Title :
Notice of Violation of IEEE Publication Principles
Design of Digital Fir Filters Using Differential Evolution Algorithm Based on Reserved Gene
Author :
Zhao, Qingshan ; Meng, Guoyan
Author_Institution :
Dept. of Comput., Xinzhou Teachers Univ., Xinzhou, China
Abstract :
Notice of Violation of IEEE Publication Principles
"Design of Digital FIR Filters Using Differential Evolution Algorithm Based on Reserved Gene"
by Qingshan Zhao and Guoyan Meng
in the Proceedings of the 2010 International Conference of Information Science and Management Engineering, August 2010, pp. 177-180
After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE\´s Publication Principles.
This paper contains significant portions of original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.
Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:
"Design of Digital FIR Filters Using Differential Evolution Algorithm Based on Reserved Gene"
by Gang Liu, YuanXiang Li, and GuoLiang He
in the Proceedings of the IEEE Congress on Evolutionary Computation, July 2010, pp. 1-7
Filtering has been an enabling technology and has found ever-increasing applications. There are two main classes of digital filters: finite impulse response (FIR) filters and infinite impulse response (IIR) filters. FIR filter can be guaranteed to have linear phase and are always stable filters, so FIR filters is widely applicable. The differential evolution (DE) algorithm, which has been proposed particularly for numeric optimization problems, is a population-based algorithm like the genetic algorithms. In this work, the DE algorithm based on reserved gene has been applied to the design of digital finite impulse response filters. It can produce new chromosomes in ever generation by combined with reserved gene of special chromosome into a single entity. And its performance has been compared to other method. Examples are illustrated to demonstrate the effectiveness of the proposed design method.
Keywords :
FIR filters; IIR filters; genetic algorithms; numerical analysis; optimisation; differential evolution algorithm; digital FIR filter; finite impulse response filters; genetic algorithms; infinite impulse response filters; numeric optimization problems; population based algorithm; reserved gene; Algorithm design and analysis; Arrays; Filtering algorithms; Finite impulse response filter; IIR filters; Signal processing algorithms; FIR filter design; differential evolution algorithm; genetic algorithm;
Conference_Titel :
Information Science and Management Engineering (ISME), 2010 International Conference of
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-7669-5
Electronic_ISBN :
978-1-4244-7670-1
DOI :
10.1109/ISME.2010.237