Step Size Optimization of LMS Algorithm Using Aunt Colony Optimization & Its comparison with Particle Swarm optimization Algorithm in System Identification

that have been sampled from analogue sources, digital signal processing (DSP) algorithms are employed. The advantages of DSP are based on the fact that the performance of the applied algorithm is always predictable. Further, the digital techniques are error prone due to quantization, free of device errors which are usually caused by the device noises, mismatches due statistical nature of the fabrication processes, and the defects that may arise during fabrication. DSP algorithms are usually described as a digital filter. Digital filters can be broadly divided into two-sub classes: finite impulse-response filters and infinite impulse-response (IIR) filters. Because the error surface of IIR filters is generally multi-modal, global optimization techniques are required in order to avoid local minima and design efficient digital IIR filters. In this work, a new method based on the Ant Colony Optimization algorithm is proposed. This algorithm is found efficient with global optimization ability, therefore it is proposed for the design of digital filters.