Low Power Adaptive Filters Based on a Combination of Genetic Optimization and Residue Number System Coding

This paper investigates design strategies for achieving reliable performance in low power VLSI adaptive filters that are prone to transient errors due to increasingly smaller feature dimensions and supply voltages of the CMOS circuits. First it is shown that a well known stochastic search algorithm, the genetic algorithm, has an inherent resistance to transient (soft) errors that may occur due to feature scaling. It is then shown how modular hardware can be designed with residue number system (RNS) coding to provide improved resistance to transient (soft) errors in low power realizations of adaptive filters that optimize the filter parameters via the genetic algorithm.