On-line system identification of complex systems using Chebyshev neural networks
Applied Soft Computing
Neural network based optimal control of a biosynthesis process
International Journal of Knowledge-based and Intelligent Engineering Systems - Advanced Intelligent Techniques in Engineering Applications
Neural network prediction of the roll motion of a ship for intelligent course control
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
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This paper presents a new single-layer neural network which is based on orthogonal functions. This neural network is developed to avoid the problems of traditional feedforward neural networks such as the determination of initial weights and the numbers of layers and processing elements. The desired output accuracy determines the required number of processing elements. Because weights are unique, the training of the neural network converges rapidly. An experiment in approximating typical continuous and discrete functions is given. The results show that the neural network has excellent performance in convergence time and approximation error