Digital circuit structure design via evolutionary algorithm method

Kok Hen Chong, I. B. Aris, M. A. Sinan, B. M. Hamiruce

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In this study, a new method for automatic optimization of digital circuit design method has been introduced. This method is base on randomized search techniques mimicking natural genetic evolution. The proposed method is an iterative procedure that consists of a constant-size population of individuals, each one encoding a possible solution in a given problem space. The structure of the circuit is encoded into one-dimensional genotype as represented by a finite string of bits. A number of bit string used to represent 8 types of possible logic gates, Wire 1, Wire 2, NOT 1, NOT 2, XOR, XNOR, NAND, NOR, AND and OR. The structure of gates are arranged in a m * n matrix form which m is the number of input variables, The experimental results have shown that this method can produce the circuit design base on user specified performance requirement. The representation approach also has been implemented with a computer program which can give better achievement in terms of quality solution and speed of convergence.

Original languageEnglish
Pages (from-to)380-385
Number of pages6
JournalJournal of Applied Sciences
Volume7
Issue number3
DOIs
Publication statusPublished - 01 Feb 2007

Fingerprint

Digital circuits
Evolutionary algorithms
Wire
Logic gates
Networks (circuits)
Computer program listings

All Science Journal Classification (ASJC) codes

  • General

Cite this

Chong, Kok Hen ; Aris, I. B. ; Sinan, M. A. ; Hamiruce, B. M. / Digital circuit structure design via evolutionary algorithm method. In: Journal of Applied Sciences. 2007 ; Vol. 7, No. 3. pp. 380-385.
@article{d8a9c65425f44f368b58c3d72ef193a7,
title = "Digital circuit structure design via evolutionary algorithm method",
abstract = "In this study, a new method for automatic optimization of digital circuit design method has been introduced. This method is base on randomized search techniques mimicking natural genetic evolution. The proposed method is an iterative procedure that consists of a constant-size population of individuals, each one encoding a possible solution in a given problem space. The structure of the circuit is encoded into one-dimensional genotype as represented by a finite string of bits. A number of bit string used to represent 8 types of possible logic gates, Wire 1, Wire 2, NOT 1, NOT 2, XOR, XNOR, NAND, NOR, AND and OR. The structure of gates are arranged in a m * n matrix form which m is the number of input variables, The experimental results have shown that this method can produce the circuit design base on user specified performance requirement. The representation approach also has been implemented with a computer program which can give better achievement in terms of quality solution and speed of convergence.",
author = "Chong, {Kok Hen} and Aris, {I. B.} and Sinan, {M. A.} and Hamiruce, {B. M.}",
year = "2007",
month = "2",
day = "1",
doi = "10.3923/jas.2007.380.385",
language = "English",
volume = "7",
pages = "380--385",
journal = "Journal of Applied Sciences",
issn = "1812-5654",
publisher = "Asian Network for Scientific Information",
number = "3",

}

Digital circuit structure design via evolutionary algorithm method. / Chong, Kok Hen; Aris, I. B.; Sinan, M. A.; Hamiruce, B. M.

In: Journal of Applied Sciences, Vol. 7, No. 3, 01.02.2007, p. 380-385.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Digital circuit structure design via evolutionary algorithm method

AU - Chong, Kok Hen

AU - Aris, I. B.

AU - Sinan, M. A.

AU - Hamiruce, B. M.

PY - 2007/2/1

Y1 - 2007/2/1

N2 - In this study, a new method for automatic optimization of digital circuit design method has been introduced. This method is base on randomized search techniques mimicking natural genetic evolution. The proposed method is an iterative procedure that consists of a constant-size population of individuals, each one encoding a possible solution in a given problem space. The structure of the circuit is encoded into one-dimensional genotype as represented by a finite string of bits. A number of bit string used to represent 8 types of possible logic gates, Wire 1, Wire 2, NOT 1, NOT 2, XOR, XNOR, NAND, NOR, AND and OR. The structure of gates are arranged in a m * n matrix form which m is the number of input variables, The experimental results have shown that this method can produce the circuit design base on user specified performance requirement. The representation approach also has been implemented with a computer program which can give better achievement in terms of quality solution and speed of convergence.

AB - In this study, a new method for automatic optimization of digital circuit design method has been introduced. This method is base on randomized search techniques mimicking natural genetic evolution. The proposed method is an iterative procedure that consists of a constant-size population of individuals, each one encoding a possible solution in a given problem space. The structure of the circuit is encoded into one-dimensional genotype as represented by a finite string of bits. A number of bit string used to represent 8 types of possible logic gates, Wire 1, Wire 2, NOT 1, NOT 2, XOR, XNOR, NAND, NOR, AND and OR. The structure of gates are arranged in a m * n matrix form which m is the number of input variables, The experimental results have shown that this method can produce the circuit design base on user specified performance requirement. The representation approach also has been implemented with a computer program which can give better achievement in terms of quality solution and speed of convergence.

UR - http://www.scopus.com/inward/record.url?scp=33847083894&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33847083894&partnerID=8YFLogxK

U2 - 10.3923/jas.2007.380.385

DO - 10.3923/jas.2007.380.385

M3 - Article

VL - 7

SP - 380

EP - 385

JO - Journal of Applied Sciences

JF - Journal of Applied Sciences

SN - 1812-5654

IS - 3

ER -