The Experts below are selected from a list of 237 Experts worldwide ranked by ideXlab platform
Jintsong Jeng - One of the best experts on this subject based on the ideXlab platform.
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discretizing continuous time controllers via annealing robust Walsh Function networks
IEEE International Conference on Fuzzy Systems, 2006Co-Authors: Jintsong Jeng, Tsutian LeeAbstract:In this paper, a new method, applied the annealing robust Walsh Function networks, is proposed to discretize the continuous-time controller in computer-controlled systems. That is, the annealing robust Walsh Function networks are used to add nonlinearly and to approximate smooth controller with digital neural networks. Hence, the proposed controller is a new smooth controller that can replace original controller and independent of the sampling time under the Sample Theorem. Besides, the input-output stability is proposed for this discretizating continuous-time controller with the annealing robust Walsh Function networks. Consequently, the proposed annealing robust Walsh Function networks controller cannot only discretize the continuous-time controllers, but can also tolerate a wider range of sampling time uncertainty.
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FUZZ-IEEE - Discretizing Continuous-time Controllers via Annealing Robust Walsh Function Networks
2006 IEEE International Conference on Fuzzy Systems, 2006Co-Authors: Shun-feng Su, Jintsong JengAbstract:In this paper, a new method, applied the annealing robust Walsh Function networks, is proposed to discretize the continuous-time controller in computer-controlled systems. That is, the annealing robust Walsh Function networks are used to add nonlinearly and to approximate smooth controller with digital neural networks. Hence, the proposed controller is a new smooth controller that can replace original controller and independent of the sampling time under the Sample Theorem. Besides, the input-output stability is proposed for this discretizating continuous-time controller with the annealing robust Walsh Function networks. Consequently, the proposed annealing robust Walsh Function networks controller cannot only discretize the continuous-time controllers, but can also tolerate a wider range of sampling time uncertainty.
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annealing robust Walsh Function networks for modeling with outliers and digital implementation
International Symposium on Circuits and Systems, 2005Co-Authors: Jintsong Jeng, Chenchia ChuangAbstract:In this paper, an annealing robust Walsh Function network (ARWFN) is proposed for modeling with outliers and its digital implementation. First, an annealing robust learning algorithm (ARLA) is used as the learning algorithm for the ARWFN, and applied to adjust the weights of ARWFNs. That is, an ARLA is proposed to overcome the problems of initialization and the cut-off points in the robust learning algorithm and deal with the model with noise and outliers. It turns out that the ARWFNs with ARLA present a fast convergence speed and are robust against outliers. Second, after the learning results, the ARWFNs are easy to implement using digital circuits. Simulation results are provided to show the validity and applicability of the proposed ARWFNs.
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Digital approximation of fuzzy model via the Walsh Function
Proceedings of the 3rd World Congress on Intelligent Control and Automation (Cat. No.00EX393), 2000Co-Authors: Jintsong JengAbstract:We apply the Walsh Function to approximate the linear and nonlinear consequent parts of a fuzzy model. For the digital implementation of the fuzzy model, we use the Walsh Function to approximate each fuzzy rule under the proposed structure. That is, the consequent part of the fuzzy model can be approximated via the Walsh Function. It turns out that the proposed approximated fuzzy model could be realized via some digital logical devices. We use the recursive least squares method with a forgetting factor to tune the coefficient of the proposed method. Hence, the proposed method not only can implement the fuzzy model via digital logical devices, but also has fast computation speed.
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a new fuzzy modeling based on input output pseudo linearization and Walsh Function
IEEE International Conference on Fuzzy Systems, 1999Co-Authors: Jintsong Jeng, Jeenfong Lin, Chenchia ChuangAbstract:We apply input-output pseudo-linearization and Walsh Function to improve and implement the proposed fuzzy modeling. For the improvement of fuzzy modeling, we employ the input-output pseudo-linearization to extend its applications. Hence, the proposed method, independent of the operating point, can reduce the number of fuzzy rule in the approximation of a nonlinear system. It turns out that the proposed method is more effective and simpler in the design of the number of rule than conventional linearization that is based on operating point. For the implement of fuzzy modeling, we use Walsh Function to approximate each fuzzy rule under the proposed fuzzy system. Therefore, this proposed fuzzy modeling could be realized via some digital logical devices.
