Complexity reduction in Volterra connectionist modelling by consideration of output mapping

The output mapping method is used to demonstrate an approach which makes the Volterra connectionist model highly efficient computationally, in comparison with current neural networks. Although the system was applied to yield linear recognizers, exactly the same approach can be used to reduce the order of a nonlinear recognizer. The network is not constrained to fit arbitrary indices and may utilize all of its degrees of freedom to improve recognition performance.<
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