| Presentation | 2002/3/13 Predictive Self-Organizing Map for Vector Quantization of Migratory Signals and Its Application to Mobile Communications Akira Hirose, Tomoyuki Nagashima, |
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| PDF Download Page | PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | This paper proposes a predictive self-organizing map (P-SOM) that performs an adaptive vector quantization of migratory time-sequential signals whose stochastic properties such as average values of signals in each cluster are varying continuously. The P-SaM possesses not only the weights corresponding to the signal values themselves but also those related to the time-derivative information. All the weights self-organize to predict appropriate future reference vectors. The prediction using the time-derivative weights brings the separation of continuously varying components from random noise components, resulting in a better performance of the adaptive vector quantization. An application to a mobile communication receiver using quasi-coherent detection is presented. Simulation experiments on the bit-error rates demonstrate that a P-SOM adaptive demodulator has a superior capability to track phase rotations caused by the Doppler effect. A theoretical noise analysis is also reported for the conventional SOM and the P-SOM. It is found that the calculation results are approximately in good agreement with the experimental ones. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Neural network / Self-organizing map / adaptive vector quantization / time-series prediction / noise / mobile communication / Doppler effect |
| Paper # | NC2001-213 |
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| Committee | NC |
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| Conference Date | 2002/3/13(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Neurocomputing (NC) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Predictive Self-Organizing Map for Vector Quantization of Migratory Signals and Its Application to Mobile Communications |
| Sub Title (in English) | |
| Keyword(1) | Neural network |
| Keyword(2) | Self-organizing map |
| Keyword(3) | adaptive vector quantization |
| Keyword(4) | time-series prediction |
| Keyword(5) | noise |
| Keyword(6) | mobile communication |
| Keyword(7) | Doppler effect |
| 1st Author's Name | Akira Hirose |
| 1st Author's Affiliation | Frontier Informatics, Graduate School of Frontier Sciences/RCAST, University of Tokyo() |
| 2nd Author's Name | Tomoyuki Nagashima |
| 2nd Author's Affiliation | Frontier Informatics, Graduate School of Frontier Sciences/RCAST, University of Tokyo |
| Date | 2002/3/13 |
| Paper # | NC2001-213 |
| Volume (vol) | vol.101 |
| Number (no) | 737 |
| Page | pp.pp.- |
| #Pages | 8 |
| Date of Issue | |