tong; Ding, Yongsheng; Zhang, Lei; Hao, Kuangrong

    2015-03-01

    This paper considered the state estimation for stochastic neural networks of neutral type with discrete and distributed delays. By using available output measurements, the state estimator can approximate the neuron states, and the asymptotic property of the state error is mean square exponential stable and also almost surely exponential stable in the presence of discrete and distributed delays. Under the Lipschitz assumptions for the activation functions and the measurement nonlinearity, a delay-dependent linear matrix inequality (LMI) criterion is proposed to guarantee the existence of the desired estimators by constructing an appropriate Lyapunov-Krasovskii function. It is shown that the existence conditions and the explicit expression of the state estimator can be parameterised in terms of the solution to a LMI. Finally, two numerical examples are presented to demonstrate the validity of the theoretical results and show that the theorem can provide less conservative conditions.

  8. Statistical signatures of geomagnetic storms with reference to delay distribution

    NASA Astrophysics Data System (ADS)

    Aslam, A. M.; Gwal, Ashok Kumar

    2016-07-01

    This paper presents a statistical study on the nature and association of time delay (between IMF Bz and Dst) with various solar wind parameters and Inter planetary Magnetic field components. The study integrally covers all (634 storms) the geomagnetic storms observed during 1996 to 2011. We have calculated the time delay (∆T) between the peak values of IMF Bz and minimum Dst for each event and statistically investigated its relation with various solar wind parameters and IMF. For this analysis we have taken Solar wind parameters; Velocity, Density, Plasma beta and Temperature as well as IMF Bz, into consideration. We have categorized the storms into three categories based on the Dst Index as weak (-30nT ≤ Dst ≤ -50nT), moderate (-50nT ≤ Dst ≤ -100nT) and intense (Dst ≤ -100nT) storms. The relation of delay with solar wind parameters and IMF components were studied separately for different classes of storms and for different delays viz. 0,1,2,3,4 (hours). From our analysis we are able to draw some interesting inferences. The fact, that the characteristic feature describing the geoeffectiveness of the IMF is its z-component; Bz, and the electric field component -V× Bz, stands true for all delay classes of the storms. The time delay (∆T) between peak values of IMF Bz and minimum Dst can vary in a wide range and mostly varies from 0-10 hours. However, it was found that a major percentage (~80 %) of the storms have a 0 - 4 hour delay. Meanwhile Temperature, density and plasma beta seems to have no significant association with the storm intensity.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. Exact and Heuristic Methods for Network Completion for Time-Varying Genetic Networks

    PubMed Central

    Nakajima, Natsu

    2014-01-01

    Robustness in biological networks can be regarded as an important feature of living systems. A system maintains its functions against internal and external perturbations, leading to topological changes in the network with varying delays. To understand the flexibility of biological networks, we propose a novel approach to analyze time-dependent networks, based on the framework of network completion, which aims to make the minimum amount of modifications to a given network so that the resulting network is most consistent with the observed data. We have developed a novel network completion method for time-varying networks by extending our previous method for the completion of stationary networks. In particular, we introduce a double dynamic programming technique to identify change time points and required modifications. Although this extended method allows us to guarantee the optimality of the solution, this method has relatively low computational efficiency. In order to resolve this difficulty, we developed a heuristic method for speeding up the calculation of minimum least squares errors. We demonstrate the effectiveness of our proposed methods through computational experiments using synthetic data and real microarray gene expression data. The results indicate that our methods exhibit good performance in terms of completing and inferring gene association networks with time-varying structures. PMID:24738067

  14. 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.

  15. 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.

  16. Delayed feedback control of unstable steady states with high-frequency modulation of the delay.

    PubMed

    Gjurchinovski, Aleksandar; Jüngling, Thomas; Urumov, Viktor; Schöll, Eckehard

    2013-09-01

    We analyze the stabilization of unstable steady states by delayed feedback control with a periodic time-varying delay in the regime of a high-frequency modulation of the delay. The average effect of the delayed feedback term in the control force is equivalent to a distributed delay in the interval of the modulation, and the obtained distribution depends on the type of the modulation. In our analysis we use a simple generic normal form of an unstable focus, and investigate the effects of phase-dependent coupling and the influence of the control loop latency on the controllability. In addition, we have explored the influence of the modulation of the delays in multiple delay feedback schemes consisting of two independent delay lines of Pyragas type. A main advantage of the variable delay is the considerably larger domain of stabilization in parameter space.

  17. Recurrence of particles in static and time varying oval billiards

    NASA Astrophysics Data System (ADS)

    Leonel, Edson D.; Dettmann, Carl P.

    2012-04-01

    Dynamical properties are studied for escaping particles, injected through a hole in an oval billiard. The dynamics is considered for both static and periodically moving boundaries. For the static boundary, two different decays for the recurrence time distribution were observed after exponential decay for short times: A changeover to: (i) power law or; (ii) stretched exponential. Both slower decays are due to sticky orbits trapped near KAM islands, with the stretched exponential apparently associated with a single group of large islands. For time dependent case, survival probability leads to the conclusion that sticky orbits are less evident compared with the static case.

  18. Low-delay center-bridged and distributed combining schemes for multipoint videoconferencing

    NASA Astrophysics Data System (ADS)

    Chen, Ting-Chung; Wang, Wen-deh

    1994-09-01

    Multipoint videoconferencing is a natural evolution of two-point videoconferencing and can increase its value to users. Currently, ITU-T's SG8 and SG15 are working on multipoint control related issues; ANSI's T1A1.5 is also working in this area. The video coding and related communication standards of the upcoming MPEG4 and H.26P will all include multipoint communication capability. This paper investigates transport structures and the associated combining schemes that can be used to support multipoint videoconferencing. Since low delay is a major issue for multipoint interactive communications, a distributed structure which renders the lowest delay with many other system advantages is especially investigated. We first analyze the insertion delay of a QCIF combiner bridge which have been proposing for multipoint videoconferencing. Partial input-output pipelining has been used to reduce the delay. To reduce the insertion delay caused by unevenly distributed inputs, a parallel parsing scheme is proposed. This parallel parsing scheme allows low complexity inputs not to be held up by high complexity inputs and can reduce insertion delay significantly. An efficient delay- reduction algorithm using intraslice coding was also cited in a previous proposal. As a comparison, we describe low delay pel-domain transcoding schemes which have similar delay performance with coded-domain combining but have much higher complexities. We also describe a recent proposal which eliminates most of the insertion delay but which require major changes to existing standards and encoder and decoder implementations. The performance of a distributed transport structure in providing multipoint video services is then investigated. Using the face that bandwidth usage is an important factor in estimating network complexity, it is shown that a distributed transport structure saves 40 to 62.5% bandwidth for a 4-point conferencing and also renders the shortest delay when compared with other center

  19. 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.

  20. 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.

  1. Extension of the spectral element method for stability analysis of time-periodic delay-differential equations with multiple and distributed delays

    NASA Astrophysics Data System (ADS)

    Lehotzky, David; Insperger, Tamas; Stepan, Gabor

    2016-06-01

    The spectral element method was introduced by Khasawneh and Mann (2013) for the stability analysis of time-periodic delay-differential equations (DDEs) with multiple delays. In this paper, this method is generalized for time-periodic DDEs with multiple delays and distributed delay. For this general case, an explicit formula is given for the construction of the matrix approximation of the monodromy operator. The derived formula enables the algorithmic application of the method to DDEs with general combinations of delays for arbitrary point sets and test functions. Stability analysis is demonstrated for specific case studies, and the computation code is provided for a complex example.

  2. 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.

  3. 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.

  4. 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.

  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. 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.

  7. A method for skew-free distribution of digital signals using matched variable delay lines

    NASA Astrophysics Data System (ADS)

    Knight, Thomas; Wu, Henry

    1992-03-01

    The ability to distribute signals to all parts of a circuit with precisely controlled and known delays is essential in large, high-speed digital systems. We present a technique by which a signal driver can adjust the arrival time of the signal at the end of the wire using a pair of matched variable delay lines. We show how this idea can be implemented requiring no extra wiring, and how it can be extended to distribute signals skew-free to receivers along the signal run as well as the receiving end. We demonstrate how this scheme can be implemented as part of the pad and scan logic of a VLSI chip.

  8. Passivity analysis for memristor-based recurrent neural networks with discrete and distributed delays.

    PubMed

    Guodong Zhang; Yi Shen; Quan Yin; Junwei Sun

    2015-01-01

    In this paper, based on the knowledge of memristor and recurrent neural networks (RNNs), the model of the memristor-based RNNs with discrete and distributed delays is established. By constructing proper Lyapunov functionals and using inequality technique, several sufficient conditions are given to ensure the passivity of the memristor-based RNNs with discrete and distributed delays in the sense of Filippov solutions. The passivity conditions here are presented in terms of linear matrix inequalities, which can be easily solved by using Matlab Tools. In addition, the results of this paper complement and extend the earlier publications. Finally, numerical simulations are employed to illustrate the effectiveness of the obtained results.

  9. Synchronization-desynchronization transitions in complex networks: an interplay of distributed time delay and inhibitory nodes.

    PubMed

    Wille, Carolin; Lehnert, Judith; Schöll, Eckehard

    2014-09-01

    We investigate the combined effects of distributed delay and the balance between excitatory and inhibitory nodes on the stability of synchronous oscillations in a network of coupled Stuart-Landau oscillators. To this end a symmetric network model is proposed for which the stability can be investigated analytically. It is found that beyond a critical inhibition ratio, synchronization tends to be unstable. However, increasing distributional widths can counteract this trend, leading to multiple resynchronization transitions at relatively high inhibition ratios. The extended applicability of the results is confirmed by numerical studies on asymmetrically perturbed network topologies. All investigations are performed on two distribution types, a uniform distribution and a Γ distribution.

  10. Preserved calibration of persistence based on delay-timing distribution during sleep deprivation.

    PubMed

    Massar, Stijn A A; Chee, Michael W L

    2015-12-01

    We frequently encounter decisions where we have to determine whether to wait for a certain reward delayed for an uncertain duration or to move on. The appropriate decision depends upon the underlying temporal distribution of the delay. With some distributions it is best to be completely persistent, whereas in others it is more appropriate to abandon waiting after a certain period of time. The current study examined whether the ability to form temporal expectations and adjust persistence accordingly is compromised by sleep deprivation. Participants performed a willingness-to-wait task either in a well-rested state or after a night of total sleep deprivation. Participants had to decide either to wait for a larger reward or to abandon waiting in favour of a smaller immediate reward. Delays were drawn from either a uniform distribution, where being persistent yields maximal returns, or from a heavy-tailed distribution, where occasional long delays render full persistence suboptimal. In spite of increased sleepiness and decreased vigilance, sleep-deprived participants were able to adjust waiting time appropriate to the experienced timing distribution. Additionally, sleep deprivation did not affect the foreperiod effect, indicating intact perception of conditional probability of temporal events and ability to adjust preparation accordingly. PMID:26179859

  11. Preserved calibration of persistence based on delay-timing distribution during sleep deprivation.

    PubMed

    Massar, Stijn A A; Chee, Michael W L

    2015-12-01

    We frequently encounter decisions where we have to determine whether to wait for a certain reward delayed for an uncertain duration or to move on. The appropriate decision depends upon the underlying temporal distribution of the delay. With some distributions it is best to be completely persistent, whereas in others it is more appropriate to abandon waiting after a certain period of time. The current study examined whether the ability to form temporal expectations and adjust persistence accordingly is compromised by sleep deprivation. Participants performed a willingness-to-wait task either in a well-rested state or after a night of total sleep deprivation. Participants had to decide either to wait for a larger reward or to abandon waiting in favour of a smaller immediate reward. Delays were drawn from either a uniform distribution, where being persistent yields maximal returns, or from a heavy-tailed distribution, where occasional long delays render full persistence suboptimal. In spite of increased sleepiness and decreased vigilance, sleep-deprived participants were able to adjust waiting time appropriate to the experienced timing distribution. Additionally, sleep deprivation did not affect the foreperiod effect, indicating intact perception of conditional probability of temporal events and ability to adjust preparation accordingly.

  12. The rates and time-delay distribution of multiply imaged supernovae behind lensing clusters

    SciTech Connect

    Li, Xue; Hjorth, Jens; Richard, Johan E-mail: jens@dark-cosmology.dk

    2012-11-01

    Time delays of gravitationally lensed sources can be used to constrain the mass model of a deflector and determine cosmological parameters. We here present an analysis of the time-delay distribution of multiply imaged sources behind 17 strong lensing galaxy clusters with well-calibrated mass models. We find that for time delays less than 1000 days, at z = 3.0, their logarithmic probability distribution functions are well represented by P(log Δt) = 5.3 × 10{sup −4}Δt{sup β-tilde}/M{sub 250}{sup 2β-tilde}, with β-tilde = 0.77, where M{sub 250} is the projected cluster mass inside 250 kpc (in 10{sup 14}M{sub ☉}), and β-tilde is the power-law slope of the distribution. The resultant probability distribution function enables us to estimate the time-delay distribution in a lensing cluster of known mass. For a cluster with M{sub 250} = 2 × 10{sup 14}M{sub ☉}, the fraction of time delays less than 1000 days is approximately 3%. Taking Abell 1689 as an example, its dark halo and brightest galaxies, with central velocity dispersions σ≥500kms{sup −1}, mainly produce large time delays, while galaxy-scale mass clumps are responsible for generating smaller time delays. We estimate the probability of observing multiple images of a supernova in the known images of Abell 1689. A two-component model of estimating the supernova rate is applied in this work. For a magnitude threshold of m{sub AB} = 26.5, the yearly rate of Type Ia (core-collapse) supernovae with time delays less than 1000 days is 0.004±0.002 (0.029±0.001). If the magnitude threshold is lowered to m{sub AB} ∼ 27.0, the rate of core-collapse supernovae suitable for time delay observation is 0.044±0.015 per year.

  13. 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.

  14. Signal power distribution in time delay in Tokyo City experimental sites

    NASA Astrophysics Data System (ADS)

    Hayakawa, M.; Katz, D.; Blaunstein, N.

    2008-06-01

    This paper presents experiments carried out in the city of Tokyo in two types of built-up environments. One environment is characterized by a straight-crossing street plan with buildings randomly lining the streets and the terminal antennas located at the line of sight (LOS) and quasi-LOS conditions along the streets. The second built-up area is characterized by straight-crossing streets with non-LOS (NLOS) conditions caused by the railway station and administrative buildings surrounding the terminal antennas. The time delay signal strength distributions obtained experimentally are presented for both multipath urban channels These test experiments are used to study whether any propagation modeling can predict the time delay distribution of signal power. Our theoretical framework is based on the corresponding crossing-street waveguide model taking into account the Poisson statistics for buildings randomly lining each street. The proposed analytical formulas are analyzed for different parameters of the built-up terrain, such as the street width, the average height of buildings, the terminal antenna heights with respect to the rooftops of buildings lining a street, and the gaps (slits) between the buildings. Then a comparison between the proposed theoretical model and experimental data is presented, which indicates a satisfactory agreement between the theoretical and experimental prediction of signal power distribution in the time delay domain. So, our modeling can be used as a promising predictor for the time delay distribution in the microcellular propagation environment.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Changes of the time-varying percentiles of daily extreme temperature in China

    NASA Astrophysics Data System (ADS)

    Li, Bin; Chen, Fang; Xu, Feng; Wang, Xinrui

    2016-09-01

    Identifying the air temperature frequency distributions and evaluating the trends in time-varying percentiles are very important for climate change studies. In order to get a better understanding of the recent temporal and spatial pattern of the temperature changes in China, we have calculated the trends in temporal-varying percentiles of the daily extreme air temperature firstly. Then we divide all the stations to get the spatial patterns for the percentile trends using the average linkage cluster analysis method. To make a comparison, the shifts of trends percentile frequency distribution from 1961-1985 to 1986-2010 are also examined. Important results in three aspects have been achieved: (1) In terms of the trends in temporal-varying percentiles of the daily extreme air temperature, the most intense warming for daily maximum air temperature (Tmax) was detected in the upper percentiles with a significant increasing tendency magnitude (>2.5 °C/50year), and the greatest warming for daily minimum air temperature (Tmin) occurred with very strong trends exceeding 4 °C/50year. (2) The relative coherent spatial patterns for the percentile trends were found, and stations for the whole country had been divided into three clusters. The three primary clusters were distributed regularly to some extent from north to south, indicating the possible large influence of the latitude. (3) The most significant shifts of trends percentile frequency distribution from 1961-1985 to 1986-2010 was found in Tmax. More than half part of the frequency distribution show negative trends less than -0.5 °C/50year in 1961-1985, while showing trends less than 2.5 °C/50year in 1986-2010.

  20. 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.

  1. 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.

  2. Performance of a weighing rain gauge under laboratory simulated time-varying reference rainfall rates

    NASA Astrophysics Data System (ADS)

    Colli, M.; Lanza, L. G.; La Barbera, P.

    2013-09-01

    The available calibration experiences about rain intensity gauges relying on the weighing measuring principle are based on laboratory tests performed under constant reference flow rate conditions. Although the Weighing Gauges (WG) do provide better performance than more traditional Tipping Bucket Rain Gauges (TBR) under constant reference flow rates, dynamic effects do impact on the accuracy of WG measurements under real-world/time-varying rainfall conditions. The most relevant biases are due to the response time of the measurement system and the derived systematic delay in assessing the exact weight of the volume of cumulated precipitation collected in the container. This delay assumes a relevant role in case high resolution rainfall intensity (RI) time series are sought from the instrument, as is the case of many hydrologic and meteo-climatic applications (the one-minute time resolution recommended by the WMO for rainfall intensity measurements is here assumed). A significant sampling error is also attributable to some kind of weighing gauge, which affects the low intensity range as well. A laboratory investigation of the accuracy and precision of a modern weighing gauge manufactured by OTT (Pluvio2) under unsteady-state reference RI conditions is here addressed. Three different laboratory test conditions are applied: single and double step variations of the reference flow rate and a simulated real-world event. The preliminary development and validation of a suitable rainfall simulator for the generation of time-variable reference intensities is presented. The generator is demonstrated to have a sufficiently short time response with respect to the expected instrument behavior in order to ensure effective comparison of the measured vs. reference intensities. The measurements obtained from the WG are compared with those derived from a traditional TBR (manufactured by Casella) under the same laboratory conditions. The TBR measurements have been corrected to account

  3. 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. PMID:23767662

  4. Exact reconstruction analysis/synthesis filter banks with time-varying filters

    NASA Technical Reports Server (NTRS)

    Arrowood, J. L., Jr.; Smith, M. J. T.

    1993-01-01

    This paper examines some of the analysis/synthesis issues associated with FIR time-varying filter banks where the filter bank coefficients are allowed to change in response to the input signal. Several issues are identified as being important in order to realize performance gains from time-varying filter banks in image coding applications. These issues relate to the behavior of the filters as transition from one set of filter banks to another occurs. Lattice structure formulations for the time varying filter bank problem are introduced and discussed in terms of their properties and transition characteristics.

