Fir Filter Design Using Optimization Implementation Using VHDL
In recent years a very intensive research work is concerned with design of digital filters. The filter shave two uses: signal separation and signal restoration. Signal separation is needed when a signal has been contaminated with interference, noise, or other signals. Signal restoration is required when a signal has been distorted in some way. Every linear filter has an impulse response, a step response and a frequency response .Each of these responses contains complete information about the filter, but in a different form. The filter design process can be described as an optimization problem where each requirement contributes with a term to an error function which should be minimized. Classical optimization methods cannot optimize such objective functions and cannot converge to the global minimum solution. To reduce all these drawbacks encountered with the classical optimization methods, several researchers have utilized many heuristic and meta-heuristic evolutionary optimization algorithms, the majority of which are based on the natural selection and evolution technique. A new algorithm binary discrete optimization method based on cat swarm optimization (CSO). BCSO is a binary version of CSO generated by observing the behaviors of cats. As in CSO, BCSO consists of two modes of operation: tracing mode and seeking mode. The obtained results are compared with a number of different optimization problems including genetic algorithm and different versions of binary discrete particle swarm optimization is the best. It is shown that the proposed method greatly improves the results obtained by other binary discrete optimization problems. Keywords— Digital filter, PSO, GA, CSO, BCSO