Presentation | 1998/4/23 A Self-Learning Digital Neural Network LSI using Sparse-Memory-Access Architecture Osamu Saito, Kimihisa Aihara, Osamu Fujita, Kuniharu Uchimura, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This digital neural network chip executes 10 GCPS for forward clalculations and 1 GCUPS for learning calculations. The chip can handle a 1 million synapse network together with external SRAM chips. Using sparse memory-access (SMA) architecture, unnecessary operations due to the nonlinera nature of neuron can be automatically eliminated without an effect on accuracy. A chip is fabricated using a 0.25 μm CMOS embedded array process and contains 64 processing units (UPs), and an eight-port external RAM access control unit to take full advantage of SMA architecute. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Neural Network / Neurochip / Digital Signal Processing / VLSI |
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Committee | ICD |
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Conference Date | 1998/4/23(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Registration To | Integrated Circuits and Devices (ICD) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | A Self-Learning Digital Neural Network LSI using Sparse-Memory-Access Architecture |
Sub Title (in English) | |
Keyword(1) | Neural Network |
Keyword(2) | Neurochip |
Keyword(3) | Digital Signal Processing |
Keyword(4) | VLSI |
1st Author's Name | Osamu Saito |
1st Author's Affiliation | NTT Integrated Information & Energy Systems Laboratories() |
2nd Author's Name | Kimihisa Aihara |
2nd Author's Affiliation | NTT Network Service Systems Laboratories |
3rd Author's Name | Osamu Fujita |
3rd Author's Affiliation | NTT System Elecrtronics Laboratories |
4th Author's Name | Kuniharu Uchimura |
4th Author's Affiliation | NTT Integrated Information & Energy Systems Laboratories |
Date | 1998/4/23 |
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Volume (vol) | vol.98 |
Number (no) | 22 |
Page | pp.pp.- |
#Pages | 8 |
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