  5. A neural observer with time-varying learning rate: analysis and applications.

    PubMed

    Gurubel, K J; Alanis, A Y; Sanchez, E N; Carlos-Hernandez, S

    2014-02-01

    In this paper, a reduced order neural observer (RONO) with a time-varying learning rate is proposed. The proposed scheme is based on a discrete-time recurrent high order neural network (RHONN) trained with an extended Kalman filter (EKF)-based algorithm. A time-varying learning rate is designed in order to improve the learning of the neuronal network in presence of disturbances and parameter variations. This work includes the stability proof of the time-varying learning. The applicability of the developed observer is illustrated via simulations for a nonlinear anaerobic digestion process.

  6. 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.

  7. Recurrent event data analysis with intermittently observed time-varying covariates.

    PubMed

    Li, Shanshan; Sun, Yifei; Huang, Chiung-Yu; Follmann, Dean A; Krause, Richard

    2016-08-15

    Although recurrent event data analysis is a rapidly evolving area of research, rigorous studies on estimation of the effects of intermittently observed time-varying covariates on the risk of recurrent events have been lacking. Existing methods for analyzing recurrent event data usually require that the covariate processes are observed throughout the entire follow-up period. However, covariates are often observed periodically rather than continuously. We propose a novel semiparametric estimator for the regression parameters in the popular proportional rate model. The proposed estimator is based on an estimated score function where we kernel smooth the mean covariate process. We show that the proposed semiparametric estimator is asymptotically unbiased, normally distributed, and derives the asymptotic variance. Simulation studies are conducted to compare the performance of the proposed estimator and the simple methods carrying forward the last covariates. The different methods are applied to an observational study designed to assess the effect of group A streptococcus on pharyngitis among school children in India. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26887664

  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. Nonlinear time-varying potential bistable energy harvesting from human motion

    NASA Astrophysics Data System (ADS)

    Cao, Junyi; Wang, Wei; Zhou, Shengxi; Inman, Daniel J.; Lin, Jing

    2015-10-01

    A theoretical and experimental investigation into nonlinear bistable energy harvesting with time-varying potential energy is presented. The motivation for examining time-varying potentials comes from the desire to harvest energy from human motion. Time-varying potential energy function of bistable oscillator with respect to the swing angle are established to derive the governing electromechanical model for harvesting vibration energy from the swaying motion during human walking or running. Numerical simulations show good agreement with the experimental potential energy function under different swing angles. Various motion speed treadmill tests are performed to demonstrate the advantage of time-varying bistable harvesters over linear and monostable ones in harvesting energy from human motion.

  11. A shortest path algorithm for satellite time-varying topological network

    NASA Astrophysics Data System (ADS)

    Zhang, Tao; Liu, Zhongkan; Zhuang, Jun

    2005-11-01

    Mobile satellite network is a special time-varying network. It is different from the classical fixed network and other time-dependent networks which have been studied. Therefore some classical network theories, such as the shortest path algorithm, can not be applied to it availably. However, no study about its shortest path problem has been done. In this paper, based on the proposed model of satellite time-varying topological network, the classical shortest path algorithm of fixed network, such as the Dijkstra algorithm, is proved to be restrictive when it is applied in satellite network. Here, a novel shortest path algorithm for satellite time-varying topological network is given and optimized. Correlative simulation indicates that this algorithm can be effectively applied to the satellite time-varying topological network.

  12. 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.

  13. Users manual for linear Time-Varying Helicopter Simulation (Program TVHIS)

    NASA Technical Reports Server (NTRS)

    Burns, M. R.

    1979-01-01

    A linear time-varying helicopter simulation program (TVHIS) is described. The program is designed as a realistic yet efficient helicopter simulation. It is based on a linear time-varying helicopter model which includes rotor, actuator, and sensor models, as well as a simulation of flight computer logic. The TVHIS can generate a mean trajectory simulation along a nominal trajectory, or propagate covariance of helicopter states, including rigid-body, turbulence, control command, controller states, and rigid-body state estimates.

  14. Arbitrary eigenvalue assignments for linear time-varying multivariable control systems

    NASA Technical Reports Server (NTRS)

    Nguyen, Charles C.

    1987-01-01

    The problem of eigenvalue assignments for a class of linear time-varying multivariable systems is considered. Using matrix operators and canonical transformations, it is shown that a time-varying system that is 'lexicography-fixedly controllable' can be made via state feedback to be equivalent to a time-invariant system whose eigenvalues are arbitrarily assignable. A simple algorithm for the design of the state feedback is provided.

  15. Design of reduced-order state estimators for linear time-varying multivariable systems

    NASA Technical Reports Server (NTRS)

    Nguyen, Charles C.

    1987-01-01

    The design of reduced-order state estimators for linear time-varying multivariable systems is considered. Employing the concepts of matrix operators and the method of canonical transformations, this paper shows that there exists a reduced-order state estimator for linear time-varying systems that are 'lexicography-fixedly observable'. In addition, the eigenvalues of the estimator can be arbitrarily assigned. A simple algorithm is proposed for the design of the state estimator.

  16. 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

  17. Effects analysis of time-varying or repeated exposures in aquatic ecological risk assessment of agrochemicals.

    PubMed

    Reinert, Kevin H; Giddings, Jeffrey M; Judd, Laura

    2002-09-01

    Exposure to agrochemicals in the aquatic environment often occurs as time-varying or repeated pulses. Time-varying exposures may occur due to runoff events and spray drift associated with precipitation and application events. Hydrologic dilution, dispersion, and degradation also produce pulsed exposures. Standard laboratory toxicity tests using constant exposure concentrations typically do not investigate the toxicity of time-varying or repeated exposures. Detoxification, elimination, and recovery may occur within organisms or populations during the periods between exposures. The difficulty of estimating effects of realistic time-varying exposures from measurements made under constant exposure conditions is often an important source of uncertainty in ecological risk assessment of pesticides. This article discusses the criteria and tools for deciding whether time-varying exposures are relevant in a particular risk assessment, approaches for laboratory toxicity testing with time-varying exposure, modeling approaches for addressing effects oftime-varying exposure, deterministic and probabilistic ecological risk characterization of time-varyingexposures and toxicity, and uncertainty analysis.

  18. 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.

  19. Multi-Moded RF Delay Line Distribution System (MDLDS) for the Next Linear Collider

    NASA Astrophysics Data System (ADS)

    Nantista, C. D.

    2002-01-01

    The Delay Line Distribution System (DLDS) is an alternative to conventional pulse compression, which enhances the peak power of rf sources while matching the long pulse of those sources to the shorter filling time of accelerator structures. We present an implementation of this scheme that combines pairs of parallel delay lines of the system into single lines. 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 from the delay line using mode-selective extractors, each of which extracts a 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.

  20. Multimoded rf delay line distribution system for the Next Linear Collider

    NASA Astrophysics Data System (ADS)

    Tantawi, S. G.; Nantista, C.; Kroll, N.; Li, Z.; Miller, R.; Ruth, R.; Wilson, P.; Neilson, J.

    2002-03-01

    The delay line distribution system is an alternative to conventional pulse compression, which enhances the peak power of rf sources while matching the long pulse of those sources to the shorter filling time of accelerator structures. We present an implementation of this scheme that combines pairs of parallel delay lines of the system into single lines. The power of several sources is combined into a single waveguide delay line using a multimode launcher. The output mode of the launcher is determined by the phase coding of the input signals. The combined power is extracted from the delay line using mode-selective extractors, each of which extracts a 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 Next Linear Collider design while maintaining high efficiency.

  1. A Multi-moded Delay Line RF Distribution System for the Next = Linear Collider

    NASA Astrophysics Data System (ADS)

    Tantawi, Sami

    1998-04-01

    The Delay Line Distribution System (DLDS) (H. Mizuno, Y. Otake, "A New Rf Power Distribution System For X Band Linac Equivalent To An Rf Pulse Compression Scheme Of Factor 2**N," 17th International Linac Conference (LINAC94), Tsukuba, Japan, Aug 21 - 26, 1994) 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 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 for the high-gradient linacs of the Next Linear Collider, while maintaining high efficiency.

  2. 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.

  3. Bipartite networks of oscillators with distributed delays: Synchronization branches and multistability.

    PubMed

    Punetha, Nirmal; Ramaswamy, Ramakrishna; Atay, Fatihcan M

    2015-04-01

    We study synchronization in bipartite networks of phase oscillators with general nonlinear coupling and distributed time delays. Phase-locked solutions are shown to arise, where the oscillators in each partition are perfectly synchronized among themselves but can have a phase difference with the other partition, with the phase difference necessarily being either zero or π radians. Analytical conditions for the stability of both types of solutions are obtained and solution branches are explicitly calculated, revealing that the network can have several coexisting stable solutions. With increasing value of the mean delay, the system exhibits hysteresis, phase flips, final state sensitivity, and an extreme form of multistability where the numbers of stable in-phase and antiphase synchronous solutions with distinct frequencies grow without bound. The theory is applied to networks of Landau-Stuart and Rössler oscillators and shown to accurately predict both in-phase and antiphase synchronous behavior in appropriate parameter ranges.

  4. Bipartite networks of oscillators with distributed delays: Synchronization branches and multistability

    NASA Astrophysics Data System (ADS)

    Punetha, Nirmal; Ramaswamy, Ramakrishna; Atay, Fatihcan M.

    2015-04-01

    We study synchronization in bipartite networks of phase oscillators with general nonlinear coupling and distributed time delays. Phase-locked solutions are shown to arise, where the oscillators in each partition are perfectly synchronized among themselves but can have a phase difference with the other partition, with the phase difference necessarily being either zero or π radians. Analytical conditions for the stability of both types of solutions are obtained and solution branches are explicitly calculated, revealing that the network can have several coexisting stable solutions. With increasing value of the mean delay, the system exhibits hysteresis, phase flips, final state sensitivity, and an extreme form of multistability where the numbers of stable in-phase and antiphase synchronous solutions with distinct frequencies grow without bound. The theory is applied to networks of Landau-Stuart and Rössler oscillators and shown to accurately predict both in-phase and antiphase synchronous behavior in appropriate parameter ranges.

  5. 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.

  6. 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.

  7. Analysis of static and time-varying polarization errors in the multiangle spectropolarimetric imager.

    PubMed

    Mahler, Anna-Britt; Diner, David J; Chipman, Russell A

    2011-05-10

    Multiangle Spectropolarimetric Imager (MSPI) sensitivity to static and time-varying polarization errors is examined. For a system without noise, static polarization errors are accurately represented by the calibration coefficients, and therefore do not impede correct mapping of measured to input Stokes vectors. But noise is invariably introduced during the detection process, and static polarization errors reduce the system's signal-to-noise ratio (SNR) by increasing noise sensitivity. Noise sensitivity is minimized by minimizing the condition number of the system data reduction matrix [Appl. Opt.41, 619 (2002)]. The sensitivity of condition numbers to static polarization errors is presented. The condition number of the nominal MSPI data reduction matrix is approximately 1.1 or less for all fields. The increase in the condition number above 1 results primarily from a quarter wave plate and mirror coating retardance magnitude errors. Sensitivity of the degree of linear polarization (DoLP) error with respect to time-varying diattenuation and retardance error was used to set a time-varying diattenuation magnitude tolerance of 0.005 and a time-varying retardance magnitude tolerance of ±0.2°. A Monte Carlo simulation of the calibration and measurements using anticipated static and time-varying errors indicates that MSPI has a probability of 0.9 of meeting its 0.005 DoLP uncertainty requirement.

  8. Isosurface Extraction in Time-Varying Fields Using a Temporal Hierarchical Index Tree

    NASA Technical Reports Server (NTRS)

    Shen, Han-Wei; Gerald-Yamasaki, Michael (Technical Monitor)

    1998-01-01

    Many high-performance isosurface extraction algorithms have been proposed in the past several years as a result of intensive research efforts. When applying these algorithms to large-scale time-varying fields, the storage overhead incurred from storing the search index often becomes overwhelming. this paper proposes an algorithm for locating isosurface cells in time-varying fields. We devise a new data structure, called Temporal Hierarchical Index Tree, which utilizes the temporal coherence that exists in a time-varying field and adoptively coalesces the cells' extreme values over time; the resulting extreme values are then used to create the isosurface cell search index. For a typical time-varying scalar data set, not only does this temporal hierarchical index tree require much less storage space, but also the amount of I/O required to access the indices from the disk at different time steps is substantially reduced. We illustrate the utility and speed of our algorithm with data from several large-scale time-varying CID simulations. Our algorithm can achieve more than 80% of disk-space savings when compared with the existing techniques, while the isosurface extraction time is nearly optimal.

  9. Magnetic Resonance Imaging of time-varying magnetic fields from therapeutic devices

    PubMed Central

    Hernandez-Garcia, Luis; Bhatia, Vivek; Prem-Kumar, Krishan; Ulfarsson, Magnus

    2013-01-01

    While magnetic resonance imaging of static magnetic fields generated by external probes has been previously demonstrated, there is an unmet need to image time-varying magnetic fields, such as those generated by transcranial magnetic stimulators or radiofrequency hyperthermia probes. A method to image such time-varying magnetic fields is introduced in this work. This article presents the theory behind the method and provides proof of concept by imaging time-varying magnetic fields generated by a figure-eight coil inside simple phantoms over a range of frequencies and intensities, using a 7T small animal MRI scanner. The method is able to reconstruct the three-dimensional components of the oscillating magnetic field vector. PMID:23355446

  10. Quantifying the effect of temporal resolution on time-varying networks

    PubMed Central

    Ribeiro, Bruno; Perra, Nicola; Baronchelli, Andrea

    2013-01-01

    Time-varying networks describe a wide array of systems whose constituents and interactions evolve over time. They are defined by an ordered stream of interactions between nodes, yet they are often represented in terms of a sequence of static networks, each aggregating all edges and nodes present in a time interval of size Δt. In this work we quantify the impact of an arbitrary Δt on the description of a dynamical process taking place upon a time-varying network. We focus on the elementary random walk, and put forth a simple mathematical framework that well describes the behavior observed on real datasets. The analytical description of the bias introduced by time integrating techniques represents a step forward in the correct characterization of dynamical processes on time-varying graphs. PMID:24141695

  11. Simulating a charged spherical pendulum in time-varying electric and magnetic fields

    NASA Astrophysics Data System (ADS)

    Wellons, Mark; King, Frank; McAlpine, Todd

    2008-03-01

    We simulate and analyze the dynamics of a charged spherical pendulum in time-varying electric and magnetic fields. The time-varying electric field is directed perpendicular to the gravitational field and serves as a driving force for the pendulum. The time-varying magnetic field is directed parallel to the gravitational field and serves to deflect the motion of the pendulum. We analyze the dynamics of the system to determine the conditions for which chaotic behavior is observed. We also include viscosity to look for strange attractors. The equations of motion are integrated using Objective C and the graphical user interface, including the three dimensional graphical representation of the system, is developed using Cocoa.

  12. Parasitic modulation of electromagnetic signals caused by time-varying plasma

    SciTech Connect

    Yang, Min Li, Xiaoping; Xie, Kai; Liu, Yanming

    2015-02-15

    An experiment on the propagation of electromagnetic (EM) signals in continuous time-varying plasma is described. The time-varying characteristics of plasma are considered to cause a parasitic modulation in both amplitude and phase, and the strength of this modulation, which carries the information of the electron density profile, is closely related to the plasma frequency and the incident wave frequency. Through theoretical analysis, we give an explanation and mechanism of the interaction between the continuous time-varying plasma and EM waves, which is verified by a comparative analysis with experiments performed under the same conditions. The effects of this modulation on the EM signals in the plasma sheath cannot be ignored.

  13. Quantum optical electromagnetic field and Rabi oscillation in time-varying medium

    NASA Astrophysics Data System (ADS)

    Jang, Eun Ji; Jung, Min; Cha, Ji Hoon; Lee, Young Kyu; Chung, Won Sang

    2016-09-01

    In this paper, we consider the quantum optical electromagnetic wave in time-varying media, where the electric permittivity ɛ( t) and the magnetic permeability μ( t) depend on time explicitly as ɛ( t) = ɛ 0(1+ qt) and μ( t) = μ 0(1+ qt). For these time-varying parameters, we solve Maxwell's equations. To construct time-dependent coherent states for this light, we adopt the invariant method proposed by Lewis and Riesenfeld and express the fields in terms of the time-dependent step operators for the invariant. We also discuss the deformed Rabi oscillation for both on-resonance and off-resonance.

  14. 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.

  15. 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.

  16. 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

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

    NASA Astrophysics Data System (ADS)

    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.

  18. Electrically-Tunable Group Delays Using Quantum Wells in a Distributed Bragg Reflector

    NASA Technical Reports Server (NTRS)

    Nelson, Thomas R., Jr.; Loehr, John P.; Fork, Richard L.; Cole, Spencer; Jones, Darryl K.; Keys, Andrew

    1999-01-01

    There is a growing interest in the fabrication of semiconductor optical group delay lines for the development of phased arrays of Vertical-Cavity Surface-Emitting Lasers (VCSELs). We present a novel structure incorporating In(x)GA(1-x)As quantum wells in the GaAs quarter-wave layers of a GaAs/AlAs distributed Bragg reflector (DBR). Application of an electric field across the quantum wells leads to red shifting and peak broadening of the el-hhl exciton peak via the quantum-confined Stark effect. Resultant changes in the index of refraction thereby provide a means for altering the group delay of an incident laser pulse. We discuss the tradeoffs between the maximum amount of change in group delay versus absorption losses for such a device. We also compare a simple theoretical model to experimental results, and discuss both angle and position tuning of the BDR band edge resonance relative to the exciton absorption peak. The advantages of such monolithically grown devices for phased-array VCSEL applications will be detailed.

  19. Time-varying geomagnetic field models: tools for studying millennial to million year secular variation

    NASA Astrophysics Data System (ADS)

    Constable, Catherine

    2010-05-01

    Global reconstructions of past geomagnetic field behavior draw on community efforts to gather reliable, well-dated paleomagnetic records. The number and spatial distribution of such records is continually improving and a range of model reconstructions have been used to assess temporal variations in geomagnetic dipole moment. On millennial time scales increasingly detailed images of the field are recovered which hint at the recurrence of prominent features like those mapped in the historical field (e.g., high latitude flux lobes and the South Atlantic Magnetic Anomaly). From lower resolution million-year models it is possible to infer the presence, if not the details, of changing non axial-dipole field structures, and to analyze the nature of temporal variations in the axial dipole moment. Such views are inevitably fuzzy representations of the real field, limited in both temporal and spatial resolution. Sharpening the image is desirable, but ongoing efforts to do so will ultimately remain restricted by data distribution, uncertainties, and finite age control. Progress in understanding long term geomagnetic secular variation requires an acute awareness of both limitations and value of such models and an ability to test specific hypotheses rather than relying on the accuracy of the resulting maps. One approach is to analyze a time varying model of a specific paleofield attribute. PADM2M is a recent reconstruction of paleomagnetic axial dipole moment variations for the past 2 million years which shows a persistent asymmetry in the growth and decay of the axial dipole moment on time scales longer than 10 kyr; overall the growth rate for the axial dipole is significantly larger than the decay rate. This feature is not limited to times when the field is reversing, suggesting that the asymmetry may reflect fundamental physical processes underlying the paleosecular variation. The longer decay cycle may suggest periods with a major contribution from diffusive processes

  20. 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.

  1. 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…

  2. 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.

  3. 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

  4. 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

  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. Discontinuous gradient algorithm for finite-time estimation of time-varying parameters

    NASA Astrophysics Data System (ADS)

    Rueda-Escobedo, Juan G.; Moreno, Jaime A.

