| Project/Area Number |
17540158
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Basic analysis
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| Research Institution | Osaka Kyoiku University |
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Principal Investigator |
ASHINO Ryuichi Osaka Kyoiku Univ., Faculty of education, Professor, 教育学部, 教授 (80249490)
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| Co-Investigator(Kenkyū-buntansha) |
MANDAI Takeshi Osaka Electro-Communication Univ., Faculty of engineering, Professor, 工学部, 教授 (10181843)
NAKAI Eiichi Osaka Kyoiku Univ., Faculty of education, Professor, 教育学部, 教授 (60259900)
MORIMOTO Akira Osaka Kyoiku Univ., Faculty of education, Assistant, 教育学部, 助手 (50239688)
TAKEUCHI Jiro Tokyo Univ. of Science, Faculty of industrial science and technology, Professor, 基礎工学部, 教授 (80082402)
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| Project Period (FY) |
2005 – 2006
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| Project Status |
Completed (Fiscal Year 2006)
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| Budget Amount *help |
¥3,200,000 (Direct Cost: ¥3,200,000)
Fiscal Year 2006: ¥1,400,000 (Direct Cost: ¥1,400,000)
Fiscal Year 2005: ¥1,800,000 (Direct Cost: ¥1,800,000)
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| Keywords | wavelet / multiwavelet / image processing / system identification / blind source separation / time-frequency analysis / generalized Sobolev space / ブラインド信号源分離 / 特異値分解 |
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| Research Abstract |
1. Wavelet and block singular value image processing: A new hybrid method consisting of a discrete wavelet transform and a spline block SVD denoising procedure is proposed and used to remove Gaussian noise from images. Filtering is based on eliminating changes in singular values and singular vectors caused by additive Gaussian white noise or other types of noise.
2. Applications of wavelet analysis to system identification: Formulae using wavelet transform to access time-frequency information of kernel distributions are deduced. A new wavelet based system identification method for time-invariant linear systems and its discretized formula using stationary wavelet transform are proposed.
3. Blind source separation using time-frequency analysis: The blind source separation problem corresponds to a way to enable computers to solve the cocktail party problem in a satisfactory manner. A blind source separation based on time-frequency informations for spatio-temporal mixture problems is discussed.
4. Multiwavelets in generalized Sobolev spaces: A class of r-regular multiwavelets is introduced with appropriate notation and definitions in generalized Sobolev spaces. The oscillation properity of the orthonormal system is obtained. A multiresolution analysis for multiwavelets is defined in generalized Sobolev spaces.
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