Evolutionary synthesis of digital filter structures
using genetic programming
K. Uesaka, and M. Kawamata. IEEE Transactions on Circuits and Systems II: Analog
and Digital Signal Processing, 50 (12):
977--983(December 2003)
Abstract
This paper presents a synthesis method for
infinite-impulse response (IIR) digital filter
structures using genetic programming with automatically
defined functions (GP-ADF). In the proposed method,
digital filter structures are represented as
S-expressions with subroutines, which are written
directly from the set of difference equations. This
paper also shows the condition for the constructing the
S-expressions that represent the filter structures
without delay-free loops. Numerical examples synthesize
two-filter structures: the low-coefficient sensitivity
fourth-order filter structure and the low-output
roundoff noise second-order filter structure.
%0 Journal Article
%1 Uesaka:2003:CS
%A Uesaka, Kazuyoshi
%A Kawamata, Masayuki
%D 2003
%J IEEE Transactions on Circuits and Systems II: Analog
and Digital Signal Processing
%K IIR S-expressions, algorithms, automatically computability, defined difference digital effects, equations, errors, evolutionary filter filter, filters, fitness fourth-order function functions, genetic global infinite-impulse low-coefficient low-output matrices, matrix measure, method, noise, optimization, programming, representation, response roundoff sensitivity, structures, subroutines, synthesis transfer wordlength
%N 12
%P 977--983
%T Evolutionary synthesis of digital filter structures
using genetic programming
%V 50
%X This paper presents a synthesis method for
infinite-impulse response (IIR) digital filter
structures using genetic programming with automatically
defined functions (GP-ADF). In the proposed method,
digital filter structures are represented as
S-expressions with subroutines, which are written
directly from the set of difference equations. This
paper also shows the condition for the constructing the
S-expressions that represent the filter structures
without delay-free loops. Numerical examples synthesize
two-filter structures: the low-coefficient sensitivity
fourth-order filter structure and the low-output
roundoff noise second-order filter structure.
@article{Uesaka:2003:CS,
abstract = {This paper presents a synthesis method for
infinite-impulse response (IIR) digital filter
structures using genetic programming with automatically
defined functions (GP-ADF). In the proposed method,
digital filter structures are represented as
S-expressions with subroutines, which are written
directly from the set of difference equations. This
paper also shows the condition for the constructing the
S-expressions that represent the filter structures
without delay-free loops. Numerical examples synthesize
two-filter structures: the low-coefficient sensitivity
fourth-order filter structure and the low-output
roundoff noise second-order filter structure.},
added-at = {2008-06-19T17:35:00.000+0200},
author = {Uesaka, Kazuyoshi and Kawamata, Masayuki},
biburl = {https://www.bibsonomy.org/bibtex/2eef9df7aa10716f5407ab086c5a87e5e/brazovayeye},
interhash = {4d31bfb2cbbd4d29c63e08748366b3c2},
intrahash = {eef9df7aa10716f5407ab086c5a87e5e},
issn = {1057-7130},
journal = {IEEE Transactions on Circuits and Systems {II}: Analog
and Digital Signal Processing},
keywords = {IIR S-expressions, algorithms, automatically computability, defined difference digital effects, equations, errors, evolutionary filter filter, filters, fitness fourth-order function functions, genetic global infinite-impulse low-coefficient low-output matrices, matrix measure, method, noise, optimization, programming, representation, response roundoff sensitivity, structures, subroutines, synthesis transfer wordlength},
month = {December},
notes = {Inspec Accession Number: 7830391},
number = 12,
pages = {977--983},
timestamp = {2008-06-19T17:53:25.000+0200},
title = {Evolutionary synthesis of digital filter structures
using genetic programming},
volume = 50,
year = 2003
}