    2016-09-01

    In this work, we present a discontinuous algorithm capable of estimating time-varying parameters in finite time. The measured output is assumed to be linear in the parameters, i.e. it corresponds to a linear parametric model. It is further assumed that the parameter variation is uniformly bounded, and that the regressor is sufficiently exciting as to make the parameters identifiable.

  7. Exploiting geo-distributed clouds for a e-health monitoring system with minimum service delay and privacy preservation.

    PubMed

    Shen, Qinghua; Liang, Xiaohui; Shen, Xuemin; Lin, Xiaodong; Luo, Henry Y

    2014-03-01

    In this paper, we propose an e-health monitoring system with minimum service delay and privacy preservation by exploiting geo-distributed clouds. In the system, the resource allocation scheme enables the distributed cloud servers to cooperatively assign the servers to the requested users under the load balance condition. Thus, the service delay for users is minimized. In addition, a traffic-shaping algorithm is proposed. The traffic-shaping algorithm converts the user health data traffic to the nonhealth data traffic such that the capability of traffic analysis attacks is largely reduced. Through the numerical analysis, we show the efficiency of the proposed traffic-shaping algorithm in terms of service delay and privacy preservation. Furthermore, through the simulations, we demonstrate that the proposed resource allocation scheme significantly reduces the service delay compared to two other alternatives using jointly the short queue and distributed control law.

  8. Time-varying effect moderation using the structural nested mean model: estimation using inverse-weighted regression with residuals

    PubMed Central

    Almirall, Daniel; Griffin, Beth Ann; McCaffrey, Daniel F.; Ramchand, Rajeev; Yuen, Robert A.; Murphy, Susan A.

    2014-01-01

    This article considers the problem of examining time-varying causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and possible confounders are time varying. The structural nested mean model (SNMM) is used to specify the moderated time-varying causal effects of interest in a conditional mean model for a continuous response given time-varying treatments and moderators. We present an easy-to-use estimator of the SNMM that combines an existing regression-with-residuals (RR) approach with an inverse-probability-of-treatment weighting (IPTW) strategy. The RR approach has been shown to identify the moderated time-varying causal effects if the time-varying moderators are also the sole time-varying confounders. The proposed IPTW+RR approach provides estimators of the moderated time-varying causal effects in the SNMM in the presence of an additional, auxiliary set of known and measured time-varying confounders. We use a small simulation experiment to compare IPTW+RR versus the traditional regression approach and to compare small and large sample properties of asymptotic versus bootstrap estimators of the standard errors for the IPTW+RR approach. This article clarifies the distinction between time-varying moderators and time-varying confounders. We illustrate the methodology in a case study to assess if time-varying substance use moderates treatment effects on future substance use. PMID:23873437

  9. 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.

  10. 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.

  11. Self-adjusting routing schemes for time-varying traffic in scale-free networks

    NASA Astrophysics Data System (ADS)

    Tang, Ming; Liu, Zonghua; Liang, Xiaoming; Hui, P. M.

    2009-08-01

    We consider the effects of time-varying packet generation rates in the performance of communication networks. The time variations could be a result of the patterns in human activities. As a model, we study the effects of a degree-dependent packet generation rate that includes a sinusoidal term. Applying a modified traffic awareness protocol (TAP) previously proposed for static packet generation rates to the present situation leads to an altered value of the optimization parameter, when compared to that obtained in the static case. To enhance the performance and to cope with the time-varying effects better, we propose a class of self-adjusting traffic awareness protocols that makes use of instantaneous traffic information beyond that included in the modified TAP. Two special cases that make use of global and local information, respectively, are studied. Comparing results of our proposal schemes with the modified TAP, it is shown that the present self-adjusting schemes perform more effectively.

  12. Dark soliton beats in the time-varying background of Bose-Einstein condensates

    SciTech Connect

    Wu Lei; Li Lu; Zhang Jiefang

    2009-07-15

    We investigate the dynamics of dark solitons in one-dimensional Bose-Einstein condensates. In the large particle limit, by introducing the lens-type transformation, we find that the macroscopic wave function evolves self-similarly when its initial profile strays from that of the equilibrium state, which provides a time-varying background for the propagation of dark solitons. The interaction of dark solitons with this kind of background is studied both analytically and numerically. We find that the center-of-mass motion of the dark soliton is deeply affected by the time-varying background, and the beating phenomena of dark soliton emerge when the intrinsic frequency of the dark soliton approaches that of the background. Lastly, we investigate the propagation of dark solitons in the freely expanding background.

  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. An improved correlation method for amplitude estimation of gravitational background signal with time-varying frequency

    NASA Astrophysics Data System (ADS)

    Wu, Wei-Huang; Tian, Yuan; Luo, Jie; Shao, Cheng-Gang; Xu, Jia-Hao; Wang, Dian-Hong

    2016-09-01

    In the measurement of the gravitational constant G with angular acceleration method, the accurate estimation of the amplitude of the useful angular acceleration generated by source masses depends on the effective subtraction of the spurious gravitational signal caused by room fixed background masses. The gravitational background signal is of time-varying frequency, and mainly consists of the prominent fundamental frequency and second harmonic components. We propose an improved correlation method to estimate the amplitudes of the prominent components of the gravitational background signal with high precision. The improved correlation method converts a sinusoidal signal with time-varying frequency into a standard sinusoidal signal by means of the stretch processing of time. Based on Gaussian white noise model, the theoretical result shows the uncertainty of the estimated amplitude is proportional to /σ √{ N T } , where σ and N are the standard deviation of noise and the number of the useful signal period T, respectively.

  15. Parametric conditions for stability of reduced-order linear time-varying control systems

    NASA Technical Reports Server (NTRS)

    Ma, C. C. H.; Vidyasagar, M.

    1987-01-01

    Using a single framework, parametric conditions are derived which encompass those for both local and global BIBO stability of a linear multivariable discrete-time reduced-order time-varying control system. These conditions indicate that the system will be BIBO stable if the norm of the system-parameter error matrix is bounded by an l exp 1 function superimposed on an l exp infinity function.

  16. 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.

  17. Simultaneously stabilising controllers for time-varying linear systems within the framework of nest algebras

    NASA Astrophysics Data System (ADS)

    Wang, Hongzhu; Yu, Tianqiu; Xiao, Jinmei

    2016-08-01

    From the perspective of strong transitivity, a controller design method is provided to simultaneously stabilise a collection of time-varying linear systems within the framework of nest algebras. In particular, all simultaneously stabilising controllers for a class of linear plants are characterised based on the doubly coprime factorisations. These results hold as well in the time-invariant case. An illustrative example is given to demonstrate the validity of the method.

  18. Delays without Mistakes: Response Time and Error Distributions in Dual-Task

    PubMed Central

    Kamienkowski, Juan Esteban; Sigman, Mariano

    2008-01-01

    Background When two tasks are presented within a short interval, a delay in the execution of the second task has been systematically observed. Psychological theorizing has argued that while sensory and motor operations can proceed in parallel, the coordination between these modules establishes a processing bottleneck. This model predicts that the timing but not the characteristics (duration, precision, variability…) of each processing stage are affected by interference. Thus, a critical test to this hypothesis is to explore whether the qualitiy of the decision is unaffected by a concurrent task. Methodology/Principal Findings In number comparison–as in most decision comparison tasks with a scalar measure of the evidence–the extent to which two stimuli can be discriminated is determined by their ratio, referred as the Weber fraction. We investigated performance in a rapid succession of two non-symbolic comparison tasks (number comparison and tone discrimination) in which error rates in both tasks could be manipulated parametrically from chance to almost perfect. We observed that dual-task interference has a massive effect on RT but does not affect the error rates, or the distribution of errors as a function of the evidence. Conclusions/Significance Our results imply that while the decision process itself is delayed during multiple task execution, its workings are unaffected by task interference, providing strong evidence in favor of a sequential model of task execution. PMID:18787706

  19. 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.

  20. 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.

  1. 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.

  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

    2016-01-01

    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

  3. 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.

  4. Time-varying modal parameters identification of a spacecraft with rotating flexible appendage by recursive algorithm

    NASA Astrophysics Data System (ADS)

    Ni, Zhiyu; Mu, Ruinan; Xun, Guangbin; Wu, Zhigang

    2016-01-01

    The rotation of spacecraft flexible appendage may cause changes in modal parameters. For this time-varying system, the computation cost of the frequently-used singular value decomposition (SVD) identification method is high. Some control problems, such as the self-adaptive control, need the latest modal parameters to update the controller parameters in time. In this paper, the projection approximation subspace tracking (PAST) recursive algorithm is applied as an alternative method to identify the time-varying modal parameters. This method avoids the SVD by signal subspace projection and improves the computational efficiency. To verify the ability of this recursive algorithm in spacecraft modal parameters identification, a spacecraft model with rapid rotational appendage, Soil Moisture Active/Passive (SMAP) satellite, is established, and the time-varying modal parameters of the satellite are identified recursively by designing the input and output signals. The results illustrate that this recursive algorithm can obtain the modal parameters in the high signal noise ratio (SNR) and it has better computational efficiency than the SVD method. Moreover, to improve the identification precision of this recursive algorithm in the low SNR, the wavelet de-noising technology is used to decrease the effect of noises.

  5. 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

  6. 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.

  7. 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.

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

    PubMed

    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.

  9. 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

  10. 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.

  11. 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

  12. Synthesis for Negative Group Delay Circuits Using Distributed and Second-Order RC Circuit Configurations

    NASA Astrophysics Data System (ADS)

    Ahn, Kyoung-Pyo; Ishikawa, Ryo; Saitou, Akira; Honjo, Kazuhiko

    This paper describes the characteristic of negative group delay (NGD) circuits for various configurations including first-order, distributed, and second-order RC circuit configurations. This study includes locus, magnitude, and phase characteristics of the NGD circuits. The simplest NGD circuit is available using first-order RC or RL configuration. As an example of distributed circuit configuration, it is verified that losses in a distributed line causes NGD characteristic at higher cut-off band of a coupled four-line bandpass filter. Also, novel wideband NGD circuits using second-order RC configuration, instead of conventional RLC configuration, are proposed. Adding a parallel resistor to a parallel-T filter enables NGD characteristic to it. Also, a Wien-Robinson bridge is modified to have NGD characteristic by controlling the voltage division ratio. They are fabricated on MMIC substrate, and their NGD characteristics are verified with measured results. They have larger insertion loss than multi-stage RLC NGD circuits, however they can realize second-order NGD characteristic without practical implementation of inductors.

  13. A New Framework for Analysis on Stability and Bifurcation in a Class of Neural Networks With Discrete and Distributed Delays.

    PubMed

    Xu, Wenying; Cao, Jinde; Xiao, Min; Ho, Daniel W C; Wen, Guanghui

    2015-10-01

    This paper studies the stability and Hopf bifurcation in a class of high-dimension neural network involving the discrete and distributed delays under a new framework. By introducing some virtual neurons to the original system, the impact of distributed delay can be described in a simplified way via an equivalent new model. This paper extends the existing works on neural networks to high-dimension cases, which is much closer to complex and real neural networks. Here, we first analyze the Hopf bifurcation in this special class of high dimensional model with weak delay kernel from two aspects: one is induced by the time delay, the other is induced by a rate parameter, to reveal the roles of discrete and distributed delays on stability and bifurcation. Sufficient conditions for keeping the original system to be stable, and undergoing the Hopf bifurcation are obtained. Besides, this new framework can also apply to deal with the case of the strong delay kernel and corresponding analysis for different dynamical behaviors is provided. Finally, the simulation results are presented to justify the validity of our theoretical analysis.

  14. Signal processing method based on group delay calculation for distributed Bragg wavelength shift in optical frequency domain reflectometry.

    PubMed

    Wada, Daichi; Igawa, Hirotaka; Murayama, Hideaki; Kasai, Tokio

    2014-03-24

    A signal processing method based on group delay calculations is introduced for distributed measurements of long-length fiber Bragg gratings (FBGs) based on optical frequency domain reflectometry (OFDR). Bragg wavelength shifts in interfered signals of OFDR are regarded as group delay. By calculating group delay, the distribution of Bragg wavelength shifts is obtained with high computational efficiency. We introduce weighted averaging process for noise reduction. This method required only 3.5% of signal processing time which was necessary for conventional equivalent signal processing based on short-time Fourier transform. The method also showed high sensitivity to experimental signals where non-uniform strain distributions existed in a long-length FBG.

  15. 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.

  16. Time-varying autoregressive modelling for nonstationary acoustic signal and its frequency analysis

    NASA Astrophysics Data System (ADS)

    Sodsri, Chukiet

    2003-06-01

    A time-varying autoregressive (TVAR) approach is used for modeling nonstationary signals, and frequency information is then extracted from the TVAR parameters. Two methods may be used for estimating the TVAR parameters: the adaptive algorithm approach and the basis function approach. Adaptive algorithms, such as the least mean square (LMS) and the recursive least square (RLS), use a dynamic model for adapting the TVAR parameters and are capable of tracking time-varying frequency, provided that the variation is slow. It is observed that, if the signals have a single time-frequency component, the RLS with a fixed pole on the unit circle yields the fastest convergence. The basis function method employs an explicit model for the TVAR parameter variation, and model parameters are estimated via a block calculation. We proposed a modification to the basis function method by utilizing both forward and backward predictors for estimating the time-varying spectral density of nonstationary signals. It is shown that our approach yields better accuracy than the existing basis function approach, which uses only the forward predictor. The selection of the basis functions and limitations are also discussed in this thesis. Finally, the proposed approach is applied to analyze violin vibrato. Our results showed superior frequency resolution and spectral line smoothness using the proposed approach, compared to conventional analysis with the short time Fourier transform (STFT) whose frequency resolution is very limited. It was also found that frequency modulation of vibrato occurs at the rate of 6 Hz, and the frequency variations for each partial are different and increase nonlinearly with the partial number.

  17. 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.

  18. Modeling of linear time-varying systems by linear time-invariant systems of lower order.

    NASA Technical Reports Server (NTRS)

    Nosrati, H.; Meadows, H. E.

    1973-01-01

    A method for modeling linear time-varying differential systems by linear time-invariant systems of lower order is proposed, extending the results obtained by Bierman (1972) by resolving such qualities as the model stability, various possible models of differing dimensions, and the uniqueness or nonuniqueness of the model coefficient matrix. In addition to the advantages cited by Heffes and Sarachik (1969) and Bierman, often by modeling a subsystem of a larger system it is possible to analyze the overall system behavior more easily, with resulting savings in computation time.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Performance of DPSK with convolutional encoding on time-varying fading channels

    NASA Technical Reports Server (NTRS)

    Mui, S. Y.; Modestino, J. W.

    1977-01-01

    The bit error probability performance of a differentially-coherent phase-shift keyed (DPSK) modem with convolutional encoding and Viterbi decoding on time-varying fading channels is examined. Both the Rician and the lognormal channels are considered. Bit error probability upper bounds on fully-interleaved (zero-memory) fading channels are derived and substantiated by computer simulation. It is shown that the resulting coded system performance is a relatively insensitive function of the choice of channel model provided that the channel parameters are related according to the correspondence developed as part of this paper. Finally, a comparison of DPSK with a number of other modulation strategies is provided.

  4. 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).

  5. Some well-posedness and general stability results in Timoshenko systems with infinite memory and distributed time delay

    NASA Astrophysics Data System (ADS)

    Guesmia, Aissa

    2014-08-01

    In this paper, we consider a Timoshenko system in one-dimensional bounded domain with infinite memory and distributed time delay both acting on the equation of the rotation angle. Without any restriction on the speeds of wave propagation and under appropriate assumptions on the infinite memory and distributed time delay convolution kernels, we prove, first, the well-posedness and, second, the stability of the system, where we present some decay estimates depending on the equal-speed propagation case and the opposite one. The obtained decay rates depend on the growths of the memory and delay kernels at infinity. In the nonequal-speed case, the decay rate depends also on the regularity of initial data. Our stability results show that the only dissipation resulting from the infinite memory guarantees the asymptotic stability of the system regardless to the speeds of wave propagation and in spite of the presence of a distributed time delay. Applications of our approach to specific coupled Timoshenko-heat and Timoshenko-wave systems as well as the discrete time delay case are also presented.

  6. From calls to communities: a model for time-varying social networks

    NASA Astrophysics Data System (ADS)

    Laurent, Guillaume; Saramäki, Jari; Karsai, Márton

    2015-11-01

    Social interactions vary in time and appear to be driven by intrinsic mechanisms that shape the emergent structure of social networks. Large-scale empirical observations of social interaction structure have become possible only recently, and modelling their dynamics is an actual challenge. Here we propose a temporal network model which builds on the framework of activity-driven time-varying networks with memory. The model integrates key mechanisms that drive the formation of social ties - social reinforcement, focal closure and cyclic closure, which have been shown to give rise to community structure and small-world connectedness in social networks. We compare the proposed model with a real-world time-varying network of mobile phone communication, and show that they share several characteristics from heterogeneous degrees and weights to rich community structure. Further, the strong and weak ties that emerge from the model follow similar weight-topology correlations as real-world social networks, including the role of weak ties.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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

    2016-01-01

    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

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

    PubMed

    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.

  14. Stagewise pseudo-value regression for time-varying effects on the cumulative incidence.

    PubMed

    Zöller, Daniela; Schmidtmann, Irene; Weinmann, Arndt; Gerds, Thomas A; Binder, Harald

    2016-03-30

    In a competing risks setting, the cumulative incidence of an event of interest describes the absolute risk for this event as a function of time. For regression analysis, one can either choose to model all competing events by separate cause-specific hazard models or directly model the association between covariates and the cumulative incidence of one of the events. With a suitable link function, direct regression models allow for a straightforward interpretation of covariate effects on the cumulative incidence. In practice, where data can be right-censored, these regression models are implemented using a pseudo-value approach. For a grid of time points, the possibly unobserved binary event status is replaced by a jackknife pseudo-value based on the Aalen-Johansen method. We combine a stagewise regression technique with the pseudo-value approach to provide variable selection while allowing for time-varying effects. This is implemented by coupling variable selection between the grid times, but determining estimates separately. The effect estimates are regularized to also allow for model fitting with a low to moderate number of observations. This technique is illustrated in an application using clinical cancer registry data from hepatocellular carcinoma patients. The results are contrasted with traditional hazard-based modeling. In addition to a more straightforward interpretation, when using the proposed technique, the identification of time-varying effect patterns on the cumulative incidence is seen to be feasible with a moderate number of observations.

  15. Adaptive sliding control of non-autonomous active suspension systems with time-varying loadings

    NASA Astrophysics Data System (ADS)

    Chen, Po-Chang; Huang, An-Chyau

    2005-04-01

    An adaptive sliding controller is proposed in this paper for controlling a non-autonomous quarter-car suspension system with time-varying loadings. The bound of the car-body loading is assumed to be available. Then, the reference coordinate is placed at the static position under the nominal loading so that the system dynamic equation is derived. Due to spring nonlinearities, the system property becomes asymmetric after coordinate transformation. Besides, in practical cases, system parameters are not easy to be obtained precisely for controller design. Therefore, in this paper, system uncertainties are lumped into two unknown time-varying functions. Since the variation bound of one of the unknown functions is not available, conventional adaptive schemes and robust designs are not applicable. To deal with this problem, the function approximation technique is employed to represent the unknown function as a finite combination of basis functions. The Lyapunov direct method can thus be used to find adaptive laws for updating coefficients in the approximating series and to prove stability of the closed-loop system. Since the position and velocity measurements of the unsprung mass are lumped into the unknown function, there is no need to install sensors on the axle and wheel assembly in the actual implementation. Simulation results are presented to show the performance of the proposed strategy.

