2001 Fiscal Year Final Research Report Summary
Signal separation from the mixture of correlated multiple signals and its application
| Project/Area Number |
12450163
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Measurement engineering
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| Research Institution | TOKYO UNIVERSITY OF AGRICULTURE AND TECHNOLOGY |
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Principal Investigator |
KOBATAKE Hidefumi Tokyo Univ. of Agri. & Tech., Graduate School of Bio-Applications and Systems Engineering, Professor, 大学院・生物システム応用科学研究科, 教授 (80013720)
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| Co-Investigator(Kenkyū-buntansha) |
HAGIHARA Yosihiro Tokyo Univ. of Agri. & Tech., Graduate School of Bio-Applications and Systems Engineering, Assistant Professor, 大学院・生物システム応用科学研究科, 助手 (80293009)
SHIMIZU Akinobu Tokyo Univ. of Agri. & Tech., Graduate School of Bio-Applications and Systems Engineering, Associate Professor, 大学院・生物システム応用科学研究科, 助教授 (80262880)
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| Project Period (FY) |
2000 – 2001
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| Keywords | BSS / Signal Separation / Independent Component / Corre l at I on |
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| Research Abstract |
The important results of this research projects can be summarized as follows.
Energy sources localization problem has not been fully addressed in nearfield scenario. We have presented an eigen-structure based near-field wideband sources localization method using arbitrarily spaced sensor array. Estimation of the source locations is based on the straightforward exploitation of the eigenstructure of array power spectral density matrices. Our method solves the 3-D (azimuth, elevation and range) localization problem. A fast algorithm but with a sacrifice in the freedom in sensor arrangement is also presented. Simulation tests prove its validity and good performance.
Blind separation of convolutive mixtures is often implemented in rfequency domain. The partial correlation between the frequency representations of original sources is sometimes too high to be neglected and consequently makes the performance of all the BSS methods efficiency down in various degrees. We proposed a recursive blind separation method for lowering the unfavorable effect from the partial correlation. The signal-to-noise ratio is greatly increased at certain bins, which results in a much better separation. Theoretically, it is possible to be used combined with any blind separation method for which the independence is assumed, and better separation can be expected.
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Research Products
(8 results)
