Low Pass Filter Design Using Bacterial Foragaing and Particle Swarm Optimization

Social foraging behavior of Escherichia Coli bacteria has been analyzed to develop an algorithm to solve optimization problem in Electronics and Control Industry. The chemotactic movement of a virtual bacterium models a solution of optimization problems. Designing of FIR filter is multimodal optimization problem. This paper presents a design of linear phase digital low pass filter using bacterial foraging with particle swarm optimization. Optimization is the process used for minimized or optimized the conflicts present in design of any filter. For realization of any filter design algorithm it’s generate a set of coefficients. These coefficients are used to provide ideal frequency response characteristics. In this paper realization of FIR digital filter for different algorithm is performed. The comparison shows that BFO-PSO algorithm provides high accuracy, better convergence speed, robustness, scalability and best solution quality as compare to conventional BFO algorithms.