W.f. Blyth - One of the best experts on this subject based on the ideXlab platform.
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volterra integral equations solved in fredholm form using Walsh Functions
Anziam Journal, 2004Co-Authors: W.f. Blyth, P WidyaningsihAbstract:Recently Walsh Function methods have been developed for the numerical solution of several classes of problems, mainly linear and nonlinear integral equations of both Volterra and Fredholm types. In addition, modifications of the basic approach have led to the solution of Functional differential equations, variational problems and parameter estimation problems. Linear Volterra integral equations are re-written as Fredholm integral equations with appropriately modified kernels. In this Fredholm equation form, the Walsh Function solution method is more efficient than directly solving the Volterra equation. Walsh Function methods are spectral methods but they have a natural grid interpretation. Multigrid methods and a variation on the use of Richardson extrapolation are used on six well known Volterra test problems, re-written in Fredholm form, to illustrate that these methods provide effective and efficient solution methods.
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a Walsh Function method for a non linear volterra integral equation
Journal of The Franklin Institute-engineering and Applied Mathematics, 2003Co-Authors: B.g. Sloss, W.f. BlythAbstract:A new method for the numerical solution of linear and non-linear Volterra integral equations, using the discontinuous wavelet packets known as the Walsh Functions, is proposed and investigated. Sufficient conditions for the method to converge are derived and a priori error estimates are obtained. Given sufficient regularity conditions on the integral equation, the method is shown to be locally of order two.
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The computational efficiency of a spectral Walsh Function method
Journal of The Franklin Institute-engineering and Applied Mathematics, 1998Co-Authors: B.g. Sloss, W.f. BlythAbstract:Abstract This paper examines the computational efficiency of the new fully discrete versions of the Walsh Function spectral method due to Blyth. Following an introduction to the Walsh Functions and relevant properties, ways of obtaining a fully discrete spectral Walsh Function method are examined. The efficiency of the spectral method is compared with well-known standard schemes where a variable coefficient one-dimensional wave equation is used as the model problem. Some properties, such as how errors increase as t increases, for various t discretized versions of this scheme, are compared.
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A priori error estimates for Corrington's Walsh Function method
Journal of The Franklin Institute-engineering and Applied Mathematics, 1994Co-Authors: B.g. Sloss, W.f. BlythAbstract:Abstract Corrington introduced a Walsh Function method for solving differential equations. In this paper, sufficient conditions for the convergence of Corrington's method are derived. Also, a priori error estimates are given in L2 norm for the approximation of the highest order derivative appearing in the differential equation. The solution to the differential equation may be recovered by integrating this high order derivative.
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A pseudospectral Walsh Function method
Journal of The Franklin Institute-engineering and Applied Mathematics, 1992Co-Authors: B.g. Sloss, W.f. BlythAbstract:Abstract A new pseudospectral Walsh Function method is introduced which solves differential equations efficiently. This is the first time pseudospectral methods have been used in conjunction with Walsh Functions. The method requires the approximation of L 1 means of Functions over certain intervals. Consequently, error estimates for these approximations are derived. Two test problems are solved by this method. The first is the one-dimensional wave equation, and the second differential equation contains exponential coefficients. The latter type sometimes involves computational difficulties when solved by spectral methods.
B.g. Sloss - One of the best experts on this subject based on the ideXlab platform.
