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| Tekijä: | Koda, M. Okano, H. |
| Otsikko: | A new stochastic learning algorithm for neural networks |
| Lehti: | Journal of the Operations Research Society of Japan
2000 : DEC, VOL. 43:4, p. 469-485 |
| Asiasana: | NETWORK ANALYSIS STOCHASTIC PROGRAMMING ALGORITHMS |
| Kieli: | eng |
| Tiivistelmä: | A new stochastic learning algorithm using Gaussian white noise sequence, referred to as Subconscious Noise Reaction (SNR), is proposed for a class of discrete-time neural networks with time-dependent connection weights. Unlike the back-propagation-through-time (BTT) algorithm, SNR does not require the synchronous transmission of information backward along connection weights, while it uses only ubiquitous noise and local signals, which are correlated against a single performance functional, to achieve simple sequential updating of connection weights. |
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