Synthesis of low-sensitivity second-order digital filters using Genetic Programming with Automatically Defined Functions

Kazuyoshi Uesaka; Masayuki Kawamata

doi:10.1109/ISCAS.2000.857104

Synthesis of low-sensitivity second-order digital filters using Genetic Programming with Automatically Defined Functions

Kazuyoshi Uesaka, Masayuki Kawamata

Research output: Contribution to journal › Conference article › peer-review

Abstract

This paper proposes a synthesis method for low coefficient sensitivity second-order IIR digital filter structures using Genetic Programming with Automatically Defined Functions (GP-ADF). In this paper, digital filter structures are represented as S-expressions with subroutines. It is easy to generate syntactically valid S-expressions and perform the genetic operations because the representation is suitable for GP. In a numerical example, we use the fitness measure including the magnitude sensitivity, and demonstrate that the proposed method can synthesize efficiently very low coefficient sensitivity filter structures.

Original language	English
Pages (from-to)	I-359-I-362
Journal	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	1
DOIs	https://doi.org/10.1109/ISCAS.2000.857104
Publication status	Published - 2000
Externally published	Yes
Event	Proceedings of the IEEE 2000 International Symposium on Circuits and Systems, ISCAS 2000 - Geneva, Switz, Switzerland Duration: 2000 May 28 → 2000 May 31

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1109/ISCAS.2000.857104

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title = "Synthesis of low-sensitivity second-order digital filters using Genetic Programming with Automatically Defined Functions",

abstract = "This paper proposes a synthesis method for low coefficient sensitivity second-order IIR digital filter structures using Genetic Programming with Automatically Defined Functions (GP-ADF). In this paper, digital filter structures are represented as S-expressions with subroutines. It is easy to generate syntactically valid S-expressions and perform the genetic operations because the representation is suitable for GP. In a numerical example, we use the fitness measure including the magnitude sensitivity, and demonstrate that the proposed method can synthesize efficiently very low coefficient sensitivity filter structures.",

author = "Kazuyoshi Uesaka and Masayuki Kawamata",

year = "2000",

doi = "10.1109/ISCAS.2000.857104",

language = "English",

volume = "1",

pages = "I--359--I--362",

journal = "Proceedings - IEEE International Symposium on Circuits and Systems",

issn = "0271-4310",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "Proceedings of the IEEE 2000 International Symposium on Circuits and Systems, ISCAS 2000 ; Conference date: 28-05-2000 Through 31-05-2000",

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TY - JOUR

T1 - Synthesis of low-sensitivity second-order digital filters using Genetic Programming with Automatically Defined Functions

AU - Uesaka, Kazuyoshi

AU - Kawamata, Masayuki

PY - 2000

Y1 - 2000

N2 - This paper proposes a synthesis method for low coefficient sensitivity second-order IIR digital filter structures using Genetic Programming with Automatically Defined Functions (GP-ADF). In this paper, digital filter structures are represented as S-expressions with subroutines. It is easy to generate syntactically valid S-expressions and perform the genetic operations because the representation is suitable for GP. In a numerical example, we use the fitness measure including the magnitude sensitivity, and demonstrate that the proposed method can synthesize efficiently very low coefficient sensitivity filter structures.

AB - This paper proposes a synthesis method for low coefficient sensitivity second-order IIR digital filter structures using Genetic Programming with Automatically Defined Functions (GP-ADF). In this paper, digital filter structures are represented as S-expressions with subroutines. It is easy to generate syntactically valid S-expressions and perform the genetic operations because the representation is suitable for GP. In a numerical example, we use the fitness measure including the magnitude sensitivity, and demonstrate that the proposed method can synthesize efficiently very low coefficient sensitivity filter structures.

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DO - 10.1109/ISCAS.2000.857104

M3 - Conference article

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VL - 1

SP - I-359-I-362

JO - Proceedings - IEEE International Symposium on Circuits and Systems

JF - Proceedings - IEEE International Symposium on Circuits and Systems

SN - 0271-4310

T2 - Proceedings of the IEEE 2000 International Symposium on Circuits and Systems, ISCAS 2000

Y2 - 28 May 2000 through 31 May 2000

ER -

Synthesis of low-sensitivity second-order digital filters using Genetic Programming with Automatically Defined Functions

Abstract

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