Design of FIR Filter to Improve Signal Using Genetic Algorithm

2017 ◽  
Vol V (VIII) ◽  
pp. 1208-1213
Author(s):  
Anshul .
Keyword(s):  
Genetic Algorithm ◽  
Fir Filter

Design of FIR filter ISOTA with the aid of genetic algorithm

Integration ◽  
2021 ◽  
Author(s):  
Abhijit Chandra ◽  
Amit Kumar ◽  
Subhabrata Roy
Keyword(s):  
Genetic Algorithm ◽  
Fir Filter

Design of FIR Filter Based on Genetic Algorithm

2021 ◽  
pp. 81-87
Author(s):  
Yipeng Wang ◽  
Yan Ding ◽  
Anding Wang ◽  
Jingyu Hua ◽  
Weidang Lu
Keyword(s):  
Genetic Algorithm ◽  
Fir Filter

Optimization of high speed pipelining in FPGA-based FIR filter design using genetic algorithm

2012 ◽  
Author(s):  
Uwe Meyer-Baese ◽  
Guillermo Botella ◽  
David E. T. Romero ◽  
Martin Kumm
Keyword(s):  
Genetic Algorithm ◽  
High Speed ◽  
Filter Design ◽  
Fir Filter ◽  
Fir Filter Design

scholarly journals Design of Finite Impulse Response Filters Based on Genetic Algorithm

2013 ◽  
Vol 6 (3) ◽  
pp. 28-39
Author(s):  
Raaed Faleh Hassan ◽  
Ali Subhi Abbood
Keyword(s):  
Genetic Algorithm ◽  
Impulse Response ◽  
Optimization Problems ◽  
Filter Design ◽  
Finite Impulse Response ◽  
Optimal Solution ◽  
Fir Filter ◽  
Language Version ◽  
Finite Impulse Response Filters ◽  
Matlab Programming

Genetic Algorithms (GAs) are used to solve many optimization problems in science and engineering such as pattern recognition, robotics, biology, medicine, and many other applications. The aim of this paper is to describe a method of designing Finite Impulse Response (FIR) filter using Genetic Algorithm (GA). In this paper, the Genetic Algorithm not only used for searching the optimal coefficients, but also it is used to find the minimum number of Taps, and hence minimize the number of multipliers and adders that can be used in the design of the FIR filter. The Evolutionary Programming is the best search procedure and most powerful than Linear Programming in providing the optimal solution that is desired to minimize the ripple content in both passband and stopband. The algorithm generates a population of genomes that represents the filter coefficient and the number of taps, where new genomes are generated by crossover and mutation operations methods. Our proposed genetic technique has able to give better result compare to other method.The FIR filter design using Genetic Algorithm is simulated using MATLAB programming language version 7.6.0.324 (R2008a).

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