  16. 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.

  17. 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.

  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. 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.

  20. Dynamic Filtering of Time-Varying Sparse Signals via ℓ _1 Minimization

    NASA Astrophysics Data System (ADS)

    Charles, Adam S.; Balavoine, Aurele; Rozell, Christopher J.

    2016-11-01

    Despite the importance of sparsity signal models and the increasing prevalence of high-dimensional streaming data, there are relatively few algorithms for dynamic filtering of time-varying sparse signals. Of the existing algorithms, fewer still provide strong performance guarantees. This paper examines two algorithms for dynamic filtering of sparse signals that are based on efficient l1 optimization methods. We first present an analysis for one simple algorithm (BPDN-DF) that works well when the system dynamics are known exactly. We then introduce a novel second algorithm (RWL1-DF) that is more computationally complex than BPDN-DF but performs better in practice, especially in the case where the system dynamics model is inaccurate. Robustness to model inaccuracy is achieved by using a hierarchical probabilistic data model and propagating higher-order statistics from the previous estimate (akin to Kalman filtering) in the sparse inference process. We demonstrate the properties of these algorithms on both simulated data as well as natural video sequences. Taken together, the algorithms presented in this paper represent the first strong performance analysis of dynamic filtering algorithms for time-varying sparse signals as well as state-of-the-art performance in this emerging application.

  1. Time-varying effects of prognostic factors associated with disease-free survival in breast cancer.

    PubMed

    Natarajan, Loki; Pu, Minya; Parker, Barbara A; Thomson, Cynthia A; Caan, Bette J; Flatt, Shirley W; Madlensky, Lisa; Hajek, Richard A; Al-Delaimy, Wael K; Saquib, Nazmus; Gold, Ellen B; Pierce, John P

    2009-06-15

    Early detection and effective treatments have dramatically improved breast cancer survivorship, yet the risk of relapse persists even 15 years after the initial diagnosis. It is important to identify prognostic factors for late breast cancer events. The authors investigated time-varying effects of tumor characteristics on breast-cancer-free survival using data on 3,088 breast cancer survivors from 4 US states who participated in a randomized dietary intervention trial in 1995-2006, with maximum follow-up through 15 years (median, 9 years). A piecewise constant penalized spline approach incorporating time-varying coefficients was adopted, allowing for deviations from the proportional hazards assumption. This method is more flexible than standard approaches, provides direct estimates of hazard ratios across time intervals, and is computationally tractable. Having a stage II or III tumor was associated with a 3-fold higher hazard of breast cancer than having a stage I tumor during the first 2.5 years after diagnosis; this hazard ratio decreased to 2.1 after 7.7 years, but higher tumor stage remained a significant risk factor. Similar diminishing effects were found for poorly differentiated tumors. Interestingly, having a positive estrogen receptor status was protective up to 4 years after diagnosis but detrimental after 7.7 years (hazard ratio = 1.5). These results emphasize the importance of careful statistical modeling allowing for possibly time-dependent effects in long-term survivorship studies. PMID:19403844

  2. Time-Varying Effects of Prognostic Factors Associated With Disease-Free Survival in Breast Cancer

    PubMed Central

    Natarajan, Loki; Pu, Minya; Parker, Barbara A.; Thomson, Cynthia A.; Caan, Bette J.; Flatt, Shirley W.; Madlensky, Lisa; Hajek, Richard A.; Al-Delaimy, Wael K.; Saquib, Nazmus; Gold, Ellen B.

    2009-01-01

    Early detection and effective treatments have dramatically improved breast cancer survivorship, yet the risk of relapse persists even 15 years after the initial diagnosis. It is important to identify prognostic factors for late breast cancer events. The authors investigated time-varying effects of tumor characteristics on breast-cancer-free survival using data on 3,088 breast cancer survivors from 4 US states who participated in a randomized dietary intervention trial in 1995–2006, with maximum follow-up through 15 years (median, 9 years). A piecewise constant penalized spline approach incorporating time-varying coefficients was adopted, allowing for deviations from the proportional hazards assumption. This method is more flexible than standard approaches, provides direct estimates of hazard ratios across time intervals, and is computationally tractable. Having a stage II or III tumor was associated with a 3-fold higher hazard of breast cancer than having a stage I tumor during the first 2.5 years after diagnosis; this hazard ratio decreased to 2.1 after 7.7 years, but higher tumor stage remained a significant risk factor. Similar diminishing effects were found for poorly differentiated tumors. Interestingly, having a positive estrogen receptor status was protective up to 4 years after diagnosis but detrimental after 7.7 years (hazard ratio = 1.5). These results emphasize the importance of careful statistical modeling allowing for possibly time-dependent effects in long-term survivorship studies. PMID:19403844

  3. 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.

  4. 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.

  5. LRS Bianchi Type-II Inflationary Universe with Massless Scalar Field and Time Varying Λ

    NASA Astrophysics Data System (ADS)

    Raj, Bali; Swati

    2012-08-01

    The locally rotationally symmetric (LRS) Bianchi type-II inflationary cosmological model is investigated for massless scalar field with flat potential and time varying Λ. To obtain the deterministic solution, it is assumed that scale factor is a(t)~eHt as we considered previously for Bianchi type-I spacetime and Λ~a-2 as considered by Chen and Wu, where H is the Hubble constant and effective potential V(phi)=const; phi Higg's field. It is shown that such a time varying Λ leads to no conflict with existing observations. However, it does change the predictions of standard cosmology in the matter-dominated phase and alleviates some problems in reconciling observations with the inflationary scenario. The model represents anisotropic spacetime in general. However, the model isotropizes for large values of t and β = 3H2, where β is constant. The physical and geometrical aspects of the model in the context of an inflationary scenario is also discussed.

  6. 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

  7. Time-varying stiffness of human elbow joint during cyclic voluntary movement.

    PubMed

    Bennett, D J; Hollerbach, J M; Xu, Y; Hunter, I W

    1992-01-01

    The objective of this study was to determine the extent to which subjects modulate their elbow joint mechanical properties during ongoing arm movement. Small pseudo-random force disturbances were applied to the wrist with an airjet actuator while subjects executed large (1 rad) elbow joint movements. Using a lumped parameter model of the muscle, tendon and proprioceptive feedback dynamics, a time-varying system identification technique was developed to analyze the phasic changes in the elbow joint's mechanical response. The mechanical properties were found to be time-varying, and well approximated by a quasi-linear second-order model. The stiffness of the arm was found to drop during movement. The arm was always underdamped, with the damping ratio changing during movement. Inertia estimates were constant and consistent with previous measurements. Overall, the moving arm was found to be very compliant, with a peak stiffness value less than the lowest value measured during posture, and a natural frequency of less than 3 Hz. Changing the speed of movement, or the load from gravity, changed the stiffness measured, but not in strict proportion to the change in net muscle torque.

  8. Adaptive neural control of nonlinear MIMO systems with time-varying output constraints.

    PubMed

    Meng, Wenchao; Yang, Qinmin; Sun, Youxian

    2015-05-01

    In this paper, adaptive neural control is investigated for a class of unknown multiple-input multiple-output nonlinear systems with time-varying asymmetric output constraints. To ensure constraint satisfaction, we employ a system transformation technique to transform the original constrained (in the sense of the output restrictions) system into an equivalent unconstrained one, whose stability is sufficient to solve the output constraint problem. It is shown that output tracking is achieved without violation of the output constraint. More specifically, we can shape the system performance arbitrarily on transient and steady-state stages with the output evolving in predefined time-varying boundaries all the time. A single neural network, whose weights are tuned online, is used in our design to approximate the unknown functions in the system dynamics, while the singularity problem of the control coefficient matrix is avoided without assumption on the prior knowledge of control input's bound. All the signals in the closed-loop system are proved to be semiglobally uniformly ultimately bounded via Lyapunov synthesis. Finally, the merits of the proposed controller are verified in the simulation environment.

  9. 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.

  10. 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.

  11. 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.

  12. Transport of time-varying plasma currents by whistler wave packets

    NASA Technical Reports Server (NTRS)

    Stenzel, R. L.; Urrutia, J. M.; Rousculp, C.

    1992-01-01

    The relationship between pulsed currents and electromagnetic waves is examined in a regime characterized by electron MHD. Pulsed currents are generated by (1) collection/emission of charged particles by/from biased electrodes and (2) induction of currents by time-varying and moving magnetic fields. Pulsed currents are observed to propagate at the speed of whistler wave packets. Their field structure forms ropelike configurations which are electromagnetically force-free. Moving sources induce 'eddy' currents which excite waves and form Cerenkov-like whistler 'wings'. The radiation patterns of moving magnetic antennas and electrodynamic tethers are investigated. Nonlinear effects of large-amplitude, antenna-launched whistler pulses are observed. These involve a new modulational instability in which a channel of high conductivity which permits the wave/currents to penetrate deeply into a collisional plasma is formed.

  13. 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.

  14. Query-driven visualization of time-varying adaptive mesh refinement data.

    PubMed

    Gosink, Luke J; Anderson, John C; Bethel, E Wes; Joy, Kenneth I

    2008-01-01

    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 that 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.

  15. Visualizing Time-Varying Phenomena In Numerical Simulations Of Unsteady Flows

    NASA Technical Reports Server (NTRS)

    Lane, David A.

    1996-01-01

    Streamlines, contour lines, vector plots, and volume slices (cutting planes) are commonly used for flow visualization. These techniques are sometimes referred to as instantaneous flow visualization techniques because calculations are based on an instant of the flowfield in time. Although instantaneous flow visualization techniques are effective for depicting phenomena in steady flows,they sometimes do not adequately depict time-varying phenomena in unsteady flows. Streaklines and timelines are effective visualization techniques for depicting vortex shedding, vortex breakdown, and shock waves in unsteady flows. These techniques are examples of time-dependent flow visualization techniques, which are based on many instants of the flowfields in time. This paper describes the algorithms for computing streaklines and timelines. Using numerically simulated unsteady flows, streaklines and timelines are compared with streamlines, contour lines, and vector plots. It is shown that streaklines and timelines reveal vortex shedding and vortex breakdown more clearly than instantaneous flow visualization techniques.

  16. Phase Response Synchronization in Neuronal Population with Time-Varying Coupling Strength

    PubMed Central

    Jiao, Xianfa; Zhao, Wanyu; Cao, Jinde

    2015-01-01

    We present the dynamic model of global coupled neuronal population subject to external stimulus by the use of phase sensitivity function. We investigate the effect of time-varying coupling strength on the synchronized phase response of neural population subjected to external harmonic stimulus. For a time-periodic coupling strength, we found that the stimulus with increasing intensity or frequency can reinforce the phase response synchronization in neuronal population of the weakly coupled neural oscillators, and the neuronal population with stronger coupling strength has good adaptability to stimulus. When we consider the dynamics of coupling strength, we found that a strong stimulus can quickly cause the synchronization in the neuronal population, the degree of synchronization grows with the increasing stimulus intensity, and the period of synchronized oscillation induced by external stimulation is related to stimulus frequency. PMID:26640514

  17. 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.

  18. 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.

  19. 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.

  20. Lagrangian Descriptors of Thermalized Transition States on Time-Varying Energy Surfaces.

    PubMed

    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. PMID:26551825

  1. Detection of time-varying harmonic amplitude alterations due to spectral interpolations between musical instrument tones.

    PubMed

    Horner, Andrew B; Beauchamp, James W; So, Richard H Y

    2009-01-01

    Gradated spectral interpolations between musical instrument tone pairs were used to investigate discrimination as a function of time-averaged spectral difference. All possible nonidentical pairs taken from a collection of eight musical instrument sounds consisting of bassoon, clarinet, flute, horn, oboe, saxophone, trumpet, and violin were tested. For each pair, several tones were generated with different balances between the primary and secondary instruments, where the balance was fixed across the duration of each tone. Among primary instruments it was found that changes to horn and bassoon [corrected] were most easily discriminable, while changes to saxophone and trumpet timbres were least discriminable. Among secondary instruments, the clarinet had the strongest effect on discrimination, whereas the bassoon had the least effect. For primary instruments, strong negative correlations were found between discrimination and their spectral incoherences, suggesting that the presence of dynamic spectral variations tends to increase the difficulty of detecting time-varying alterations such as spectral interpolation. PMID:19173434

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. Detection of time-varying harmonic amplitude alterations due to spectral interpolations between musical instrument tones.

    PubMed

    Horner, Andrew B; Beauchamp, James W; So, Richard H Y

    2009-01-01

    Gradated spectral interpolations between musical instrument tone pairs were used to investigate discrimination as a function of time-averaged spectral difference. All possible nonidentical pairs taken from a collection of eight musical instrument sounds consisting of bassoon, clarinet, flute, horn, oboe, saxophone, trumpet, and violin were tested. For each pair, several tones were generated with different balances between the primary and secondary instruments, where the balance was fixed across the duration of each tone. Among primary instruments it was found that changes to horn and bassoon [corrected] were most easily discriminable, while changes to saxophone and trumpet timbres were least discriminable. Among secondary instruments, the clarinet had the strongest effect on discrimination, whereas the bassoon had the least effect. For primary instruments, strong negative correlations were found between discrimination and their spectral incoherences, suggesting that the presence of dynamic spectral variations tends to increase the difficulty of detecting time-varying alterations such as spectral interpolation.

  7. Ponderomotive force of a uniform electromagnetic wave in a time varying dielectric medium

    SciTech Connect

    Mori, W.B. ); Katsouleas, T. )

    1992-12-14

    A ponderomotive force associated with a [ital uniform] electromagnetic wave propagating in a medium with time varying dielectric properties [e.g., [epsilon]=[epsilon]([ital x][minus][ital v][sub 0][ital t])] is identified. In particular, when a laser ionizes a gas through which it propagates, a force is exerted on the medium at the ionization front that is proportional to ([del][epsilon])[ital E][sup 2] rather than the usual ([epsilon][minus]1)[del][ital E][sup 2]. This force excites a wake in the plasma medium behind the ionization front. The ponderomotive force and wake amplitude are derived and tested with 1D particle-in-cell simulations.

  8. 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.

  9. 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.

  10. 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.

  11. Sliding mode control for multi-agent systems under a time-varying topology

    NASA Astrophysics Data System (ADS)

    Dong, Lijing; Chai, Senchun; Zhang, Baihai; Kiong Nguang, Sing

    2016-07-01

    This paper addresses the tracking problem of a class of multi-agent systems under uncertain communication environments which has been modelled by a finite number of constant Laplacian matrices together with their corresponding scheduling functions. Sliding mode control method is applied to solve this nonlinear tracking problem under a time-varying topology. The controller of each tracking agent has been designed by using only its own and neighbours' information. Sufficient conditions for the existence of a sliding mode control tracking strategy have been provided by the solvability of linear matrix inequalities. At the end of this work, numerical simulations are employed to demonstrate the effectiveness of the proposed sliding mode control tracking strategy.

  12. 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.

  13. 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

  14. Time-Varying Wing-Twist Improves Aerodynamic Efficiency of Forward Flight in Butterflies

    PubMed Central

    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. PMID:23341923

  15. 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. PMID:23341923

  16. Local inertial oscillations in the surface ocean generated by time-varying winds

    NASA Astrophysics Data System (ADS)

    Chen, Shengli; Polton, Jeff A.; Hu, Jianyu; Xing, Jiuxing

    2015-12-01

    A new relationship is presented to give a review study on the evolution of inertial oscillations in the surface ocean locally generated by time-varying wind stress. The inertial oscillation is expressed as the superposition of a previous oscillation and a newly generated oscillation, which depends upon the time-varying wind stress. This relationship is employed to investigate some idealized wind change events. For a wind series varying temporally with different rates, the induced inertial oscillation is dominated by the wind with the greatest variation. The resonant wind, which rotates anti-cyclonically at the local inertial frequency with time, produces maximal amplitude of inertial oscillations, which grows monotonically. For the wind rotating at non-inertial frequencies, the responses vary periodically, with wind injecting inertial energy when it is in phase with the currents, but removing inertial energy when it is out of phase. The wind rotating anti-cyclonically with time is much more favorable to generate inertial oscillations than the cyclonic rotating wind. The wind with a frequency closer to the inertial frequency generates stronger inertial oscillations. For a diurnal wind, the induced inertial oscillation is dependent on latitude and is most significant at 30 °. This relationship is also applied to examine idealized moving cyclones. The inertial oscillation is much stronger on the right-hand side of the cyclone path than on the left-hand side (in the northern hemisphere). This is due to the wind being anti-cyclonic with time on the right-hand side, but cyclonic on the other side. The inertial oscillation varies with the cyclone translation speed. The optimal translation speed generating the greatest inertial oscillations is 2 m/s at the latitude of 10 ° and gradually increases to 6 m/s at the latitude of 30 °.

  17. 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.

  18. Time-varying effects of smoking quantity and nicotine dependence on adolescent smoking regularity

    PubMed Central

    Selya, Arielle S.; Dierker, Lisa C.; Rose, Jennifer S.; Hedeker, Donald; Tan, Xianming; Li, Runze; Mermelstein, Robin J.

    2012-01-01

    Background Little is known about time-varying effects of smoking quantity and nicotine dependence on the regularity of adolescent smoking behavior. Methods The sample was drawn from the Social and Emotional Contexts of Adolescent Smoking Patterns Study which followed adolescent smokers over 5 assessment waves spanning 48 months. Participants included former experimenters (smoked <100 cigarettes/lifetime but did not smoke in past 90 days), recent experimenters (smoked <100 cigarettes/lifetime and smoked in past 90 days), and current smokers (smoked >100 cigarettes/lifetime and smoked in past 30 days). Mixed-effects regression models were run to examine the time-varying effects of smoking quantity and nicotine dependence on regularity of smoking behavior, as measured by number of days smoked. Results Smoking quantity and nicotine dependence were each found to be significantly associated with regularity of adolescent smoking and the size of each effect exhibited significant variation over time. The effect of smoking quantity decreased across time for each smoking group, while the effect of nicotine dependence increased across time for former and recent experimenters. By the 48-month follow-up, the effects of smoking quantity and nicotine dependence had each stabilized across groups. Conclusions This study reveals that smoking quantity and nicotine dependence are not static risk factors for the development of more regular smoking patterns. At low levels of smoking when nicotine dependence symptoms are less common, smoking quantity is a stronger predictor of increased regularity of smoking, while for more experienced smokers, nicotine dependence predicts further increases in regularity. PMID:22995764

  19. A Hepatitis C Virus Infection Model with Time-Varying Drug Effectiveness: Solution and Analysis

    PubMed Central

    Conway, Jessica M.; Perelson, Alan S.

