With the unique erggdicity, i rregularity, and.special ability to avoid being trapped in local optima, chaos optimization has been a novel global optimization technique and has attracted considerable attention for a...With the unique erggdicity, i rregularity, and.special ability to avoid being trapped in local optima, chaos optimization has been a novel global optimization technique and has attracted considerable attention for application in various fields, such as nonlinear programming problems. In this article, a novel neural network nonlinear predic-tive control （NNPC） strategy baseed on the new Tent-map chaos optimization algorithm （TCOA） is presented. Thefeedforward neural network＇is used as the multi-step predictive model. In addition, the TCOA is applied to perform the nonlinear rolling optimization to enhance the convergence and accuracy in the NNPC. Simulation on a labora-tory-scale liquid-level system is given to illustrate the effectiveness of the proposed method.展开更多
We present a simple three-neuron Hopfield neural network as a tentative model to illustrate the perspective alternation of Necker cube. This neural network has a chaotic attractor with two "leaves", each lea...We present a simple three-neuron Hopfield neural network as a tentative model to illustrate the perspective alternation of Necker cube. This neural network has a chaotic attractor with two "leaves", each leaf can be regarded as a dynamic process corresponding a feature of the Necker cube. This tentative model suggests another manifestation of the role of chaos in information processing.展开更多
基金Supported by the National Natural Science Foundation of China （No.60374037, No.60574036）, the Program for New Century Excellent Talents in University of China （NCET）, the Specialized Research Fund for the Doctoral Program of Higher Education of China （No.20050055013）, .and the 0pening Project Foundation of National Lab of Industrial Control Technology （No.0708008）.
文摘With the unique erggdicity, i rregularity, and.special ability to avoid being trapped in local optima, chaos optimization has been a novel global optimization technique and has attracted considerable attention for application in various fields, such as nonlinear programming problems. In this article, a novel neural network nonlinear predic-tive control （NNPC） strategy baseed on the new Tent-map chaos optimization algorithm （TCOA） is presented. Thefeedforward neural network＇is used as the multi-step predictive model. In addition, the TCOA is applied to perform the nonlinear rolling optimization to enhance the convergence and accuracy in the NNPC. Simulation on a labora-tory-scale liquid-level system is given to illustrate the effectiveness of the proposed method.
基金Supported in part by National Natural Science Foundation of China under Grant No. 10972082
文摘We present a simple three-neuron Hopfield neural network as a tentative model to illustrate the perspective alternation of Necker cube. This neural network has a chaotic attractor with two "leaves", each leaf can be regarded as a dynamic process corresponding a feature of the Necker cube. This tentative model suggests another manifestation of the role of chaos in information processing.
