An improved Teaching-Learning-Based Optimization Algorithm applied to the design of linear phase digital FIR filter

Optimization algorithms based on evolutionary techniques have been applied for the optimal design of the linear phase digital FIR filter for better control of the parameters of it. The coefficients of the actual filter are optimized by these algorithms to approximate the frequency response of the desired filter. In this paper, an improved Teaching-Learning-Based Optimization (ITLBO) algorithm is applied for the design of linear phase digital FIR filter and its results are compared with those obtained by using Teaching-Learning-Based Optimization (TLBO) algorithm. The simulation results and comparison show that fast convergence is obtained in the both the cases of TLBO and ITLBO algorithms; however, the approximation error is smaller in the case of ITLBO algorithm. When frequency responses obtained using these algorithms are compared with those obtained using least-squares (LS) method of FIR filter design, better performance is shown by ITLBO algorithm.