環(huán)結(jié)構(gòu)神經(jīng)網(wǎng)絡(luò)及其互聯(lián)想性能
LOOP ARCHITECTURE NEURAL NETWORK
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摘要: 本文提出了一種稱為環(huán)結(jié)構(gòu)神經(jīng)網(wǎng)絡(luò)(LANN)模型及其學(xué)習(xí)算法。它能像Hopfield網(wǎng)絡(luò),雙向聯(lián)想記憶(BAM)網(wǎng)絡(luò)和其它類(lèi)似網(wǎng)絡(luò)一樣工作,特別是它能執(zhí)行多類(lèi)樣本之間的互聯(lián)想記憶。理論分析和計(jì)算機(jī)模擬都證明LANN具有很好的收斂性,是一種有效的網(wǎng)絡(luò)結(jié)構(gòu)。最后本文給出了計(jì)算機(jī)模擬結(jié)果。Abstract: This paper provides a new architecture of neural network, called Loop Architecture Neural Network (LANN), and its learning rules. One of its distinguished features from other network, such as Hopfield and bidirectional assiociative memories, is that it can perform the associative memory among multiple categories. Analysis and simulated results have proved that it is an effective network with excellent convergence.
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Farhat N H, Psaltis P. Prata A, et al[J].Applied Optics.1985, 24(10):1469-1475[2]Hopfield J J.[3]Neurons with graded response have collective computational properities like those of two states neurons. Proceedings of the National Academy of Sciences, USA; 31, May,1984. 3088-3092.[4]Anderson J A. IEEE Trans. on Systems, Man, and Cybernetics, 1983, SMC-13(5): 799-815.[5]Kosko B. Applied Optics, 1981, 26(23): 4974-4979. -
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