| Presentation | 2009-05-25 Advantages and their origins of complex-valued neural networks Akira HIROSE, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | We discuss the merits of complex-valued neural networks (CVNNs) and their origin. First we look back the mathematical history to elucidate the features of complex numbers, in particular to confirm the importance of the phase-and-amplitude viewpoint for designing and constructing CVNNs to enhance the features. The viewpoint is essential in general to deal with waves such as electromagnetic-wave and lightwave. Then we point out that, although we represent a complex number as an ordered pair of real numbers for example, we can reduce ineffective degree of freedom in learning or self-organization in CVNNs to achieve better generalization characteristics. This wave-oriented merit is useful widely for general signal processing with Fourier synthesis or in frequency-domain treatment through Fourier transform. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Complex number / ordered pair of real numbers / real 2×2 matrix representation / generalization |
| Paper # | NC2009-2 |
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| Committee | NC |
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| Conference Date | 2009/5/18(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) | Advantages and their origins of complex-valued neural networks |
| Sub Title (in English) | |
| Keyword(1) | Complex number |
| Keyword(2) | ordered pair of real numbers |
| Keyword(3) | real 2×2 matrix representation |
| Keyword(4) | generalization |
| 1st Author's Name | Akira HIROSE |
| 1st Author's Affiliation | Department of Electric Engineering and Information Systems, The University of Tokyo() |
| Date | 2009-05-25 |
| Paper # | NC2009-2 |
| Volume (vol) | vol.109 |
| Number (no) | 53 |
| Page | pp.pp.- |
| #Pages | 6 |
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