By Xingui He
For the 1st time, this e-book units forth the concept that and version for a strategy neural community. You’ll detect how a approach neural community expands the mapping courting among the enter and output of conventional neural networks and significantly complements the expression power of man-made neural networks. exact illustrations assist you visualize info processing stream and the mapping dating among inputs and outputs.
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Additional info for Process Neural Networks: Theory and Applications (Advanced Topics in Science and Technology in China)
Another combination is to adopt some fuzzy logica l rules to control the structure and the values of property parameters of a fuzzy neural network. For example, some learning parameters change according to fuzzy reasoning rules during the learning or the running process for fuzzy neural networks. The parameters u and d in the RPROP algorithm are originall y fixed constant s. The origin al algorithm is greatl y 34 ProcessNeural Networks improved after adopting a fuzzy control method to make the parameters change during the running.
G. (1998) The Theory and Techniques of Fuzzy Knowledge . G. (2001) Turing equivalence of fuzzy max-min operator neural networks. F. (1997) Theoretical frame based on neural network of biometric-model of nerve cells. , Lang KJ. (1989) Phoneme recognition using time-delay neural networks. C. (1994) Locally recurrent globally feedforword networks. A Critical Review of Architectures. A. (1996) Dynamic recurrent neural networks: A dynamical analysis. G. (1991) Introduction to the Theory of Neural Computation .
E) For a group of given sample data, we should research "how to properly classify the learning sample and the test sample to obtain the minimum approximation error of the neural network through learning in the whole sample set". 6 Applications of Feedforward Neural Networks As neural networks need not build accurate mathematical or physical models in advance in order to solve a problem, they are broadly applied to fields that lack prior theory and knowledge or where it is difficult to build accurate mathematical or physical models, such as in scientific research, engineering computing and other facets of daily life.