Analog decoding using a gradient-type neural network

The problem of analog (soft) decision decoding of block codes by means of neural networks is addressed. The proposed solution is based on a recurrent high-order network implementing a special gradient-type system. Simulation results for two different codes are reported, showing improved performances over the classical hard decision decoder.