NDLI: Synthesis Tool Based on Genetic Algorithm for FIR Filters with User-Defined Magnitude Characteristics

Content Provider	Springer Nature Link
Author	Szopos, Ervin Neag, Marius Saracut, Ioana Popescu, Victor Topa, Marina
Copyright Year	2015
Abstract	This paper presents a method for synthesizing linear-phase FIR filters capable of implementing magnitude characteristics defined arbitrarily by the user through a set of frequency–magnitude points, filters that are optimized with respect to several criteria. The main idea is to approach the filter synthesis as a multi-objective optimization problem, targeting the minimization of both the peak magnitude and the total squared errors of the resulting magnitude characteristics, as well as implementation-related requirements such as the reduction of the filter length. The optimization procedure uses a genetic algorithm tailored to this application; it employs a novel encoding scheme for the filter chromosome and an efficient fitness function, based on only two well-chosen constraints. Several design examples are presented: first, optimized synthesis of FIR filters with magnitude characteristics that match given (arbitrary) human audiograms, and second, synthesis of filters defined by parameters related to their pass- and stop-bands. The results yielded by the proposed method compare well with filters synthesized by means of previously reported methods and an industry-standard MATLAB tool.
Starting Page	253
Ending Page	279
Page Count	27
File Format	PDF
ISSN	0278081X
Journal	Circuits, Systems, and Signal Processing
Volume Number	35
Issue Number	1
e-ISSN	15315878
Language	English
Publisher	Springer US
Publisher Date	2015-04-25
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	FIR synthesis Arbitrary magnitude characteristic Genetic algorithm Multi-objective optimization Audiogram emulation Circuits and Systems Electrical Engineering Signal, Image and Speech Processing Electronics and Microelectronics, Instrumentation
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Signal Processing

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