Computational Intelligence Techniques for Direct and Inverse Modelling

This book deals with the following real time problems: (i) Development of accurate direct and inverse models of complex plants using some novel architecture and new learning techniques. (ii) Development of new training rules which alleviates local minima problem during training and thus help in generating improved adaptive models. (iii)Development of robust training strategy which is less sensitive to outliers in training and thus to create identification and equalization models which are robust against outliers. In essence, this book proposed many new and efficient algorithms and structure for identification and equalization task such as distributed algorithms, robust algorithms, algorithms for pole-zero identification and Hammerstein models. All these new methods are shown to be better in terms of performance, speed of computation or accuracy of results.