인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
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지원사업
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커뮤니티
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논문 기본 정보
- 저자정보
피인용 0
초록·키워드
This paper presents a design method for 2-D state-space digital filters (2D-SSDFs) with powers-of-two coefficients using a genetic algorithm (GA). The designed 2D-SSDFs are attractive for the high-speed operation and simplification of hardware, since the signal can be processed by using only shifting operations and additions instead of multiplications. Moreover, various additional routines can be embedded in the GA procedure to synthesize the minimum roundoff noise structure and to ensure the stability of resulting 2D-SSDFs. The proposed method can obtain 2D-SSDFs with smaller approximation error than those of the other methods which use transfer functions in a continuous coefficient space. The effectiveness of the proposed method is demonstrated with a design example. In this paper our interest also lies in 2D-SSDFs that are designed with powers-of-two as a set of filter coefficients without significantly increasing the noise power gain. High-speed digital filtering can be obtained by 2D-SSDFs with powers-of-two coefficients because the multiplication of these coefficients is possible with appropriate shifting operations. By traditional optimization methods, however, it is very difficult to design 2D-SSDFs with small approximation error in a nonuniform discrete space such as powers-of-two coefficients. We thus consider an application of genetic algorithm (GA) to the design problem of 2D-SSDFs. GAs are search algorithms based on biological evolutionary theories to solve optimization problems [4]. In general, it is well known that GAs are particularly suitable for solving complex optimization problem in the discrete space. The other reason we adopt GA is that some useful techniques, such as the stability test and the minimization of roundoff noise, can be simultaneously embedded to the procedure of GA.
본문·목차
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최근 본 자료 전체보기
UCI(KEPA) : I410-ECN-0101-2009-569-013195098
