An Incremental Evolutionary Strategy for the Design of FIR Filters Targeting Real-Time Applications

This paper introduces a new methodology for the design of finite impulse response filters within an evolvable hardware platform targeting real-time adaptation. The methodology incorporates a technique, which directs the search by focusing it into regions responsible for the evolution of individual coefficients. The methodology has been evaluated with three different paradigms that include two low-pass filters (29-order and 34-order, respectively) and a 41-order pass-band finite impulse response filter. The proposed method is compared with a conventional evolutionary strategy that has been commonly used for the implementation of digital filters resulting in significant improvements in terms of quality, convergence speed and computational efficiency.