具有可调输出单元的亚微米模拟神经网络

Proceedings of the Tenth International Conference on Microelectronics (Cat. No.98EX186) Pub Date : 1998-12-14 DOI:10.1109/ICM.1998.825622

A.H. Abutalebi, S. M. Fakhraie

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引用次数: 4

摘要

描述了一种亚微米前馈模拟神经网络。该网络的突触使用亚微米吉尔伯特乘法器，神经元使用基于电流比较器电路的新型电路。该网络解决了异或问题，证明了实现多层网络的能力。该网络采用0.5 /spl mu/m的技术设计。HSPICE仿真验证了该网络运行的有效性。

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A submicron analog neural network with an adjustable-level output unit

A submicron feedforward analog neural network is described. This network uses submicron Gilbert multipliers for its synapses and a novel circuit based on the current-comparator circuit for its neuron. The XOR problem is solved by this network to demonstrate the capability of implementing multi-layer networks. The network is designed in a 0.5 /spl mu/m technology. HSPICE simulation shows the validity of the operation of the network.

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Proceedings of the Tenth International Conference on Microelectronics (Cat. No.98EX186)

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