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A Neural Network Design using Pulsewidth-Modulation (PWM) Technique  

전응련 (김천직업전문학교)
전흥우 (금오공과대학교)
송성해 (금오공과대학교)
정금섭 (구미기능대학교)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.6, no.1, 2002 , pp. 14-24 More about this Journal
Abstract
In this paper, a design of the pulsewidth-modulation(PWM) neural network with both retrieving and learning function is proposed. In the designed PWM neural system, the input and output signals of the neural network are represented by PWM signals. In neural network, the multiplication is one of the most commonly used operations. The multiplication and summation functions are realized by using the PWM technique and simple mixed-mode circuits. Thus, the designed neural network only occupies the small chip area. By applying some circuit design techniques to reduce the nonideal effects, the designed circuits have good linearity and large dynamic range. Moreover, the delta learning rule can easily be realized. To demonstrate the learning capability of the realized PWM neural network, the delta learning nile is realized. The circuit with one neuron, three synapses, and the associated learning circuits has been designed. The HSPICE simulation results on the two learning examples on AND function and OR function have successfully verified the function correctness and performance of the designed neural network.
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