Low power FIR filter design using modified multi-objective artificial bee colony algorithm

被引:30
作者
Dwivedi, Atul Kumar [1 ]
Ghosh, Subhojit [1 ]
Londhe, Narendra D. [1 ]
机构
[1] NIT Raipur, Dept Elect Engn, Raipur, Madhya Pradesh, India
关键词
Digital FIR filters; FPGA; Evolutionary algorithms; Multi-objective artificial bee colony algorithm; Low power design; PARTICLE SWARM OPTIMIZATION; GENETIC ALGORITHM; HIGH-SPEED; REALIZATION; FLOW;
D O I
10.1016/j.engappai.2016.06.006
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Inspite of the significance of the requirement of low power consumption, most of the existing techniques on FIR filter design have only concentrated on minimizing the ripples in pass band and stop band. In this regard the present work proposes an optimization based approach for filter design, which not only minimizes the pass band and stop band ripples but also aims at reducing the power consumption during filter execution. The tradeoff between pass band ripple, stop band ripple and power consumption avoids the use of the classical single objective based optimization approaches. Hence the filter design task has been framed as a multi-objective optimization problem and solved using a modified version of multi objective artificial bee colony algorithm. The final solution obtained post convergence of the algorithm provides a set of optimal filters (Pareto front) which maintains a tradeoff between the multiple specifications. It allows the designer to choose a particular filter (coefficients) based on the requirement and/or application. The applicability of the proposed approach has been evaluated by comparing the ripples and power consumption with other state of the art evolutionary algorithms. In addition to the numerical. results, the filters derived have been validated experimentally by implementing them in Vitex-7 FPGA. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:58 / 69
页数:12
相关论文
共 56 条
[1]   Linear phase FIR filter design using particle swarm optimization and genetic algorithms [J].
Ababneh, Jehad I. ;
Bataineh, Mohammad H. .
DIGITAL SIGNAL PROCESSING, 2008, 18 (04) :657-668
[2]  
Ahmad S. U., 2006, 2006 IEEE International Symposium on Circuits and Systems (IEEE Cat. No. 06CH37717C)
[3]  
Ahmad Sabbir U., 2007, 2007 IEEE International Symposium on Signal Processing and Information Technology, P525, DOI 10.1109/ISSPIT.2007.4458200
[4]   Synchronous and asynchronous Pareto-based multi-objective Artificial Bee Colony algorithms [J].
Akay, Bahriye .
JOURNAL OF GLOBAL OPTIMIZATION, 2013, 57 (02) :415-445
[5]   Design of digital filters for low power applications by reducing the hamming distance of the filter coefficients using mean field annealing algorithm [J].
Aktan, M ;
Çini, U ;
Dündar, G .
PROCEEDINGS OF THE IEEE 12TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE, 2004, :646-648
[6]   An Algorithm for the Design of Low-Power Hardware-Efficient FIR Filters [J].
Aktan, Mustafa ;
Yurdakul, Arda ;
Duendar, Guenhan .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS, 2008, 55 (06) :1536-1545
[7]   Low power design for DSP: Methodologies and techniques [J].
Arslan, T ;
Erdogan, AT ;
Horrocks, DH .
MICROELECTRONICS JOURNAL, 1996, 27 (08) :731-744
[8]   Low-Power Finite Impulse Response (FIR) Filter Design Using Two-Dimensional Logarithmic Number System (2DLNS) Representations [J].
Azarmehr, Mahzad ;
Ahmadi, Majid .
CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2012, 31 (06) :2075-2091
[9]   An efficient hybrid genetic algorithm to design finite impulse response filters [J].
Boudjelaba, Kamal ;
Ros, Frederic ;
Chikouche, Djamel .
EXPERT SYSTEMS WITH APPLICATIONS, 2014, 41 (13) :5917-5937
[10]  
Ching-Long Su, 1994, Digest of Papers. Spring COMPCON 94 (Cat. No.94CH3414-0), P489, DOI 10.1109/CMPCON.1994.282878