    2014-01-01

    Simple models of therapy for viral diseases such as hepatitis C virus (HCV) or human immunodeficiency virus assume that, once therapy is started, the drug has a constant effectiveness. More realistic models have assumed either that the drug effectiveness depends on the drug concentration or that the effectiveness varies over time. Here a previously introduced varying-effectiveness (VE) model is studied mathematically in the context of HCV infection. We show that while the model is linear, it has no closed-form solution due to the time-varying nature of the effectiveness. We then show that the model can be transformed into a Bessel equation and derive an analytic solution in terms of modified Bessel functions, which are defined as infinite series, with time-varying arguments. Fitting the solution to data from HCV infected patients under therapy has yielded values for the parameters in the model. We show that for biologically realistic parameters, the predicted viral decay on therapy is generally biphasic and resembles that predicted by constant-effectiveness (CE) models. We introduce a general method for determining the time at which the transition between decay phases occurs based on calculating the point of maximum curvature of the viral decay curve. For the parameter regimes of interest, we also find approximate solutions for the VE model and establish the asymptotic behavior of the system. We show that the rate of second phase decay is determined by the death rate of infected cells multiplied by the maximum effectiveness of therapy, whereas the rate of first phase decline depends on multiple parameters including the rate of increase of drug effectiveness with time. PMID:25101902

  20. Time-varying subspace dimensionality: Useful as a seismic signal detection method?

    NASA Astrophysics Data System (ADS)

    Rowe, C. A.; Stead, R. J.; Begnaud, M. L.

    2012-12-01

    We explore the application of dimensional analysis to the problem of anomaly detection in multichannel time series. These techniques, which have been used for real-time load management in large computer systems, revolve around the time-varying dimensionality estimates of the signal subspace. Our application is to multiple channels of incoming seismic waveform data, as from a large array or across a network. Subspace analysis has been applied to seismic data before, but the routine use of the method is for the identification of a particular signal type, and requires a priori information about the range of signals for which the algorithm is searching. In this paradigm, a known but variable source (such as a mining region or aftershock sequence) provides known waveforms that are assumed to span the space occupied by incoming events of interest. Singular value decomposition or principal components analysis of the identified waveforms will allow for the selection of basis vectors that define the subspace onto which incoming signals are projected, to determine whether they belong to the source population of interest. In our application we do not seek to compare incoming signals to previously identified waveforms, but instead we seek to detect anomalies from the background behavior across an array or network. The background seismic levels will describe a signal space whose dimension may change markedly when an earthquake or other signal of interest occurs. We explore a variety of means by which we can evaluate the time-varying dimensionality of the signal space, and we compare the detection performance to other standard event detection methods.

  1. 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.

  2. Analysis of local ionospheric time varying characteristics with singular value decomposition

    NASA Astrophysics Data System (ADS)

    Jakobsen, Jakob; Knudsen, Per; Jensen, Anna B. O.

    2010-07-01

    In this paper, a time series from 1999 to 2007 of absolute total electron content (TEC) values has been computed and analyzed using singular value decomposition (SVD). The data set has been computed using a Kalman Filter and is based on dual frequency GPS data from three reference stations in Denmark located in the midlatitude region. The station separation between the three stations is 132-208 km (the time series of the TEC can be freely downloaded at http://www.heisesgade.dk ). For each year, a SVD has been performed on the TEC time series in order to identify the three time varying (daily, yearly, and 11 yearly) characteristics of the ionosphere. The applied SVD analysis provides a new method for separating the daily from the yearly components. The first singular value is very dominant (approximately six times larger than the second singular value), and this singular value corresponds clearly to the variation of the daily cycle over the year. The second singular value corresponds to variations of the width of the daily peak over the year, and the third singular value shows a clear yearly variation of the daily signal with peaks around the equinoxes. The singular values for each year show a very strong correlation with the sunspot number for all the singular values. The correlation coefficients for the first 5 sets of singular values are all above 0.96. Based on the SVD analysis yearly models of the TEC in the ionosphere can be recomposed and illustrate the three time varying characteristics of the ionosphere very clearly. By prediction of the yearly mean sunspot number, future yearly models can also be predicted. These can serve as a priori information for a real time space weather service providing information of the current status of the ionosphere. They will improve the Kalman filter processing making it more robust, but can also be used as

  3. 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

  4. 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.

  5. Analytical impact time and angle guidance via time-varying sliding mode technique.

    PubMed

    Zhao, Yao; Sheng, Yongzhi; Liu, Xiangdong

    2016-05-01

    To concretely provide a feasible solution for homing missiles with the precise impact time and angle, this paper develops a novel guidance law, based on the nonlinear engagement dynamics. The guidance law is firstly designed with the prior assumption of a stationary target, followed by the practical extension to a moving target scenario. The time-varying sliding mode (TVSM) technique is applied to fulfill the terminal constraints, in which a specific TVSM surface is constructed with two unknown coefficients. One is tuned to meet the impact time requirement and the other one is targeted with a global sliding mode, so that the impact angle constraint as well as the zero miss distance can be satisfied. Because the proposed law possesses three guidance gain as design parameters, the intercept trajectory can be shaped according to the operational conditions and missile׳s capability. To improve the tolerance of initial heading errors and broaden the application, a new frame of reference is also introduced. Furthermore, the analytical solutions of the flight trajectory, heading angle and acceleration command can be totally expressed for the prediction and offline parameter selection by solving a first-order linear differential equation. Numerical simulation results for various scenarios validate the effectiveness of the proposed guidance law and demonstrate the accuracy of the analytic solutions.

  6. Simple reaction time to the onset of time-varying sounds.

    PubMed

    Schlittenlacher, Josef; Ellermeier, Wolfgang

    2015-10-01

    Although auditory simple reaction time (RT) is usually defined as the time elapsing between the onset of a stimulus and a recorded reaction, a sound cannot be specified by a single point in time. Therefore, the present work investigates how the period of time immediately after onset affects RT. By varying the stimulus duration between 10 and 500 msec, this critical duration was determined to fall between 32 and 40 milliseconds for a 1-kHz pure tone at 70 dB SPL. In a second experiment, the role of the buildup was further investigated by varying the rise time and its shape. The increment in RT for extending the rise time by a factor of ten was about 7 to 8 msec. There was no statistically significant difference in RT between a Gaussian and linear rise shape. A third experiment varied the modulation frequency and point of onset of amplitude-modulated tones, producing onsets at different initial levels with differently rapid increase or decrease immediately afterwards. The results of all three experiments results were explained very well by a straightforward extension of the parallel grains model (Miller and Ulrich Cogn. Psychol. 46, 101-151, 2003), a probabilistic race model employing many parallel channels. The extension of the model to time-varying sounds made the activation of such a grain depend on intensity as a function of time rather than a constant level. A second approach by mechanisms known from loudness produced less accurate predictions.

  7. Simulations of Recovery of Time-Varying Gravity from DECIGO Pathfinder

    NASA Technical Reports Server (NTRS)

    Hasegawa, Takashi; Kyoto, U.; Rowlands, Dave; Luthcke, Scott; Sabaka, Terri; Camp, Jordan B.

    2011-01-01

    We simulated time-varying Earth's gravity field recovered from DPF to evaluate an impact of DPF and future satellite gradiometry mission on earth science. From hydrological water movement data and orbit information, gravity gradients to be measured at altitude about 500km were generated. Errors caused by atmospheric and oceanic variations and instrumental noise were added. Monthly gravity fields were estimated solving normal equations between spherical harmonic coefficients and simulated gravity gradient data. Simulation results show that DPF likely provides monthly hydrological water storage change with spatial scale between 400 and 1000km. Sensitivities to large scale estimates depends on long-term stability of gravity gradient measurement, and errors in short scale estimates are caused by instrumental noise and imperfections in atmospheric and ocean model. With acceleration noise level is lower than 5 x 10(exp -14) [m/s2/sqrtHz] at frequency higher than 3mHz, water storage changes at limited small basins will be provided by DPF. To monitor continental scale hydrological water movement, noise level must be lower than 5 x 10(exp -14) [m/s2/sqrtHz] at frequency higher than 1mHz.

  8. Circuital characterisation of space-charge motion with a time-varying applied bias.

    PubMed

    Kim, Chul; Moon, Eun-Yi; Hwang, Jungho; Hong, Hiki

    2015-01-01

    Understanding the behaviour of space-charge between two electrodes is important for a number of applications. The Shockley-Ramo theorem and equivalent circuit models are useful for this; however, fundamental questions of the microscopic nature of the space-charge remain, including the meaning of capacitance and its evolution into a bulk property. Here we show that the microscopic details of the space-charge in terms of resistance and capacitance evolve in a parallel topology to give the macroscopic behaviour via a charge-based circuit or electric-field-based circuit. We describe two approaches to this problem, both of which are based on energy conservation: the energy-to-current transformation rule, and an energy-equivalence-based definition of capacitance. We identify a significant capacitive current due to the rate of change of the capacitance. Further analysis shows that Shockley-Ramo theorem does not apply with a time-varying applied bias, and an additional electric-field-based current is identified to describe the resulting motion of the space-charge. Our results and approach provide a facile platform for a comprehensive understanding of the behaviour of space-charge between electrodes. PMID:26133999

  9. Regularization of the big bang singularity with a time varying equation of state w > 1

    NASA Astrophysics Data System (ADS)

    Xue, BingKan; Belbruno, Edward

    2014-08-01

    We study the classical dynamics of the universe undergoing a transition from contraction to expansion through a big bang singularity. The dynamics is described by a system of differential equations for a set of physical quantities, such as the scale factor a, the Hubble parameter H, the equation of state parameter w, and the density parameter Ω. The solutions of the dynamical system have a singularity at the big bang. We study if the solutions can be regularized at the singularity in the sense of whether they have unique branch extensions through the singularity. In particular, we consider the model in which the contracting universe is dominated by a scalar field with a time varying equation of state w, which approaches a constant value wc near the singularity. We prove that, for {{w}_{c}}>1, the solutions are regularizable only for a discrete set of wc values that satisfy a coprime number condition. Our result implies that the evolution of a bouncing universe through the big bang singularity does not have a continuous classical limit unless the equation of state is extremely fine-tuned.

  10. Framework and algorithms for illustrative visualizations of time-varying flows on unstructured meshes

    DOE PAGES

    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 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

  11. 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).

  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. 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.

  14. 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

  15. Self-Organizing Map With Time-Varying Structure to Plan and Control Artificial Locomotion.

    PubMed

    Araujo, Aluizio F R; Santana, Orivaldo V

    2015-08-01

    This paper presents an algorithm, self-organizing map-state trajectory generator (SOM-STG), to plan and control legged robot locomotion. The SOM-STG is based on an SOM with a time-varying structure characterized by constructing autonomously close-state trajectories from an arbitrary number of robot postures. Each trajectory represents a cyclical movement of the limbs of an animal. The SOM-STG was designed to possess important features of a central pattern generator, such as rhythmic pattern generation, synchronization between limbs, and swapping between gaits following a single command. The acquisition of data for SOM-STG is based on learning by demonstration in which the data are obtained from different demonstrator agents. The SOM-STG can construct one or more gaits for a simulated robot with six legs, can control the robot with any of the gaits learned, and can smoothly swap gaits. In addition, SOM-STG can learn to construct a state trajectory form observing an animal in locomotion. In this paper, a dog is the demonstrator agent.

  16. Optimal routing of hazardous substances in time-varying, stochastic transportation networks

    SciTech Connect

    Woods, A.L.; Miller-Hooks, E.; Mahmassani, H.S.

    1998-07-01

    This report is concerned with the selection of routes in a network along which to transport hazardous substances, taking into consideration several key factors pertaining to the cost of transport and the risk of population exposure in the event of an accident. Furthermore, the fact that travel time and the risk measures are not constant over time is explicitly recognized in the routing decisions. Existing approaches typically assume static conditions, possibly resulting in inefficient route selection and unnecessary risk exposure. The report described the application of recent advances in network analysis methodologies to the problem of routing hazardous substances. Several specific problem formulations are presented, reflecting different degrees of risk aversion on the part of the decision-maker, as well as different possible operational scenarios. All procedures explicitly consider travel times and travel costs (including risk measures) to be stochastic time-varying quantities. The procedures include both exact algorithms, which may require extensive computational effort in some situations, as well as more efficient heuristics that may not guarantee a Pareto-optimal solution. All procedures are systematically illustrated for an example application using the Texas highway network, for both normal and incident condition scenarios. The application illustrates the trade-offs between the information obtained in the solution and computational efficiency, and highlights the benefits of incorporating these procedures in a decision-support system for hazardous substance shipment routing decisions.

  17. Time-varying span efficiency through the wingbeat of desert locusts.

    PubMed

    Henningsson, Per; Bomphrey, Richard J

    2012-06-01

    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. 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.

  19. Time-varying spatial spectrum estimation with a maneuverable towed array.

    PubMed

    Rogers, Jeffrey S; Krolik, Jeffrey L

    2010-12-01

    This paper addresses the problem of field directionality mapping (FDM) or spatial spectrum estimation in dynamic environments with a maneuverable towed acoustic array. Array processing algorithms for towed arrays are typically designed assuming the array is straight, and are thus degraded during tow-ship maneuvers. In this paper, maneuvering the array is treated as a feature allowing for left and right disambiguation as well as improved resolution toward endfire. The Cramér-Rao lower bound is used to motivate the improvement in source localization which can be theoretically achieved by exploiting array maneuverability. Two methods for estimating time-varying field directionality with a maneuvering array are presented: (1) Maximum likelihood (ML) estimation solved using the expectation maximization algorithm and (2) a non-negative least squares (NNLS) approach. The NNLS method is designed to compute the field directionality from beamformed power outputs, while the ML algorithm uses raw sensor data. A multi-source simulation is used to illustrate both the proposed algorithms' ability to suppress ambiguous towed array backlobes and resolve closely spaced interferers near endfire which pose challenges for conventional beamforming approaches especially during array maneuvers. Receiver operating characteristics are presented to evaluate the algorithms' detection performance versus signal-to-noise ratio. The results indicate that both FDM algorithms offer the potential to provide superior detection performance when compared to conventional beamforming with a maneuverable array.

  20. [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.

  1. Video Extrapolation Method Based on Time-Varying Energy Optimization and CIP.

    PubMed

    Sakaino, Hidetomo

    2016-09-01

    Video extrapolation/prediction methods are often used to synthesize new videos from images. For fluid-like images and dynamic textures as well as moving rigid objects, most state-of-the-art video extrapolation methods use non-physics-based models that learn orthogonal bases from a number of images but at high computation cost. Unfortunately, data truncation can cause image degradation, i.e., blur, artifact, and insufficient motion changes. To extrapolate videos that more strictly follow physical rules, this paper proposes a physics-based method that needs only a few images and is truncation-free. We utilize physics-based equations with image intensity and velocity: optical flow, Navier-Stokes, continuity, and advection equations. These allow us to use partial difference equations to deal with the local image feature changes. Image degradation during extrapolation is minimized by updating model parameters, where a novel time-varying energy balancer model that uses energy based image features, i.e., texture, velocity, and edge. Moreover, the advection equation is discretized by high-order constrained interpolation profile for lower quantization error than can be achieved by the previous finite difference method in long-term videos. Experiments show that the proposed energy based video extrapolation method outperforms the state-of-the-art video extrapolation methods in terms of image quality and computation cost. PMID:27305677

  2. 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.

  3. Computationally Efficient Partial Crosstalk Cancellation in Fast Time-Varying DSL Crosstalk Environments

    NASA Astrophysics Data System (ADS)

    Forouzan, Amir R.; Garth, Lee M.

    2007-12-01

    Line selection (LS), tone selection (TS), and joint tone-line selection (JTLS) partial crosstalk cancellers have been proposed to reduce the online computational complexity of far-end crosstalk (FEXT) cancellers in digital subscriber lines (DSL). However, when the crosstalk profile changes rapidly over time, there is an additional requirement that the partial crosstalk cancellers, particularly the LS and JTLS schemes, should also provide a low preprocessing complexity. This is in contrast to the case for perfect crosstalk cancellers. In this paper, we propose two novel channel matrix inversion methods, the approximate inverse (AI) and reduced inverse (RI) schemes, which reduce the recurrent complexity of the LS and JTLS schemes. Moreover, we propose two new classes of JTLS algorithms, the subsort and Lagrange JTLS algorithms, with significantly lower computational complexity than the recently proposed optimal greedy JTLS scheme. The computational complexity analysis of our algorithms shows that they provide much lower recurrent complexities than the greedy JTLS algorithm, allowing them to work efficiently in very fast time-varying crosstalk environments. Moreover, the analytical and simulation results demonstrate that our techniques are close to the optimal solution from the crosstalk cancellation point of view. The results also reveal that partial crosstalk cancellation is more beneficial in upstream DSL, particularly for short loops.

  4. Magma acoustics and time-varying melt properties at Arenal Volcano, Costa Rica

    NASA Astrophysics Data System (ADS)

    Garcés, Milton A.; Hagerty, Michael T.; Schwartz, Susan Y.

    The similarity of acoustic and seismic spectra recorded during Strombolian activity of Arenal Volcano provides conclusive evidence that pressure waves are generated and propagated within the magma-gas mixture inside volcanic conduits. These pressure waves are sensitive to the flow velocity and to small changes in the gas content of the magma-gas mixture, and thus can provide useful indicators of the time-varying properties of the unsteady flow regime and the chemical composition of the melt. The dominant features of the observed explosion and tremor signals are attributed to the source excitation functions and the acoustic resonance of a magma-gas mixture inside the volcanic conduit. We postulate that explosions are triggered in the shallow parts of the magma conduit, where a drastic pressure drop with depth creates a region where violent degassing can occur. Tremor may be sustained by unsteady flow fluctuations at depth. Equilibrium degassing of the melt creates a stable, stratified magma column where the void fraction increases with decreasing depth. Disruption of this equilibrium stratification is thought to be responsible for observed variations in the seismic efficiency of explosions and enhanced acoustic transmission from the interior of the conduit to the atmosphere.

  5. 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.

  6. 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.

  7. 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.

  8. Quantifying time-varying coordination of multimodal speech signals using correlation map analysis.

    PubMed

    Barbosa, Adriano Vilela; Déchaine, Rose-Marie; Vatikiotis-Bateson, Eric; Yehia, Hani Camille

    2012-03-01

    This paper demonstrates an algorithm for computing the instantaneous correlation coefficient between two signals. The algorithm is the computational engine for analyzing the time-varying coordination between signals, which is called correlation map analysis (CMA). Correlation is computed around any pair of points in the two input signals. Thus, coordination can be assessed across a continuous range of temporal offsets and be detected even when changing over time due to temporal fluctuations. The correlation algorithm has two major features: (i) it is structurally similar to a tunable filter, requiring only one parameter to set its cutoff frequency (and sensitivity), (ii) it can be applied either uni-directionally (computing correlation based only on previous samples) or bi-directionally (computing correlation based on both previous and future samples). Computing instantaneous correlation for a range of time offsets between two signals produces a 2D correlation map, in which correlation is characterized as a function of time and temporal offset. Graphic visualization of the correlation map provides rapid assessment of how correspondence patterns progress through time. The utility of the algorithm and of CMA are exemplified using the spatial and temporal coordination of various audible and visible components associated with linguistic performance. PMID:22423712

  9. 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.

