| Project/Area Number |
05650404
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| Research Category |
Grant-in-Aid for General Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Research Field |
計測・制御工学
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| Research Institution | HIROSHIMA UNIVERSITY |
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Principal Investigator |
HINAMOTO Takao Hiroshima Univ., Fac.of Eng., professor, 工学部, 教授 (50031141)
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| Co-Investigator(Kenkyū-buntansha) |
MUNEYASU Mitsuji Hiroshima Univ., Fac.of Eng., Assoc.Prof., 工学部, 助教授 (30229942)
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| Project Period (FY) |
1993 – 1994
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| Project Status |
Completed (Fiscal Year 1994)
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| Budget Amount *help |
¥1,900,000 (Direct Cost: ¥1,900,000)
Fiscal Year 1994: ¥600,000 (Direct Cost: ¥600,000)
Fiscal Year 1993: ¥1,300,000 (Direct Cost: ¥1,300,000)
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| Keywords | multi-dimensional signal processing / adaptive signal processing / adaptive filter / state-space description / LMS algorithm / image processing / system identification / 並列処理 / Roesserモデル / Fornasini-Marchesiniモデル / 空間領域 / 周波数領域 |
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| Research Abstract |
A study on the two-dimensional (2-D) adaptive state-space filters and their applications has been carried out and we have obtained the following results :
1.An algorithm for designing 2-D (3-D) adaptive state-space filters has been developed by using the Roesser local state-space (LSS) model and the least mean square (LMS) algorithm.
2.To reduce its computational burden, an adaptive algorithm has been introduced in a 2-D (3-D) separable-denominator form.
3.An adaptive algorithm based on the parallel-form realization of 2-D (3-D) state-space filters has been investigated.
4.An adaptive algorithm has been considered in the fequency domain by using the Roesser LSS model.
5.The Fornasini-Marchesini second LSS model and the LMS algorithm have been used to design 2-D adaptive state-space filters.
6.The 2-D adaptive state-space filters mentioned above have been applied to both noise reduction of an image and 2-D system identification.
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