Neural network realization of support vector methods for patternclassification

摘要

We apply a recurrent neural network to support vector machine(SVM) training for pattern recognition. Specifically, a primal-dualneural network is exploited to solve the quadratic programming problemencountered in training SVMs. The properties of the network allow one todesign SVMs without adjustable network parameters and give a bettersolution for ill-posed problems