  10. Left ventricular function: time-varying elastance and left ventricular aortic coupling.

    PubMed

    Walley, Keith R

    2016-01-01

    Many aspects of left ventricular function are explained by considering ventricular pressure-volume characteristics. Contractility is best measured by the slope, Emax, of the end-systolic pressure-volume relationship. Ventricular systole is usefully characterized by a time-varying elastance (ΔP/ΔV). An extended area, the pressure-volume area, subtended by the ventricular pressure-volume loop (useful mechanical work) and the ESPVR (energy expended without mechanical work), is linearly related to myocardial oxygen consumption per beat. For energetically efficient systolic ejection ventricular elastance should be, and is, matched to aortic elastance. Without matching, the fraction of energy expended without mechanical work increases and energy is lost during ejection across the aortic valve. Ventricular function curves, derived from ventricular pressure-volume characteristics, interact with venous return curves to regulate cardiac output. Thus, consideration of ventricular pressure-volume relationships highlight features that allow the heart to efficiently respond to any demand for cardiac output and oxygen delivery. PMID:27613430

  11. 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.

  12. Circuital characterisation of space-charge motion with a time-varying applied bias

    PubMed Central

    Kim, Chul; Moon, Eun-Yi; Hwang, Jungho; Hong, Hiki

    2015-01-01

    Understanding the behaviour of space-charge between two electrodes is important for a number of applications. The Shockley-Ramo theorem and equivalent circuit models are useful for this; however, fundamental questions of the microscopic nature of the space-charge remain, including the meaning of capacitance and its evolution into a bulk property. Here we show that the microscopic details of the space-charge in terms of resistance and capacitance evolve in a parallel topology to give the macroscopic behaviour via a charge-based circuit or electric-field-based circuit. We describe two approaches to this problem, both of which are based on energy conservation: the energy-to-current transformation rule, and an energy-equivalence-based definition of capacitance. We identify a significant capacitive current due to the rate of change of the capacitance. Further analysis shows that Shockley-Ramo theorem does not apply with a time-varying applied bias, and an additional electric-field-based current is identified to describe the resulting motion of the space-charge. Our results and approach provide a facile platform for a comprehensive understanding of the behaviour of space-charge between electrodes. PMID:26133999

  13. Measuring time-varying information flow in scalp EEG signals: orthogonalized partial directed coherence.

    PubMed

    Omidvarnia, Amir; Azemi, Ghasem; Boashash, Boualem; O'Toole, John M; Colditz, Paul B; Vanhatalo, Sampsa

    2014-03-01

    This study aimed to develop a time-frequency method for measuring directional interactions over time and frequency from scalp-recorded electroencephalographic (EEG) signals in a way that is less affected by volume conduction and amplitude scaling. We modified the time-varying generalized partial directed coherence (tv-gPDC) method, by orthogonalization of the strictly causal multivariate autoregressive model coefficients, to minimize the effect of mutual sources. The novel measure, generalized orthogonalized PDC (gOPDC), was tested first using two simulated models with feature dimensions relevant to EEG activities. We then used the method for assessing event-related directional information flow from flash-evoked responses in neonatal EEG. For testing statistical significance of the findings, we followed a thresholding procedure driven by baseline periods in the same EEG activity. The results suggest that the gOPDC method 1) is able to remove common components akin to volume conduction effect in the scalp EEG, 2) handles the potential challenge with different amplitude scaling within multichannel signals, and 3) can detect directed information flow within a subsecond time scale in nonstationary multichannel EEG datasets. This method holds promise for estimating directed interactions between scalp EEG channels that are commonly affected by the confounding impact of mutual cortical sources.

  14. Circuital characterisation of space-charge motion with a time-varying applied bias.

    PubMed

    Kim, Chul; Moon, Eun-Yi; Hwang, Jungho; Hong, Hiki

    2015-07-02

    Understanding the behaviour of space-charge between two electrodes is important for a number of applications. The Shockley-Ramo theorem and equivalent circuit models are useful for this; however, fundamental questions of the microscopic nature of the space-charge remain, including the meaning of capacitance and its evolution into a bulk property. Here we show that the microscopic details of the space-charge in terms of resistance and capacitance evolve in a parallel topology to give the macroscopic behaviour via a charge-based circuit or electric-field-based circuit. We describe two approaches to this problem, both of which are based on energy conservation: the energy-to-current transformation rule, and an energy-equivalence-based definition of capacitance. We identify a significant capacitive current due to the rate of change of the capacitance. Further analysis shows that Shockley-Ramo theorem does not apply with a time-varying applied bias, and an additional electric-field-based current is identified to describe the resulting motion of the space-charge. Our results and approach provide a facile platform for a comprehensive understanding of the behaviour of space-charge between electrodes.

  15. 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

  16. A Class of Prediction-Correction Methods for Time-Varying Convex Optimization

    NASA Astrophysics Data System (ADS)

    Simonetto, Andrea; Mokhtari, Aryan; Koppel, Alec; Leus, Geert; Ribeiro, Alejandro

    2016-09-01

    This paper considers unconstrained convex optimization problems with time-varying objective functions. We propose algorithms with a discrete time-sampling scheme to find and track the solution trajectory based on prediction and correction steps, while sampling the problem data at a constant rate of $1/h$, where $h$ is the length of the sampling interval. The prediction step is derived by analyzing the iso-residual dynamics of the optimality conditions. The correction step adjusts for the distance between the current prediction and the optimizer at each time step, and consists either of one or multiple gradient steps or Newton steps, which respectively correspond to the gradient trajectory tracking (GTT) or Newton trajectory tracking (NTT) algorithms. Under suitable conditions, we establish that the asymptotic error incurred by both proposed methods behaves as $O(h^2)$, and in some cases as $O(h^4)$, which outperforms the state-of-the-art error bound of $O(h)$ for correction-only methods in the gradient-correction step. Moreover, when the characteristics of the objective function variation are not available, we propose approximate gradient and Newton tracking algorithms (AGT and ANT, respectively) that still attain these asymptotical error bounds. Numerical simulations demonstrate the practical utility of the proposed methods and that they improve upon existing techniques by several orders of magnitude.

  17. AST: Activity-Security-Trust driven modeling of time varying networks.

    PubMed

    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

  18. Indexical properties influence time-varying amplitude and fundamental frequency contributions of vowels to sentence intelligibility

    PubMed Central

    Fogerty, Daniel

    2015-01-01

    The present study investigated how non-linguistic, indexical information about talker identity interacts with contributions to sentence intelligibility by the time-varying amplitude (temporal envelope) and fundamental frequency (F0). Young normal-hearing adults listened to sentences that preserved the original consonants but replaced the vowels with a single vowel production. This replacement vowel selectively preserved amplitude or F0 cues of the original vowel, but replaced cues to phonetic identity. Original vowel duration was always preserved. Three experiments investigated indexical contributions by replacing vowels with productions from the same or different talker, or by acoustically morphing the original vowel. These stimulus conditions investigated how vowel suprasegmental and indexical properties interact and contribute to intelligibility independently from phonetic information. Results demonstrated that indexical properties influence the relative contribution of suprasegmental properties to sentence intelligibility. F0 variations are particularly important in the presence of conflicting indexical information. Temporal envelope modulations significantly improve sentence intelligibility, but are enhanced when either indexical or F0 cues are available. These findings suggest that F0 and other indexical cues may facilitate perceptually grouping suprasegmental properties of vowels with the remainder of the sentence. Temporal envelope modulations of vowels may contribute to intelligibility once they are successfully integrated with the preserved signal. PMID:26543276

  19. Higher dimensional analysis shows reduced dynamism of time-varying network connectivity in schizophrenia patients.

    PubMed

    Miller, Robyn L; Yaesoubi, Maziar; Calhoun, Vince D

    2014-01-01

    Assessments of functional connectivity between brain networks is a fixture of resting state fMRI research. Until very recently most of this work proceeded from an assumption of stationarity in resting state network connectivity. In the last few years however, interest in moving beyond this simplifying assumption has grown considerably. Applying group temporal independent component analysis (tICA) to a set of time-varying functional network connectivity (FNC) matrices derived from a large multi-site fMRI dataset (N=314; 163 healthy, 151 schizophrenia patients), we obtain a set of five basic correlation patterns (component spatial maps (SMs)) from which observed FNCs can be expressed as mutually independent linear combinations, i.e., the coefficient on each SM in the linear combination is maximally independent of the others. We study dynamic properties of network connectivity as they are reflected in this five-dimensional space, and report stark differences in connectivity dynamics between schizophrenia patients and healthy controls. We also find that the most important global differences in FNC dynamism between patient and control groups are replicated when the same dynamical analysis is performed on sets of correlation patterns obtained from either PCA or spatial ICA, giving us additional confidence in the results.

  20. Circuital characterisation of space-charge motion with a time-varying applied bias

    NASA Astrophysics Data System (ADS)

    Kim, Chul; Moon, Eun-Yi; Hwang, Jungho; Hong, Hiki

    2015-07-01

    Understanding the behaviour of space-charge between two electrodes is important for a number of applications. The Shockley-Ramo theorem and equivalent circuit models are useful for this; however, fundamental questions of the microscopic nature of the space-charge remain, including the meaning of capacitance and its evolution into a bulk property. Here we show that the microscopic details of the space-charge in terms of resistance and capacitance evolve in a parallel topology to give the macroscopic behaviour via a charge-based circuit or electric-field-based circuit. We describe two approaches to this problem, both of which are based on energy conservation: the energy-to-current transformation rule, and an energy-equivalence-based definition of capacitance. We identify a significant capacitive current due to the rate of change of the capacitance. Further analysis shows that Shockley-Ramo theorem does not apply with a time-varying applied bias, and an additional electric-field-based current is identified to describe the resulting motion of the space-charge. Our results and approach provide a facile platform for a comprehensive understanding of the behaviour of space-charge between electrodes.

  1. Analytical impact time and angle guidance via time-varying sliding mode technique.

    PubMed

    Zhao, Yao; Sheng, Yongzhi; Liu, Xiangdong

    2016-05-01

    To concretely provide a feasible solution for homing missiles with the precise impact time and angle, this paper develops a novel guidance law, based on the nonlinear engagement dynamics. The guidance law is firstly designed with the prior assumption of a stationary target, followed by the practical extension to a moving target scenario. The time-varying sliding mode (TVSM) technique is applied to fulfill the terminal constraints, in which a specific TVSM surface is constructed with two unknown coefficients. One is tuned to meet the impact time requirement and the other one is targeted with a global sliding mode, so that the impact angle constraint as well as the zero miss distance can be satisfied. Because the proposed law possesses three guidance gain as design parameters, the intercept trajectory can be shaped according to the operational conditions and missile׳s capability. To improve the tolerance of initial heading errors and broaden the application, a new frame of reference is also introduced. Furthermore, the analytical solutions of the flight trajectory, heading angle and acceleration command can be totally expressed for the prediction and offline parameter selection by solving a first-order linear differential equation. Numerical simulation results for various scenarios validate the effectiveness of the proposed guidance law and demonstrate the accuracy of the analytic solutions. PMID:26952314

  2. Estimation of Bid Curves in Power Exchanges using Time-varying Simultaneous-Equations Models

    NASA Astrophysics Data System (ADS)

    Ofuji, Kenta; Yamaguchi, Nobuyuki

    Simultaneous-equations model (SEM) is generally used in economics to estimate interdependent endogenous variables such as price and quantity in a competitive, equilibrium market. In this paper, we have attempted to apply SEM to JEPX (Japan Electric Power eXchange) spot market, a single-price auction market, using the publicly available data of selling and buying bid volumes, system price and traded quantity. The aim of this analysis is to understand the magnitude of influences to the auctioned prices and quantity from the selling and buying bids, than to forecast prices and quantity for risk management purposes. In comparison with the Ordinary Least Squares (OLS) estimation where the estimation results represent average values that are independent of time, we employ a time-varying simultaneous-equations model (TV-SEM) to capture structural changes inherent in those influences, using State Space models with Kalman filter stepwise estimation. The results showed that the buying bid volumes has that highest magnitude of influences among the factors considered, exhibiting time-dependent changes, ranging as broad as about 240% of its average. The slope of the supply curve also varies across time, implying the elastic property of the supply commodity, while the demand curve remains comparatively inelastic and stable over time.

  3. Consensus analysis of networks with time-varying topology and event-triggered diffusions.

    PubMed

    Han, Yujuan; Lu, Wenlian; Chen, Tianping

    2015-11-01

    This paper studies the consensus problem of networks with time-varying topology. Event-triggered rules are employed in diffusion coupling terms to reduce the updating load of the coupled system. Two strategies are considered: event-triggered strategy, that each node observes the state information in an instantaneous way, to determine the next triggering event time, and self-triggered strategy, that each node only needs to observe the state information at the event time to predict the next triggering event time. In each strategy, two kinds of algorithms are considered: the pull-based algorithm, that the diffusion coupling term of every node is updated at the latest observations of the neighborhood at its triggered time, and push-based algorithm, the diffusion coupling term of every node uses the state information of its neighborhood at their latest triggered time. It is proved that if the coupling matrix across time intervals with length less than some given constant has spanning trees, then the proposed algorithms can realize consensus. Examples with numerical simulation are provided to show the effectiveness of the theoretical results.

  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. 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.

  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. Delay correction model for estimating bus emissions at signalized intersections based on vehicle specific power distributions.

    PubMed

    Song, Guohua; Zhou, Xixi; Yu, Lei

    2015-05-01

    The intersection is one of the biggest emission points for buses and also the high exposure site for people. Several traffic performance indexes have been developed and widely used for intersection evaluations. However, few studies have focused on the relationship between these indexes and emissions at intersections. This paper intends to propose a model that relates emissions to the two commonly used measures of effectiveness (i.e. delay time and number of stops) by using bus activity data and emission data at intersections. First, with a large number of field instantaneous emission data and corresponding activity data collected by the Portable Emission Measurement System (PEMS), emission rates are derived for different vehicle specific power (VSP) bins. Then, 2002 sets of trajectory data, an equivalent of about 140,000 sets of second-by-second activity data, are obtained from Global Position Systems (GPSs)-equipped diesel buses in Beijing. The delay and the emission factors of each trajectory are estimated. Then, by using baseline emission factors for two types of intersections, e.g. the Arterial @ Arterial Intersection and the Arterial @ Collector, delay correction factors are calculated for the two types of intersections at different congestion levels. Finally, delay correction models are established for adjusting emission factors for each type of intersections and different numbers of stops. A comparative analysis between estimated and field emission factors demonstrates that the delay correction model is reliable.

  9. Delay correction model for estimating bus emissions at signalized intersections based on vehicle specific power distributions.

    PubMed

    Song, Guohua; Zhou, Xixi; Yu, Lei

    2015-05-01

    The intersection is one of the biggest emission points for buses and also the high exposure site for people. Several traffic performance indexes have been developed and widely used for intersection evaluations. However, few studies have focused on the relationship between these indexes and emissions at intersections. This paper intends to propose a model that relates emissions to the two commonly used measures of effectiveness (i.e. delay time and number of stops) by using bus activity data and emission data at intersections. First, with a large number of field instantaneous emission data and corresponding activity data collected by the Portable Emission Measurement System (PEMS), emission rates are derived for different vehicle specific power (VSP) bins. Then, 2002 sets of trajectory data, an equivalent of about 140,000 sets of second-by-second activity data, are obtained from Global Position Systems (GPSs)-equipped diesel buses in Beijing. The delay and the emission factors of each trajectory are estimated. Then, by using baseline emission factors for two types of intersections, e.g. the Arterial @ Arterial Intersection and the Arterial @ Collector, delay correction factors are calculated for the two types of intersections at different congestion levels. Finally, delay correction models are established for adjusting emission factors for each type of intersections and different numbers of stops. A comparative analysis between estimated and field emission factors demonstrates that the delay correction model is reliable. PMID:25659309

  10. 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.

  11. Analysis of multilevel grouped survival data with time-varying regression coefficients.

    PubMed

    Wong, May C M; Lam, K F; Lo, Edward C M

    2011-02-10

    Correlated or multilevel grouped survival data are common in medical and dental research. Two common approaches to analyze such data are the marginal and the random-effects approaches. Models and methods in the literature generally assume that the treatment effect is constant over time. A researcher may be interested in studying whether the treatment effects in a clinical trial vary over time, say fade out gradually. This is of particular clinical value when studying the long-term effect of a treatment. This paper proposed to extend the random effects grouped proportional hazards models by incorporating the possibly time-varying covariate effects into the model in terms of a state-space formulation. The proposed model is very flexible and the estimation can be performed using the MCMC approach with non-informative priors in the Bayesian framework. The method is applied to a data set from a prospective clinical trial investigating the effectiveness of silver diamine fluoride (SDF) and sodium fluoride (NaF) varnish in arresting active dentin caries in the Chinese preschool children. It is shown that the treatment groups with caries removal prior to the topical fluoride applications are most effective in shortening the arrest times in the first 6-month interval, but their effects fade out rapidly since then. The effects of treatment groups without caries removal prior to topical fluoride application drop at a very slow rate and can be considered as more or less constant over time. The applications of SDF solution is found to be more effective than the applications of NaF vanish.

  12. Time-varying, serotype-specific force of infection of dengue virus

    PubMed Central

    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.

    2014-01-01

    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. PMID:24847073

  13. Transient evolution of eigenmodes in dynamic cavities and time-varying media

    NASA Astrophysics Data System (ADS)

    Gradoni, Gabriele; Arnaut, Luk R.

    2015-12-01

    In this paper, we investigate the perturbation of natural eigenmodes of dynamic cavities with boundaries moving at quasi-static speeds relative to the wave velocity. For an arbitrarily shaped source-free cavity, the amplitude of the irrotational mode is modeled as a damped harmonic oscillator with time-varying eigenfrequency, i.e., a parametric oscillator. It is found that the effect of the pure Doppler shift of the resonance frequencies of the eigenmodes is small at nonrelativistic speeds. However, it is known that any spectrum of eigenenergies that is perturbed by a space- and/or time-fluctuating medium can develop frequency shifts of arbitrary magnitude. By using a linear dynamic (time-dependent) shift for the cavity broad resonances, we find that Doppler-like large shifts result in a mere frequency modulation of the total (resultant) field amplitude, while nonuniform red or blue shift can create a hybrid amplitude and frequency modulation. Interestingly, the combined action of red and blue shifts of uniform magnitude can also create a hybrid modulation. If the angle between modal wave vector and stirrer speed is accounted for in the static (time-independent) shift, the resulting red and blue shifts lead to irregular hybrid modulations. This can occur even for regular perturbations in regular cavities. In addition, owing to the stochastic nature of mode-stirred cavities, the effect of random Doppler-like shifts is also investigated, leading to a Fokker-Planck equation whose diffusion coefficient shows quadratic dependence on the mode amplitude. Thus, the analysis of random perturbations offers an effective framework for observed instantaneous Doppler effects in closed electromagnetic environments. The mathematical framework obtained in terms of stochastic differential equations is useful to predict the nonstationary response of dynamic cavities with complicated or unknown boundary geometry.

  14. The time-varying association between perceived stress and hunger within and between days

    PubMed Central

    Huh, Jimi; Shiyko, Mariya; Keller, Stefen; Dunton, Genevieve; Schembre, Susan M.

