Function Approximations using FF Networks
The inherent capability of neural networks to perform massive parallel processing of information enhance the approximation of fuzzy systems by neural networks. Chen, Cybenko, Funahashi, Babri and others studied function approximation capabilities by feedforward neural networks. Ramakrishnan and others used sigmoidal signals to study the approximations of continuous functions. In this effort, the right sigmoidal signal is used to establish function approximation theorems.
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