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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | An-Xin Zhao Xiao-Jun Tang Zhong-Hua Zhang Jun-Hua Liu |
| Copyright Year | 2014 |
| Description | Author affiliation: State Key Lab. of Electr. Insulation & Power Equip., Xi'an Jiaotong Univ., Xian, China (Xiao-Jun Tang; Zhong-Hua Zhang; Jun-Hua Liu) || State Key Lab. of Electr. Insulation & Power Equip., Xi'an Univ. of Sci. & Technol., Xian, China (An-Xin Zhao) |
| Abstract | The design target of Finite Impulse Response (FIR) filter is to approximate the ideal filters on the request of a given designing filter specifications. Genetic algorithm is one of global optimal search algorithm of mimic biological evolution, but it has the precocious and slow convergence problems if it is directly applicated. Based on these problems, the adaptive selection algorithm was used to improve the choice of the crossover operator and its mutation operator for genetic algorithm. And then, the improved genetic algorithm was used to design and optimize the Finite Impulse Response (FIR) filter. Based on design features of FIR filter frequency sampling method, we used the improved genetic algorithm, Look-up table and references methods for compare their results. The results of the proposed method by MATLAB simulation showd that the proposed method can obtain better results in the same design specifications. |
| Starting Page | 452 |
| Ending Page | 455 |
| File Size | 174245 |
| Page Count | 4 |
| File Format | |
| e-ISBN | 9781479943159 |
| DOI | 10.1109/ICIEA.2014.6931206 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-06-09 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Finite impulse response filters Genetic algorithms Sociology Statistics Educational institutions Table lookup Look-up table Genetic Algorithm Finite Impulse Response filter Frequency sampling method |
| Content Type | Text |
| Resource Type | Article |
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