    2015-01-01

    Objective Examine the association between perceived stress and hunger continuously over a week in free-living individuals. Methods Forty five young adults (70% women, 30% overweight/obese) ages 18 to 24 years (Mean = 20.7, SD = 1.5), with BMI between 17.4 and 36.3 kg/m2 (Mean = 23.6, SD = 4.0) provided between 513 and 577 concurrent ratings of perceived stress and hunger for 7 days via hourly, text messaging assessments and real-time eating records. Time-varying effect modeling was used to explore whether the within-day fluctuations in stress are related to perceived hunger assessed on a momentary basis. Results A generally positive stress–hunger relationship was confirmed, but we found that the strength of the relationship was not linear. Rather, the magnitude of the association between perceived stress and hunger changed throughout the day such that only during specific time intervals were stress and hunger significantly related. Specifically, the strength of the positive association peaked during late afternoon hours on weekdays (β = 0.31, p < .05) and it peaked during evening hours on weekend days (β = 0.56, p < .05). Conclusion This is the first empirical study to demonstrate potentially maladaptive, nonlinear stress–hunger associations that peak in the afternoon or evening hours. While we are unable to infer causality from these analyses, our findings provide empirical evidence for a potentially high-risk time of day for stress-induced eating. Replication of these findings in larger, more diverse samples will aid with the design and implementation of real-time intervention studies aimed at reducing stress-eating. PMID:25666299

  15. 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. PMID:27312479

  16. 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.

  17. Autonomic responses to cold face stimulation in sickle cell disease: a time-varying model analysis.

    PubMed

    Chalacheva, Patjanaporn; Kato, Roberta M; Sangkatumvong, Suvimol; Detterich, Jon; Bush, Adam; Wood, John C; Meiselman, Herbert; Coates, Thomas D; Khoo, Michael C K

    2015-07-14

    Sickle cell disease (SCD) is characterized by sudden onset of painful vaso-occlusive crises (VOC), which occur on top of the underlying chronic blood disorder. The mechanisms that trigger VOC remain elusive, but recent work suggests that autonomic dysfunction may be an important predisposing factor. Heart-rate variability has been employed in previous studies, but the derived indices have provided only limited univariate information about autonomic cardiovascular control in SCD. To circumvent this limitation, a time-varying modeling approach was applied to investigate the functional mechanisms relating blood pressure (BP) and respiration to heart rate and peripheral vascular resistance in healthy controls, untreated SCD subjects and SCD subjects undergoing chronic transfusion therapy. Measurements of respiration, heart rate, continuous noninvasive BP and peripheral vascular resistance were made before, during and after the application of cold face stimulation (CFS), which perturbs both the parasympathetic and sympathetic nervous systems. Cardiac baroreflex sensitivity estimated from the model was found to be impaired in nontransfused SCD subjects, but partially restored in SCD subjects undergoing transfusion therapy. Respiratory-cardiac coupling gain was decreased in SCD and remained unchanged by chronic transfusion. These results are consistent with autonomic dysfunction in the form of impaired parasympathetic control and sympathetic overactivity. As well, CFS led to a significant reduction in vascular resistance baroreflex sensitivity in the nontransfused SCD subjects but not in the other groups. This blunting of the baroreflex control of peripheral vascular resistance during elevated sympathetic drive could be a potential factor contributing to the triggering of VOC in SCD. PMID:26177958

  18. Autonomic responses to cold face stimulation in sickle cell disease: a time-varying model analysis

    PubMed Central

    Chalacheva, Patjanaporn; Kato, Roberta M; Sangkatumvong, Suvimol; Detterich, Jon; Bush, Adam; Wood, John C; Meiselman, Herbert; Coates, Thomas D; Khoo, Michael C K

    2015-01-01

    Sickle cell disease (SCD) is characterized by sudden onset of painful vaso-occlusive crises (VOC), which occur on top of the underlying chronic blood disorder. The mechanisms that trigger VOC remain elusive, but recent work suggests that autonomic dysfunction may be an important predisposing factor. Heart-rate variability has been employed in previous studies, but the derived indices have provided only limited univariate information about autonomic cardiovascular control in SCD. To circumvent this limitation, a time-varying modeling approach was applied to investigate the functional mechanisms relating blood pressure (BP) and respiration to heart rate and peripheral vascular resistance in healthy controls, untreated SCD subjects and SCD subjects undergoing chronic transfusion therapy. Measurements of respiration, heart rate, continuous noninvasive BP and peripheral vascular resistance were made before, during and after the application of cold face stimulation (CFS), which perturbs both the parasympathetic and sympathetic nervous systems. Cardiac baroreflex sensitivity estimated from the model was found to be impaired in nontransfused SCD subjects, but partially restored in SCD subjects undergoing transfusion therapy. Respiratory-cardiac coupling gain was decreased in SCD and remained unchanged by chronic transfusion. These results are consistent with autonomic dysfunction in the form of impaired parasympathetic control and sympathetic overactivity. As well, CFS led to a significant reduction in vascular resistance baroreflex sensitivity in the nontransfused SCD subjects but not in the other groups. This blunting of the baroreflex control of peripheral vascular resistance during elevated sympathetic drive could be a potential factor contributing to the triggering of VOC in SCD. PMID:26177958

  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 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

  1. 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.

  2. 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.

  3. Hearing loss from interrupted, intermittent, and time varying non-Gaussian noise exposure: The applicability of the equal energy hypothesis.

    PubMed

    Hamernik, Roger P; Qiu, Wei; Davis, Bob

    2007-10-01

    Sixteen groups of chinchillas (N=140) were exposed to various equivalent energy noise paradigms at 100 dB(A) or 103 dB(A) SPL. Eleven groups received an interrupted, intermittent, and time varying (IITV) non-Gaussian exposure quantified by the kurtosis statistic. The IITV exposures, which lasted for 8 hday, 5 daysweek for 3 weeks, were designed to model some of the essential features of an industrial workweek. Five equivalent energy reference groups were exposed to either a Gaussian or non-Gaussian 5 days, 24 hday continuous noise. Evoked potentials were used to estimate hearing thresholds and surface preparations of the organ of Corti quantified the sensory cell population. For IITV exposures at an equivalent energy and kurtosis, the temporal variations in level did not alter trauma and in some cases the IITV exposures produced results similar to those found for the 5 day continuous exposures. Any increase in kurtosis at a fixed energy was accompanied by an increase in noise-induced trauma. These results suggest that the equal energy hypothesis is an acceptable approach to evaluating noise exposures for hearing conservation purposes provided that the kurtosis of the amplitude distribution is taken into consideration. Temporal variations in noise levels seem to have little effect on trauma. PMID:17902860

  4. Contribution of time-varying measures of health behaviours to socioeconomic inequalities in mortality: how to understand the underlying mechanisms?

    PubMed

    Oude Groeniger, Joost; van Lenthe, Frank J

    2016-10-01

    A higher prevalence of unhealthy behaviours in lower socioeconomic groups contributes to socioeconomic inequalities in mortality. Recent cohort studies suggest that the contribution of health behaviours to socioeconomic inequalities in mortality is larger when measured repeatedly over time ('time-varying') instead of once only ('time-fixed'). Explanations for a larger contribution of health behaviours, however, are hardly discussed in the current literature, and appear to be more complex than a widening of inequalities in health behaviours over time alone. We describe the use of time-varying health behaviours to examine socioeconomic inequalities in mortality, systematically listing underlying mechanisms that may cause differences between time-varying and time-fixed models, and show that these mechanisms may be specific for each health behaviour. The use of time-varying health behaviours advances our understanding of the explanation of socioeconomic inequalities in mortality, but underlying mechanisms must be carefully examined.

  5. 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...

  6. Dynamics of a hypoid gear pair considering the effects of time-varying mesh parameters and backlash nonlinearity

    NASA Astrophysics Data System (ADS)

    Wang, Jun; Lim, Teik C.; Li, Mingfeng

    2007-11-01

    A generalized nonlinear time-varying (NLTV) dynamic model of a hypoid gear pair with backlash nonlinearity is formulated which is also applicable to spur, helical, spiral bevel and worm gears. Firstly, the fundamental harmonic form of time-varying mesh parameters is used to study the effects of mesh parameter variations on the dynamic response, and the interactions between them and backlash nonlinearity. The analysis also examines the effects of mean load and mesh damping. Secondly, based on a three-dimensional quasi-static tooth contact analysis, a new significantly more exact time-varying mesh model is proposed, which describes the true mesh characteristics of hypoid gear pairs. The enhanced time-varying mesh model is applied to perform further dynamic analysis. Computational results reveal numerous interesting nonlinear characteristics, such as jump discontinuities, sub-harmonic and chaotic behaviors, especially for lightly loaded and lightly damped cases.

  7. 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.

  8. Performance of time-varying predictors in multilevel models under an assumption of fixed or random effects.

    PubMed

    Baird, Rachel; Maxwell, Scott E

    2016-06-01

    Time-varying predictors in multilevel models are a useful tool for longitudinal research, whether they are the research variable of interest or they are controlling for variance to allow greater power for other variables. However, standard recommendations to fix the effect of time-varying predictors may make an assumption that is unlikely to hold in reality and may influence results. A simulation study illustrates that treating the time-varying predictor as fixed may allow analyses to converge, but the analyses have poor coverage of the true fixed effect when the time-varying predictor has a random effect in reality. A second simulation study shows that treating the time-varying predictor as random may have poor convergence, except when allowing negative variance estimates. Although negative variance estimates are uninterpretable, results of the simulation show that estimates of the fixed effect of the time-varying predictor are as accurate for these cases as for cases with positive variance estimates, and that treating the time-varying predictor as random and allowing negative variance estimates performs well whether the time-varying predictor is fixed or random in reality. Because of the difficulty of interpreting negative variance estimates, 2 procedures are suggested for selection between fixed-effect and random-effect models: comparing between fixed-effect and constrained random-effect models with a likelihood ratio test or fitting a fixed-effect model when an unconstrained random-effect model produces negative variance estimates. The performance of these 2 procedures is compared. (PsycINFO Database Record

  9. Mixed Effects Models for Recurrent Events Data with Partially Observed Time-Varying Covariates: Ecological Momentary Assessment of Smoking

    PubMed Central

    Rathbun, Stephen L.; Shiffman, Saul

    2015-01-01

    Summary Cigarette smoking is a prototypical example of a recurrent event. The pattern of recurrent smoking events may depend on time-varying covariates including mood and environmental variables. Fixed effects and frailty models for recurrent events data assume that smokers have a common association with time-varying covariates. We develop a mixed effects version of a recurrent events model that may be used to describe variation among smokers in how they respond to those covariates, potentially leading to the development of individual-based smoking cessation therapies. Our method extends the modified EM algorithm of Steele (1996) for generalized mixed models to recurrent events data with partially observed time-varying covariates. It is offered as an alternative to the method of Rizopoulos, Verbeke and Lesaffre (2009) who extended Steele’s (1996) algorithm to a joint-model for the recurrent events data and time-varying covariates. Our approach does not require a model for the time-varying covariates, but instead assumes that the time-varying covariates are sampled according to a Poisson point process with known intensity. Our methods are well suited to data collected using Ecological Momentary Assessment (EMA), a method of data collection widely used in the behavioral sciences to collect data on emotional state and recurrent events in the every-day environments of study subjects using electronic devices such as Personal Digital Assistants (PDA) or smart phones. PMID:26410189

  10. 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

  11. Time-varying loss forecast for an earthquake scenario in Basel, Switzerland

    NASA Astrophysics Data System (ADS)

    Herrmann, Marcus; Zechar, Jeremy D.; Wiemer, Stefan

    2014-05-01

    When an unexpected earthquake occurs, people suddenly want advice on how to cope with the situation. The 2009 L'Aquila quake highlighted the significance of public communication and pushed the usage of scientific methods to drive alternative risk mitigation strategies. For instance, van Stiphout et al. (2010) suggested a new approach for objective evacuation decisions on short-term: probabilistic risk forecasting combined with cost-benefit analysis. In the present work, we apply this approach to an earthquake sequence that simulated a repeat of the 1356 Basel earthquake, one of the most damaging events in Central Europe. A recent development to benefit society in case of an earthquake are probabilistic forecasts of the aftershock occurrence. But seismic risk delivers a more direct expression of the socio-economic impact. To forecast the seismic risk on short-term, we translate aftershock probabilities to time-varying seismic hazard and combine this with time-invariant loss estimation. Compared with van Stiphout et al. (2010), we use an advanced aftershock forecasting model and detailed settlement data to allow us spatial forecasts and settlement-specific decision-making. We quantify the risk forecast probabilistically in terms of human loss. For instance one minute after the M6.6 mainshock, the probability for an individual to die within the next 24 hours is 41 000 times higher than the long-term average; but the absolute value remains at minor 0.04 %. The final cost-benefit analysis adds value beyond a pure statistical approach: it provides objective statements that may justify evacuations. To deliver supportive information in a simple form, we propose a warning approach in terms of alarm levels. Our results do not justify evacuations prior to the M6.6 mainshock, but in certain districts afterwards. The ability to forecast the short-term seismic risk at any time-and with sufficient data anywhere-is the first step of personal decision-making and raising risk

  12. 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

  13. 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.

  14. Prediction of spectral shifts proportional to source distances by time-varying frequency or wavelength selection

    NASA Astrophysics Data System (ADS)

    Guruprasad, V.

    2008-08-01

    Any frequency selective device with an ongoing drift will cause observed spectra to be variously and simultaneously scaled in proportion to their source distances. The reason is that detectors after the drifting selection will integrate instantaneous electric or magnetic field values from successive sinusoids, and these sinusoids would differ in both frequency and phase. Phase differences between frequencies are ordinarily irrelevant, and recalibration procedures at most correct for frequency differences. With drifting selection, however, each integrated field value comes from the sinusoid of the instantaneously selected frequency at its instantaneous received phase, hence the waveform constructed by the integration will follow the drifting selection with a phase acceleration given by the drift rate times the slope of the received phase spectrum. A phase acceleration is literally a frequency shift, and the phase spectrum slope of a received waveform is an asymptotic measure of the source distance, as the path delay presents phase offsets proportional to frequency times the distance, and eventually exceeding all initial phase differences. Tunable optics may soon be fast enough for realizing such shifts by Fourier switching, and could lead to pocket X-ray devices; sources continuously variable from RF to gamma rays; capacity multiplication with jamming and noise immunity in both fibre and radio channels, passive ranging from ground to deep space; etc.

  15. 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.

  16. Effect of time-varying load on degree of bronchoconstriction in the dog.

    PubMed

    Shinozuka, N; Lavoie, J P; Martin, J G; Bates, J H

    1998-10-01

    It is well established that the degree of airway smooth muscle shortening produced by a given dose of bronchial agonist is greatly affected by lung volume. The airways are tethered by parenchymal attachments, the tension of which increases progressively with lung volume, thereby presenting a commensurately increasing hindrance to smooth muscle contraction. Earlier studies (P. F. Dillon, M. O. Aksoy, S. P. Driska, and R. A. Murphy. Science 211: 495-497, 1981) presented evidence that smooth muscle contraction initially involves rapidly cycling cross bridges, which then change to noncycling (latch) bridges. They also suggested that most of the muscle shortening occurs during the early rapid cross-bridge phase. This implies that smooth muscle subject to a given load early in contraction should shorten less than when it is subject to the same load later on. An in vitro study (W. Li and N. L. Stephens. Can. J. Physiol. Pharmacol. 72: 1458-1463, 1994) obtained support for this notion. To test this hypothesis in vivo, we measured the changes in lung impedance at 1 and 6 Hz produced in dogs by a bolus intravenous injection of methacholine when lung volume was increased for 10 s at different times after injection. We found that the changes in mechanics were greatly inhibited, whereas lung volume was elevated. However, when lung volume was returned to its initial level, the lung mechanics continued to change at a rate unaffected by the preceding volume change. We conclude that temporary mechanical inhibition of airway smooth muscle shortening in the normal dog in vivo merely delays an otherwise normal course of contraction. PMID:9760342

  17. Latent time-varying factors in longitudinal analysis: a linear mixed hidden Markov model for heart rates

    PubMed Central

    Lagona, Francesco; Jdanov, Dmitri; Shkolnikova, Maria

    2014-01-01

    Longitudinal data are often segmented by unobserved time-varying factors, which introduce latent heterogeneity at the observation level, in addition to heterogeneity across subjects. We account for this latent structure by a linear mixed hidden Markov model. It integrates subject-specific random effects and Markovian sequences of time-varying effects in the linear predictor. We propose an expectation—maximization algorithm for maximum likelihood estimation, based on data augmentation. It reduces to the iterative maximization of the expected value of a complete likelihood function, derived from an augmented dataset with case weights, alternated with weights updating. In a case study of the Survey on Stress Aging and Health in Russia, the model is exploited to estimate the influence of the observed covariates under unobserved time-varying factors, which affect the cardiovascular activity of each subject during the observation period. PMID:24889355

  18. Adaptive backstepping sliding mode control of flexible ball screw drives with time-varying parametric uncertainties and disturbances.

    PubMed

    Dong, Liang; Tang, Wen Cheng

    2014-01-01

    This paper presents a method to model and design servo controllers for flexible ball screw drives with dynamic variations. A mathematical model describing the structural flexibility of the ball screw drive containing time-varying uncertainties and disturbances with unknown bounds is proposed. A mode-compensating adaptive backstepping sliding mode controller is designed to suppress the vibration. The time-varying uncertainties and disturbances represented in finite-term Fourier series can be estimated by updating the Fourier coefficients through function approximation technique. Adaptive laws are obtained from Lyapunov approach to guarantee the convergence and stability of the closed loop system. The simulation results indicate that the tracking accuracy is improved considerably with the proposed scheme when the time-varying parametric uncertainties and disturbances exist.

  19. 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.

  20. 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.

  1. 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.

  2. A vegetation-based time-varying parameterization framework for improving hydrological modeling under non-stationary conditions

    NASA Astrophysics Data System (ADS)

    Sun, Yu; Tian, Fuqiang; Hu, Hongchang

    2015-04-01

    Temporal stability of model parameters is one major concern in hydrological modeling especially under non-stationary conditions including climate change and variation in catchment characteristics. In this study, we focus on the impact of variation in catchment characteristics on model parameters stability. According to the annual cycle of vegetation phenology inferred by the variability of NDVI, we split one year to growth period (May-October) and dormant period (November-April), and calibrate the parameters of a semi-distributed model (the THREW model) to 19 growth periods and 19 dormant periods during 1982-2000 in the upper Han River basin of central China (the largest tributary of Yangtze River). The results show that the calibrated parameters present significant non-stationarity, where the variation magnitude for the dormant periods is larger than that for the growth periods. The variation of the parameters can be attributed to the variation of vegetation cover, which is the most visible and detectable feature in all catchment characteristics experiencing change during the study period. Furthermore, it can be considered as an index representing the self-organization of catchment characteristics due to co-evolution of vegetation, soil, topography, geology, and so on, and even the feedbacks between climate and various catchment characteristics. We develop a time-varying parameterization scheme consisting of 14 unitary regression equations for NDVI and model parameters, and embed this scheme in the hydrological model. The correlation coefficients between model parameters and NDVI are 0.50-0.75 for the growth periods, and 0.42-0.63 for the dormant periods, indicating that the variability of calibrated parameters can reflect the changing conditions of the study area. The simulations of the modified parameterization scheme suggest that considering time instability of model parameters can improve the modeling performance for both high flows and low flows under non

  3. A numerical study on the time-varying attitudes and aerodynamics of freely falling conical graupel

    NASA Astrophysics Data System (ADS)

    Chueh, Chih-Che; Wang, Pao K.

