| Project/Area Number |
07558168
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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| Allocation Type | Single-year Grants |
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| Section | 展開研究 |
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| Research Field |
情報システム学(含情報図書館学)
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| Research Institution | Waseda University |
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Principal Investigator |
HIRASAWA Shigeichi Waseda Univ., School of Science and Engineering, Professor, 理工学部, 教授 (30147946)
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| Co-Investigator(Kenkyū-buntansha) |
INAZUMI Hiroshige Aoyama Gakuin University, College of Science and Engineering, Associate Professo, 理工学部, 助教授 (00168402)
TAJIMA Masato Toyama University, Faculty of Engineering, Associate Professor, 工学部, 助教授 (20251879)
NISHIJIMA Toshihisa Hosei University, College of Engineering, Associate Professor, 工学部, 助教授 (70211456)
KOHNOSU Toshiyuki Waseda Univ., Multimedia Network Center, 理工学総合研究センター, 嘱託(研究職) (60257194)
MATSUSHIMA Toshiyasu Waseda Univ., School of Science and Engineering, Professor, 理工学部, 教授 (30219430)
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| Project Period (FY) |
1995 – 1997
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| Project Status |
Completed (Fiscal Year 1997)
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| Budget Amount *help |
¥4,400,000 (Direct Cost: ¥4,400,000)
Fiscal Year 1997: ¥2,100,000 (Direct Cost: ¥2,100,000)
Fiscal Year 1996: ¥2,300,000 (Direct Cost: ¥2,300,000)
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| Keywords | Bays Code / Model Selection / Data compaction with distortion / Bounded distance decoding / Soft decision decoding / ARQ method / Convolutional ads / Signature method / 畳込み符号 / ビタビ復号法 / 巡回符号 / 並列符号化器・復号化器 / MDL基準 / エントロピー / 学習アルゴリズム / 連接符号 / マルチメディア / ユニバーサル情報源符号化 / シンドローム復号 / ARQ / 2元巡回符号 |
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| Research Abstract |
(1) (1)We studied data compression for text in source coding. We theoretically derived difference in code lengths between the codes based on the MDL principle and the Bays codes. Then these results were applied to the model selection problem.
(2)We developed an approximately optimal algorithm which reduces complexity in calculation for the Bays code. We applied this algorithm to benchmark test, files, and so on, which gave good results. As data compression for speech, image, and so on, we also proposed an algorithm which applied the trellis codes to the source coding problem, and performed an evaluation experiment for this algorithm.
(2) (1)In channel coding, we developed an algorithm on decoding beyond the BCH bound for BCH codes, and also an algorithm on soft decision decoding for block codes. From the viewpoint of complexity in calculation, we found a practical decoding method.
(2)For convolutional codes, the relation between the Viterbi decoding method and the syndrome decoding method was elucidated. And these results were applied to the ARQ method. We found a decoding method having excellent performance at low rate.
(3)We performed signature analysis by parallel processing as an application of the error-correcting codes to test methods of LSI.
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