The Experts below are selected from a list of 117 Experts worldwide ranked by ideXlab platform
R.e. Mortensen - One of the best experts on this subject based on the ideXlab platform.
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Signal processing of power System load data based on stochastic hybrid-state jump-Dynamic System Theory
1991. IEEE International Sympoisum on Circuits and Systems, 1991Co-Authors: R.e. MortensenAbstract:The author considers the problems of filtering and smoothing for LG (linear Gaussian) hybrid-state regime-shift signal processing Systems where a totally observed state process is generated by a linear stochastic differential equation whose parameters are functions of a random jump process called the regime. The objective is to compute the conditional probability distribution of the regime variable at each instant of time, given the data set relevant to filtering or smoothing. The pertinent continuous-time equations are given as well as results of a computer simulation for a power System application.
Sanjeev Sharma - One of the best experts on this subject based on the ideXlab platform.
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An exploratory study of chaos in human-machine System Dynamics
IEEE Transactions on Systems Man and Cybernetics Part A:Systems and Humans, 2006Co-Authors: Sanjeev SharmaAbstract:The human-machine System behavior and performance are Dynamic, nonlinear, and possibly chaotic. Various techniques have been used to describe such Dynamic and nonlinear System characteristics. However, these techniques have rarely been able to accommodate the chaotic behavior of such a nonlinear System. Therefore, this study proposes the use of nonlinear Dynamic System Theory as one possible technique to account for the Dynamic, nonlinear, and possibly chaotic human-machine System characteristics. It briefly describes some of the available nonlinear Dynamic System techniques and illustrates how their application can explain various properties of the human-machine System. A pilot's heart interbeat interval (IBI) and altitude tracking error time series data are used in the illustration. Further, the possible applications of the Theory in various domains of human factors for on-line assessment, short-term prediction, and control of human-machine System behavior and performance are discussed.
Jeanjacques E Slotine - One of the best experts on this subject based on the ideXlab platform.
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2008 special issue where neuroscience and Dynamic System Theory meet autonomous robotics a contracting basal ganglia model for action selection
Neural Networks, 2008Co-Authors: Benoit Girard, Nicolas Tabareau, Quangcuong Pham, Alain Berthoz, Jeanjacques E SlotineAbstract:Action selection, the problem of choosing what to do next, is central to any autonomous agent architecture. We use here a multi-disciplinary approach at the convergence of neuroscience, Dynamical System Theory and autonomous robotics, in order to propose an efficient action selection mechanism based on a new model of the basal ganglia. We first describe new developments of contraction Theory regarding locally projected Dynamical Systems. We exploit these results to design a stable computational model of the cortico-baso-thalamo-cortical loops. Based on recent anatomical data, we include usually neglected neural projections, which participate in performing accurate selection. Finally, the efficiency of this model as an autonomous robot action selection mechanism is assessed in a standard survival task. The model exhibits valuable dithering avoidance and energy-saving properties, when compared with a simple if-then-else decision rule.
Zheng Fang - One of the best experts on this subject based on the ideXlab platform.
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chaotic oscillations of tropical climate a Dynamic System Theory for enso
Journal of the Atmospheric Sciences, 1996Co-Authors: Bin Wang, Zheng FangAbstract:Abstract Based on first principles, a theoretical model for El Nino-Southern Oscillation (ENSO) is derived that consists of prognostic equations for sea surface temperature (SST) and for thermocline variation. Considering only the large-scale, equatorially symmetric, standing basin mode yields a minimum Dynamic System that highlights the cyclic, chaotic, and season-dependent evolution of ENSO. For a steady annual mean basic state, the Dynamic System exhibits a unique limit cycle solution for a fairly restricted range of air-sea coupling. The limit cycle is a stable attractor and represents an intrinsic interannual oscillation of the coupled System. The deepening (rising) of the thermocline in the eastern (western) Pacific leads eastern Pacific warming by a small fraction of the cycle, which agrees well with observation and plays a critical role in sustaining the oscillation. When the nonlinear growth of SST anomalies reaches a critical amplitude, the delayed response of thermocline adjustment provides a n...
Jiantong Wu - One of the best experts on this subject based on the ideXlab platform.
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Data Fusion Estimation of Inertial Sensors Based on Multiscale Stochastic Dynamic Models
2007 International Conference on Mechatronics and Automation, 2007Co-Authors: Xuemei Zhou, Jiantong WuAbstract:In the paper, combing with discrete wavelet transform, Dynamic System Theory and stochastic process Theory establish multiscale stochastic Dynamic models considering scale as variable and present multiscale fusion estimation algorithm in order to realize the optimum estimation of the state. The algorithm may be a method used in no state model. Using the algorithm for gyro signals processing and fusing the observation at different scales, the accuracy is improved obviously. Simulation and test all prove that the algorithm is available.