    2016-04-01

    The flow fields and dynamic motions of conical graupel of diameters 0.5-5mm falling in air of 800 hPa and -20°C are studied by solving the transient Navier-Stokes equations numerically for flow past the conical graupel and the body dynamics equations representing the 6-degrees-of-freedom motion that determines the position and orientation of the graupel in response to the hydrodynamic force of the flow fields. The shape of conical graupel made through a simple but practical existing mathematical equation allows us to have an uneven mass distribution, which is generally believed to have great influence on ice particles' orientations while falling when inertial force becomes increasingly dominant over other effects. The simulated motions include vertical fall, lateral translation, sailing, rotation and pendulum swing. The computed flow fields are characterized in terms of streamtrace patterns as well as the vorticity magnitude fields, and the corresponding motion of the conical graupel is physically featured by looking upon the graupel surface distributions of pressure coefficient, torques contributed by both pressure as well as viscous effects. Tumbling occurs when an initial orientation of the graupel is 160° about Y axis, and the torque contributed by the pressure effect is dominant over that contributed by the viscous effect.

  4. 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.

  5. 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. PMID:25449286

  6. 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.

  7. L0-regularized time-varying sparse inverse covariance estimation for tracking dynamic fMRI brain networks.

    PubMed

    Zening Fu; Sheng Han; Ao Tan; Yiheng Tu; Zhiguo Zhang

    2015-08-01

    Exploration of time-varying functional brain connectivity based on functional Magnetic Resonance Imaging (fMRI) data is important for understanding dynamic brain mechanisms. l1-penalized inverse covariance is a common measure for the inference of sparse structure of functional brain networks, and it has been recently extended to estimate time-varying sparse brain networks by using a sliding window and incorporating a smoothing constraint on temporal variation. However, l1 penalty cannot induce maximum sparsity, as compared with l0 penalty, so l0 penalty is supposed to have superior quality on inverse covariance estimation. This paper introduces a novel time-varying sparse inverse covariance estimation method based on dual l0-penalties (DLP). The new DLP method estimates the sparse inverse covariance by minimizing an l0-penalized log-likelihood function and an extra l0 penalty on temporal homogeneity. A cyclic descent optimization algorithm is further developed to localize the minimum of the objective function. Experiment results on simulated signals show that the proposed DLP method can achieve better performance than conventional l1-penalized methods in estimating time-varying sparse network structures under different scenarios.

  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. Statistical distribution of the Wigner-Smith time-delay matrix moments for chaotic cavities

    NASA Astrophysics Data System (ADS)

    Cunden, Fabio Deelan

    2015-06-01

    We derive the joint distribution of the moments Tr Qκ(κ ≥1 ) of the Wigner-Smith matrix for a chaotic cavity supporting a large number of scattering channels n . This distribution turns out to be asymptotically Gaussian, and we compute explicitly averages and covariances. The results are in a compact form and have been verified numerically. The general methodology of proof and computations has a wide range of applications.

  10. 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

  11. GRACE, time-varying gravity, Earth system dynamics and climate change.

    PubMed

    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.

  12. 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.; Laska, Jason A.; Sullivan, Blair D.

    2016-10-20

    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

  13. 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.

  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. A Lightweight Remote Parallel Visualization Platform for Interactive Massive Time-varying Climate Data Analysis

    NASA Astrophysics Data System (ADS)

    Li, J.; Zhang, T.; Huang, Q.; Liu, Q.

    2014-12-01

    Today's climate datasets are featured with large volume, high degree of spatiotemporal complexity and evolving fast overtime. As visualizing large volume distributed climate datasets is computationally intensive, traditional desktop based visualization applications fail to handle the computational intensity. Recently, scientists have developed remote visualization techniques to address the computational issue. Remote visualization techniques usually leverage server-side parallel computing capabilities to perform visualization tasks and deliver visualization results to clients through network. In this research, we aim to build a remote parallel visualization platform for visualizing and analyzing massive climate data. Our visualization platform was built based on Paraview, which is one of the most popular open source remote visualization and analysis applications. To further enhance the scalability and stability of the platform, we have employed cloud computing techniques to support the deployment of the platform. In this platform, all climate datasets are regular grid data which are stored in NetCDF format. Three types of data access methods are supported in the platform: accessing remote datasets provided by OpenDAP servers, accessing datasets hosted on the web visualization server and accessing local datasets. Despite different data access methods, all visualization tasks are completed at the server side to reduce the workload of clients. As a proof of concept, we have implemented a set of scientific visualization methods to show the feasibility of the platform. Preliminary results indicate that the framework can address the computation limitation of desktop based visualization applications.

  16. The stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays and reaction-diffusion terms.

    PubMed

    Tan, Jie; Li, Chuandong; Huang, Tingwen

    2015-04-01

    The global asymptotic stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays and reaction-diffusion terms is investigated. Under some suitable assumptions and using Lyapunov-Krasovskii functional method, we apply the linear matrix inequality technique to propose some new sufficient conditions for the global asymptotic stability of the addressed model in the stochastic sense. The mixed time delays comprise both the time-varying and continuously distributed delays. The effectiveness of the theoretical result is illustrated by a numerical example.

  17. Exact model reduction with delays: closed-form distributions and extensions to fully bi-directional monomolecular reactions

    PubMed Central

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

    2014-01-01

    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. PMID:24694895

  18. Time-varying correlations between delta EEG power and heart rate variability in midlife women: The SWAN Sleep Study

    PubMed Central

    Rothenberger, Scott D.; Krafty, Robert T.; Taylor, Briana J.; Cribbet, Matthew R.; Thayer, Julian F.; Buysse, Daniel J.; Kravitz, Howard M.; Buysse, Evan D.; Hall, Martica H.

    2014-01-01

    No studies have evaluated the dynamic, time-varying, relationship between delta electroencephalographic (EEG) sleep and high frequency heart rate variability (HF-HRV) in women. Delta EEG and HF-HRV were measured during sleep in 197 midlife women (Mage =52.1, SD =2.2). Delta EEG-HF-HRV correlations in Non-Rapid Eye Movement (NREM) sleep were modeled as whole night averages and as continuous functions of time. The whole-night delta EEG-HF-HRV correlation was positive. Strongest correlations were observed during the first NREM sleep period preceding and following peak delta power. Time-varying correlations between delta EEG-HF-HRV were stronger in participants with sleep-disordered breathing and self-reported insomnia compared to healthy controls. The dynamic interplay between sleep and autonomic activity can be modeled across the night to examine within- and between-participant differences including individuals with and without sleep disorders. PMID:25431173

  19. 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.

  20. Robustness of controllability and observability of linear time-varying systems with application to the emergency control of power systems

    SciTech Connect

    Sastry, S. S.; Desoer, C. A.

    1980-01-01

    Fixed point methods from nonlinear anaysis are used to establish conditions under which the uniform complete controllability of linear time-varying systems is preserved under non-linear perturbations in the state dynamics and the zero-input uniform complete observability of linear time-varying systems is preserved under non-linear perturbation in the state dynamics and output read out map. Algorithms for computing the specific input to steer the perturbed systems from a given initial state to a given final state are also presented. As an application, a very specific emergency control of an interconnected power system is formulated as a steering problem and it is shown that this emergency control is indeed possible in finite time.

  1. 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.

  2. Continuous higher-order sliding mode control with time-varying gain for a class of uncertain nonlinear systems.

    PubMed

    Han, Yaozhen; Liu, Xiangjie

    2016-05-01

    This paper presents a continuous higher-order sliding mode (HOSM) control scheme with time-varying gain for a class of uncertain nonlinear systems. The proposed controller is derived from the concept of geometric homogeneity and super-twisting algorithm, and includes two parts, the first part of which achieves smooth finite time stabilization of pure integrator chains. The second part conquers the twice differentiable uncertainty and realizes system robustness by employing super-twisting algorithm. Particularly, time-varying switching control gain is constructed to reduce the switching control action magnitude to the minimum possible value while keeping the property of finite time convergence. Examples concerning the perturbed triple integrator chains and excitation control for single-machine infinite bus power system are simulated respectively to demonstrate the effectiveness and applicability of the proposed approach. PMID:26920085

  3. Continuous higher-order sliding mode control with time-varying gain for a class of uncertain nonlinear systems.

    PubMed

    Han, Yaozhen; Liu, Xiangjie

    2016-05-01

    This paper presents a continuous higher-order sliding mode (HOSM) control scheme with time-varying gain for a class of uncertain nonlinear systems. The proposed controller is derived from the concept of geometric homogeneity and super-twisting algorithm, and includes two parts, the first part of which achieves smooth finite time stabilization of pure integrator chains. The second part conquers the twice differentiable uncertainty and realizes system robustness by employing super-twisting algorithm. Particularly, time-varying switching control gain is constructed to reduce the switching control action magnitude to the minimum possible value while keeping the property of finite time convergence. Examples concerning the perturbed triple integrator chains and excitation control for single-machine infinite bus power system are simulated respectively to demonstrate the effectiveness and applicability of the proposed approach.

  4. Linking the fractional derivative and the Lomnitz creep law to non-Newtonian time-varying viscosity

    NASA Astrophysics Data System (ADS)

    Pandey, Vikash; Holm, Sverre

    2016-09-01

    Many of the most interesting complex media are non-Newtonian and exhibit time-dependent behavior of thixotropy and rheopecty. They may also have temporal responses described by power laws. The material behavior is represented by the relaxation modulus and the creep compliance. On the one hand, it is shown that in the special case of a Maxwell model characterized by a linearly time-varying viscosity, the medium's relaxation modulus is a power law which is similar to that of a fractional derivative element often called a springpot. On the other hand, the creep compliance of the time-varying Maxwell model is identified as Lomnitz's logarithmic creep law, making this possibly its first direct derivation. In this way both fractional derivatives and Lomnitz's creep law are linked to time-varying viscosity. A mechanism which yields fractional viscoelasticity and logarithmic creep behavior has therefore been found. Further, as a result of this linking, the curve-fitting parameters involved in the fractional viscoelastic modeling, and the Lomnitz law gain physical interpretation.

  5. Exploratory time varying lagged regression: modeling association of cognitive and functional trajectories with expected clinic visits in older adults.

    PubMed

    Sentürk, Damla; Ghosh, Samiran; Nguyen, Danh V

    2014-05-01

    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.

  6. Nonlinear finite element model updating of an infilled frame based on identified time-varying modal parameters during an earthquake

    NASA Astrophysics Data System (ADS)

    Asgarieh, Eliyar; Moaveni, Babak; Stavridis, Andreas

    2014-11-01

    A model updating methodology is proposed for calibration of nonlinear finite element (FE) models simulating the behavior of real-world complex civil structures subjected to seismic excitations. In the proposed methodology, parameters of hysteretic material models assigned to elements (or substructures) of a nonlinear FE model are updated by minimizing an objective function. The objective function used in this study is the misfit between the experimentally identified time-varying modal parameters of the structure and those of the FE model at selected time instances along the response time history. The time-varying modal parameters are estimated using the deterministic-stochastic subspace identification method which is an input-output system identification approach. The performance of the proposed updating method is evaluated through numerical and experimental applications on a large-scale three-story reinforced concrete frame with masonry infills. The test structure was subjected to seismic base excitations of increasing amplitude at a large outdoor shake-table. A nonlinear FE model of the test structure has been calibrated to match the time-varying modal parameters of the test structure identified from measured data during a seismic base excitation. The accuracy of the proposed nonlinear FE model updating procedure is quantified in numerical and experimental applications using different error metrics. The calibrated models predict the exact simulated response very accurately in the numerical application, while the updated models match the measured response reasonably well in the experimental application.

  7. Neural-Dynamic-Method-Based Dual-Arm CMG Scheme With Time-Varying Constraints Applied to Humanoid Robots.

    PubMed

    Zhang, Zhijun; Li, Zhijun; Zhang, Yunong; Luo, Yamei; Li, Yuanqing

    2015-12-01

    We propose a dual-arm cyclic-motion-generation (DACMG) scheme by a neural-dynamic method, which can remedy the joint-angle-drift phenomenon of a humanoid robot. In particular, according to a neural-dynamic design method, first, a cyclic-motion performance index is exploited and applied. This cyclic-motion performance index is then integrated into a quadratic programming (QP)-type scheme with time-varying constraints, called the time-varying-constrained DACMG (TVC-DACMG) scheme. The scheme includes the kinematic motion equations of two arms and the time-varying joint limits. The scheme can not only generate the cyclic motion of two arms for a humanoid robot but also control the arms to move to the desired position. In addition, the scheme considers the physical limit avoidance. To solve the QP problem, a recurrent neural network is presented and used to obtain the optimal solutions. Computer simulations and physical experiments demonstrate the effectiveness and the accuracy of such a TVC-DACMG scheme and the neural network solver.

  8. Characterization of time-varying macroscopic electro-chemo-mechanical behavior of SOFC subjected to Ni-sintering in cermet microstructures

    NASA Astrophysics Data System (ADS)

    Muramatsu, M.; Terada, K.; Kawada, T.; Yashiro, K.; Takahashi, K.; Takase, S.

    2015-10-01

    In order to perform stress analyses of a solid oxide fuel cell (SOFC) under operation, we propose a characterization method of its time-varying macroscopic electro-chemo-mechanical behavior of electrodes by considering the time-varying geometries of anode microstructures due to Ni-sintering. The phase-field method is employed to simulate the micro-scale morphology change with time, from which the time-variation of the amount of triple-phase boundaries is directly predicted. Then, to evaluate the time-variation of the macroscopic oxygen ionic and electronic conductivities and the inelastic properties of the anode electrode, numerical material tests based on the homogenization method are conducted for each state of sintered microstructures. In these homogenization analyses, we also have to consider the dependencies of the properties of constituent materials on the temperature and/or the oxygen potential that is supposed to change within an operation period. To predict the oxygen potential distribution in an overall SOFC structure under long-period operation, which determines reduction-induced expansive/contractive deformation of oxide materials, an unsteady problem of macroscopic oxygen ionic and electronic conductions is solved. Using the calculated stress-free strains and the homogenized mechanical properties, both of which depend on the operational environment, we carry out the macroscopic stress analysis of the SOFC.

  9. Consensus of Euler-Lagrange systems networked by sampled-data information with probabilistic time delays.

    PubMed

    Ma, Chao; Shi, Peng; Zhao, Xudong; Zeng, Qingshuang

    2015-06-01

    This paper investigates the consensus problem of multiple Euler-Lagrange systems under directed topology. Unlike the common assumptions on continuous-time information exchanges, a more realistic sampled-data communication strategy is proposed with probabilistic occurrence of time-varying delays. Both of the sampling period and the delays are assumed to be time-varying, which is more general in some practical situations. In addition, the relative coordinate derivative information is not required in the distributed controllers such that the communication network burden can be further reduced. In particular, a distinct feature of the proposed scheme lies in the fact that it can effectively reduce the energy consumption. By employing the stochastic analysis techniques, sufficient conditions are established to guarantee that the consensus can be achieved. Finally, a numerical example is provided to illustrate the applicability and benefits of the theoretical results.

  10. Stabilizability of linear quadratic state feedback for uncertain fuzzy time-delay systems.

    PubMed

    Wang, Rong-Jyue; Lin, Wei-Wei; Wang, Wen-June

    2004-04-01

    This paper investigates the problem of designing a fuzzy state feedback controller to stabilize an uncertain fuzzy system with time-varying delay. Based on Lyapunov criterion and Razumikhin theorem, some sufficient conditions are derived under which the parallel-distributed fuzzy control can stabilize the whole uncertain fuzzy time-delay system asymptotically. By Schur complement, these sufficient conditions can be easily transformed into the problem of LMIs. Furthermore, the tolerable bound of the perturbation is also obtained. A practical example based on the continuous stirred tank reactor (CSTR) model is given to illustrate the control design and its effectiveness.

  11. 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

  12. Centralized and decentralized global outer-synchronization of asymmetric recurrent time-varying neural network by data-sampling.

    PubMed

    Lu, Wenlian; Zheng, Ren; Chen, Tianping

    2016-03-01

    In this paper, we discuss outer-synchronization of the asymmetrically connected recurrent time-varying neural networks. By using both centralized and decentralized discretization data sampling principles, we derive several sufficient conditions based on three vector norms to guarantee that the difference of any two trajectories starting from different initial values of the neural network converges to zero. The lower bounds of the common time intervals between data samples in centralized and decentralized principles are proved to be positive, which guarantees exclusion of Zeno behavior. A numerical example is provided to illustrate the efficiency of the theoretical results.

  13. Pilot-aided chip-interleaved DS-CDMA transmission over time-varying channels (Invited Paper)

    NASA Astrophysics Data System (ADS)

    Na, Yanxin; Saquib, Mohammad; Win, Moe Z.

    2005-05-01

    Time-varying multipath fading associated with the wireless link limit the capacity of a wireless system. To adapt to this adverse radio environment efficiently, we investigate the use of a pilot-aided fade-resistant transmission scheme for the uplink of a chip-interleaved code division multiple access (CDMA) system. We analyze the trade-off between the number of diversity branches and the channel estimation error. We derive the optimum ratio of pilot signal power to information signal power. Our numerical study indicates that depending on the transmitter power and channel condition, the proposed system is capable of outperforming the conventional CDMA system.

  14. 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

  15. Experimental measurement of a time-varying optical path difference using the small-aperture beam technique

    NASA Astrophysics Data System (ADS)

    Hugo, Ronald J.; Jumper, Eric J.

    1993-12-01

    This paper discusses the use of time series of the jitter angle of multiple, small-aperture probe beams as they emerge from a turbulent, optically-active flow field to quantify the time-varying optical path difference (OPD). Techniques to reconstruct a complete time series of instantaneous realizations of the OPD are first applied to a numerically-generated flow field and then to an experimental flow field. The flow field studied was that for the transitionally- turbulent region of a heated, two-dimensional jet. From these OPD histories spatial and temporal frequencies characterizing the OPD's are extracted. The relevance of these results to adaptive-optic devices is discussed.

  16. Estimation and Identification of Time-Varying Long-Term Fading Channels via the Particle Filter and the EM Algorithm

    SciTech Connect

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

    2011-01-01

    In this paper, we are concerned with the estimation and identification of time-varying wireless long-term fading channels. The dynamics of the fading channels are captured using a mean-reverting linear stochastic differential equation driven by a Brownian motion. Recursive estimation and identification algorithms solely from received signal strength data are developed. These algorithms are based on combining the particle filter (PF) with the expectation maximization (EM) algorithm that estimate and identify the power path-loss of the channel and its parameters, respectively. Numerical results are provided to evaluate the accuracy of the proposed algorithms.

  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. Quantum key distribution with delayed privacy amplification and its application to the security proof of a two-way deterministic protocol

    NASA Astrophysics Data System (ADS)

    Fung, Chi-Hang Fred; Ma, Xiongfeng; Chau, H. F.; Cai, Qing-Yu

    2012-03-01

    Privacy amplification (PA) is an essential postprocessing step in quantum key distribution (QKD) for removing any information an eavesdropper may have on the final secret key. In this paper, we consider delaying PA of the final key after its use in one-time pad encryption and prove its security. We prove that the security and the key generation rate are not affected by delaying PA. Delaying PA has two applications: it serves as a tool for significantly simplifying the security proof of QKD with a two-way quantum channel, and also it is useful in QKD networks with trusted relays. To illustrate the power of the delayed PA idea, we use it to prove the security of a qubit-based two-way deterministic QKD protocol which uses four states and four encoding operations.

  19. 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.

  20. 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

    2016-04-01

    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