The Experts below are selected from a list of 303 Experts worldwide ranked by ideXlab platform
Li Yang - One of the best experts on this subject based on the ideXlab platform.
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Existence and exponential stability of periodic solution for stochastic Hopfield neural networks on time scales
Neurocomputing, 2015Co-Authors: Li YangAbstract:In this paper, by using the Contraction Mapping Theorem and Gronwall?s Inequality on time scales, we establish some sufficient conditions on the existence and exponential stability of periodic solutions for a class of stochastic neural networks on time scales. Moreover, we present an example to illustrate the feasibility of our results and to show that the continuous-time neural network and its discrete-time analogue have the same dynamical behaviors.
Amit Ailon - One of the best experts on this subject based on the ideXlab platform.
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Output controllers based on iterative schemes for set-point regulation of uncertain flexible-joint robot models
Automatica, 1996Co-Authors: Amit AilonAbstract:This paper considers the set-point regulation problem of a flexible-joint robot with unknown parameters where only position measurements are available. The proposed iterative schemes guarantee that every system response converges to an arbitrarily small neighborhood of the equilibrium point. An essential tool in the present approach is the Contraction Mapping Theorem.
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Analysis and Synthesis of an Output Feedback for an Uncertain Robot Model with Flexible Joints
IFAC Proceedings Volumes, 1995Co-Authors: Amit AilonAbstract:Abstract This study considers the set-point regulation problem of a flexible-joint robot with uncertain parameters and unknown gravity forces when only position measurements are available for the controller. An essential tool in the present approach is the Contraction Mapping Theorem. An analytical solution to the underlying control problem is presented. Some practical issues associated with the implementation of the controller-observer are considered.
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An approach for set-point regulation of electrically driven flexible-joint robots with uncertain parameters
Proceedings of the 1998 IEEE International Conference on Control Applications (Cat. No.98CH36104), 1Co-Authors: Amit AilonAbstract:This study considers the set-point regulation control problem of a rigid-link flexible-joint electrically driven robot manipulator with model uncertainties and an unknown payload. The proposed control scheme is derived from the Contraction Mapping Theorem. The resulting controller is essentially based on a simple linear controller.
Karl Schmedders - One of the best experts on this subject based on the ideXlab platform.
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discrete time dynamic principal agent models Contraction Mapping Theorem and computational treatment
Quantitative Economics, 2020Co-Authors: Philipp Renner, Karl SchmeddersAbstract:We consider discrete‐time dynamic principal–agent problems with continuous choice sets and potentially multiple agents. We prove the existence of a unique solution for the principal's value function only assuming continuity of the functions and compactness of the choice sets. We do this by a Contraction Mapping Theorem and so also obtain a convergence result for the value function iteration. To numerically compute a solution for the problem, we have to solve a collection of static principal–agent problems at each iteration. As a result, in the discrete‐time setting solving the static problem is the difficult step. If the agent's expected utility is a rational function of his action, then we can transform the bi‐level optimization problem into a standard nonlinear program. The final results of our solution method are numerical approximations of the policy and value functions for the dynamic principal–agent model. We illustrate our solution method by solving variations of two prominent social planning models from the economics literature. Optimal unemployment tax principal–agent model repeated moral hazard C63 D80 D82
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Discrete‐time dynamic principal–agent models: Contraction Mapping Theorem and computational treatment
Quantitative Economics, 2020Co-Authors: Philipp Renner, Karl SchmeddersAbstract:We consider discrete‐time dynamic principal–agent problems with continuous choice sets and potentially multiple agents. We prove the existence of a unique solution for the principal's value function only assuming continuity of the functions and compactness of the choice sets. We do this by a Contraction Mapping Theorem and so also obtain a convergence result for the value function iteration. To numerically compute a solution for the problem, we have to solve a collection of static principal–agent problems at each iteration. As a result, in the discrete‐time setting solving the static problem is the difficult step. If the agent's expected utility is a rational function of his action, then we can transform the bi‐level optimization problem into a standard nonlinear program. The final results of our solution method are numerical approximations of the policy and value functions for the dynamic principal–agent model. We illustrate our solution method by solving variations of two prominent social planning models from the economics literature. Optimal unemployment tax principal–agent model repeated moral hazard C63 D80 D82
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Discrete‐time dynamic principal–agent models: Contraction Mapping Theorem and computational treatment
Quantitative Economics, 2020Co-Authors: Philipp Renner, Karl SchmeddersAbstract:We consider discrete‐time dynamic principal–agent problems with continuous choice sets and potentially multiple agents. We prove the existence of a unique solution for the principal's value function only assuming continuity of the functions and compactness of the choice sets. We do this by a Contraction Mapping Theorem and so also obtain a convergence result for the value function iteration. To numerically compute a solution for the problem, we have to solve a collection of static principal–agent problems at each iteration. As a result, in the discrete‐time setting solving the static problem is the difficult step. If the agent's expected utility is a rational function of his action, then we can transform the bi‐level optimization problem into a standard nonlinear program. The final results of our solution method are numerical approximations of the policy and value functions for the dynamic principal–agent model. We illustrate our solution method by solving variations of two prominent social planning models from the economics literature.
Tohru Ozawa - One of the best experts on this subject based on the ideXlab platform.
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Well-Posedness for the Cauchy Problem for a System of Semirelativistic Equations
Communications in Mathematical Physics, 2015Co-Authors: Kazumasa Fujiwara, Shuji Machihara, Tohru OzawaAbstract:The local well-posedness for the Cauchy problem of a system of semirelativistic equations in one space dimension is shown in the Sobolev space Hs of order s ≥ 0. We apply the standard Contraction Mapping Theorem by using Bourgain type spaces Xs,b. We also use an auxiliary space for the solution in L2 = H0. We give the global well-posedness by this conservation law and the argument of the persistence of regularity.
Yuanguo Zhu - One of the best experts on this subject based on the ideXlab platform.
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Uncertain fractional forward difference equations for Riemann–Liouville type
SpringerOpen, 2019Co-Authors: Yuanguo ZhuAbstract:Abstract To model complex systems with discrete-time features and memory effects in the uncertain environment, a definition of an uncertain fractional forward difference equation with Riemann–Liouville-like forward difference is introduced. Moreover, analytic solutions to a type of special linear uncertain fractional difference equations are presented by the Picard iteration method. Then, an existence and uniqueness Theorem of the solutions is proved by applying Banach Contraction Mapping Theorem. Finally, two examples are provided to illustrate the validity of the existence and uniqueness Theorem