Design of Low Pass FIR Filter using Artificial Bee Colony Optimization Technique and its Comparison with Particle Swarm Optimization

Digital Signal Processing (DSP) is one of the most powerful technologies that are shaping science and engineering in the twenty-first century. Revolutionary changes have already been made in a broad range of fields: communications, medical imaging, radar and sonar, and high fidelity music reproduction, to name just a few. Each of these areas has developed a comprehensive DSP technology, with its own algorithms, mathematics, and specialized techniques. Analog (electronic) filters can be used for these tasks, as these are cheap, fast, and have a large dynamic range in both amplitude and frequency; however, digital filters are vastly superior in the level of performance. Digital filters are an essential part of DSP. The purpose of the filters is to allow some frequencies to pass unaltered, while completely blocking others. The digital filters are mainly used for two purposes: separation of signals that have been combined, and restoration of signals that have been distorted in some way. In this present work, Digital FIR filter is designed using Artificial Bee Colony (ABC) optimization technique and its comparison is done with particle swarm optimization.

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