Block Linkage Learning Genetic Algorithm: An Efficient Evolutionary Computational Technique for the Design of Ternary Weighted FIR Filters

The representation of genes in a chromosome by locus, value, and block has provided a richer source of relations through representation for a fast converging genetic algorithm. The algorithm circumvents the limitations of linkage learning on the natural selection by injecting the genetic material at high recombination centers, obtained by introducing the fuzziness at the center of acceptance of the genetic material. The evolutionary advantage of propagating the building blocks in the block linkage learning genetic algorithm is used to design a finite impulse response filter with ternary {1, 0, -1} weights.