Learning characteristics of adaptive fault tolerant filters in the presence of transient errors

Adaptive digital filters can be designed with hardware redundancy so they can continue operating effectively after the occurrence of certain types of hardware failures, thereby achieving reliability through a mechanism known as adaptive fault tolerance. It is known that the extra degrees of freedom provided by properly added hardware redundancy gives many equivalent optimal solutions within the coefficient parameter space. This paper investigates the convergence properties of an adaptive fault tolerant FIR filter when temporary noise-induced errors occur.