摘要：The conventional Parks-McClellan (PMc) filter optimization technique suffers saviour broadening of Transition width and the cutoff frequency error between ideal and designed Finite Impulse Response (FIR) filter. In the proposed work an optimization technique based on Genetic Algorithm (GA) is developed to design FIR filter. GA is an Evolutionary optimization technique. The proposed algorithm overcomes the above drawback of Parks-McClellan method at the cost of small amount of passband ripples. Reduced transition width signifies the sharp transition between passband & stopband frequencies.
其他摘要：The conventional Parks-McClellan (PMc) filter optimization technique suffers saviour broadening of Transition width and the cutoff frequency error between ideal and designed Finite Impulse Response (FIR) filter. In the proposed work an optimization technique based on Genetic Algorithm (GA) is developed to design FIR filter. GA is an Evolutionary optimization technique. The proposed algorithm overcomes the above drawback of Parks-McClellan method at the cost of small amount of passband ripples. Reduced transition width signifies the sharp transition between passband & stopband frequencies.
