Neural network learning for analog VLSI implementations of support vector machines: a survey

Analog Neural Network for Support Vector Machine Learning

An analog neural network for support vector machine learning is proposed, based on a partially dual formulation of the quadratic programming problem. It results in a simpler circuit implementation with respect to existing neural solutions for the same application. The effectiveness of the proposed network is shown through some computer simulations concerning benchmark problems.