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This document provides a survey of recurrent neural networks that can be used to solve the constrained quadratic programming problem related to support vector machine learning and model selection. It reviews several proposals in the literature for implementing such networks on analog very-large-scale integration systems. The networks are mapped to dynamical systems described by ordinary differential equations whose stable points correspond to the solutions of the optimization process. This allows the proble

Author

Purohit Manish R

Language

EN