基于模塊電路結構的BP神經網絡及其應用研究
A MODULAR STRUCTURE BASED BP NEURAL NETWORK AND ITS APPLICATION
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摘要: 本文采用一種簡化的BP(Back Propagation)神經網絡硬件模塊實現(xiàn)方法。該方法利用全電流模式電路組成神經元模塊,再用若干模塊構成簡化的BP神經網絡。所提出的模塊結構網絡系統(tǒng)具有在線學習和在線權值存儲能力,且可應用于實現(xiàn)編、解碼和二維圖像識別。文中提供了PSPICE和高級語言計算機仿真結果。Abstract: This paper presents a hardware implementation approach for realizing simple BP (Backward Propagation) neural network. The full current-mode analog circuits are used to form neuron modules, and a simple BP network is build using basic modules. This network has the property of on-chip learning and on-chip weight storing, and it can be used for coding, decoding and two-dimensional image recognition. Simuiation results with PSPICE and high-level languages are given.
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Bibyk S, et al. Current-mode neural network building blocks for analog MOS VLSI. IEEE ISCAS,[2]Helsinki: 1990, 3283-3285.[3]Mead C. Analog VLSI and Nearal Networks. Reading, Meassachusetts: Addison Wesley, 1989. [3] 龐維珍, 任魯涌, 等. 在片學習及權值刷新神經網絡硬件實現(xiàn)方法的研究. 天津大學學報. 1996, 29(6): 821-827.[4]Salam F, Choi M. An all-MOS analog feedforward neural circuit with learning. IEEE ISCAS, Helsinki: 1990, 2508-2511. -
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