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Using the property of universal approximation of multilayer perceptron neural network, a class of discrete nonlinear dynamical systems are modeled by a perceptron with two hidden layers. A backpropagation algorithm is then used to train the model to identify the nonlinear systems to a desired level of accuracy. Based on the identified model, a… (More)

In this paper, we present a new model of discrete neural associative memories and its design rule. The most important feature of this new model is that a static mapping instead of the dynamic convergent process is used to retrieve the stored messages. The new model features a two-layer structure, with feedforward connections only and uses two kinds of… (More)

This paper tries to demonstrate how a heuristic neural control approach can be used to solve a complex nonlinear control problem. The control task is to swing up a pendulum mounted on a cart from its stable position (vertically down) to the zero state (up right) and keep it there by applying a sequence of two opposing constant forces of equal magnitude to… (More)

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