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a Walsh Function method for a non linear volterra integral equation
Journal of The Franklin Institute-engineering and Applied Mathematics, 2003Co-Authors: B.g. Sloss, W.f. BlythAbstract:A new method for the numerical solution of linear and non-linear Volterra integral equations, using the discontinuous wavelet packets known as the Walsh Functions, is proposed and investigated. Sufficient conditions for the method to converge are derived and a priori error estimates are obtained. Given sufficient regularity conditions on the integral equation, the method is shown to be locally of order two.
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The computational efficiency of a spectral Walsh Function method
Journal of The Franklin Institute-engineering and Applied Mathematics, 1998Co-Authors: B.g. Sloss, W.f. BlythAbstract:Abstract This paper examines the computational efficiency of the new fully discrete versions of the Walsh Function spectral method due to Blyth. Following an introduction to the Walsh Functions and relevant properties, ways of obtaining a fully discrete spectral Walsh Function method are examined. The efficiency of the spectral method is compared with well-known standard schemes where a variable coefficient one-dimensional wave equation is used as the model problem. Some properties, such as how errors increase as t increases, for various t discretized versions of this scheme, are compared.
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A priori error estimates for Corrington's Walsh Function method
Journal of The Franklin Institute-engineering and Applied Mathematics, 1994Co-Authors: B.g. Sloss, W.f. BlythAbstract:Abstract Corrington introduced a Walsh Function method for solving differential equations. In this paper, sufficient conditions for the convergence of Corrington's method are derived. Also, a priori error estimates are given in L2 norm for the approximation of the highest order derivative appearing in the differential equation. The solution to the differential equation may be recovered by integrating this high order derivative.
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A pseudospectral Walsh Function method
Journal of The Franklin Institute-engineering and Applied Mathematics, 1992Co-Authors: B.g. Sloss, W.f. BlythAbstract:Abstract A new pseudospectral Walsh Function method is introduced which solves differential equations efficiently. This is the first time pseudospectral methods have been used in conjunction with Walsh Functions. The method requires the approximation of L 1 means of Functions over certain intervals. Consequently, error estimates for these approximations are derived. Two test problems are solved by this method. The first is the one-dimensional wave equation, and the second differential equation contains exponential coefficients. The latter type sometimes involves computational difficulties when solved by spectral methods.
Tsutian Lee - One of the best experts on this subject based on the ideXlab platform.
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discretizing continuous time controllers via annealing robust Walsh Function networks
IEEE International Conference on Fuzzy Systems, 2006Co-Authors: Jintsong Jeng, Tsutian LeeAbstract:In this paper, a new method, applied the annealing robust Walsh Function networks, is proposed to discretize the continuous-time controller in computer-controlled systems. That is, the annealing robust Walsh Function networks are used to add nonlinearly and to approximate smooth controller with digital neural networks. Hence, the proposed controller is a new smooth controller that can replace original controller and independent of the sampling time under the Sample Theorem. Besides, the input-output stability is proposed for this discretizating continuous-time controller with the annealing robust Walsh Function networks. Consequently, the proposed annealing robust Walsh Function networks controller cannot only discretize the continuous-time controllers, but can also tolerate a wider range of sampling time uncertainty.
Shun-feng Su - One of the best experts on this subject based on the ideXlab platform.
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FUZZ-IEEE - Discretizing Continuous-time Controllers via Annealing Robust Walsh Function Networks
2006 IEEE International Conference on Fuzzy Systems, 2006Co-Authors: Shun-feng Su, Jintsong JengAbstract:In this paper, a new method, applied the annealing robust Walsh Function networks, is proposed to discretize the continuous-time controller in computer-controlled systems. That is, the annealing robust Walsh Function networks are used to add nonlinearly and to approximate smooth controller with digital neural networks. Hence, the proposed controller is a new smooth controller that can replace original controller and independent of the sampling time under the Sample Theorem. Besides, the input-output stability is proposed for this discretizating continuous-time controller with the annealing robust Walsh Function networks. Consequently, the proposed annealing robust Walsh Function networks controller cannot only discretize the continuous-time controllers, but can also tolerate a wider range of sampling time uncertainty.