Hardware-oriented algorithm for associative memories on cellular neural networks

R. Perfetti, M. Salerno, G. Costantini
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Abstract

We present a new learning algorithm used to implement associative memories on digital cellular neural networks. The algorithm can be easily implemented in hardware or simulated on a digital computer without numerical errors. These attractive features come from the finite precision of connection weights, automatically taken into account as a design constraint; moreover, no multiplication is needed for weight computation.
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面向硬件的细胞神经网络联想记忆算法
提出了一种新的学习算法,用于在数字细胞神经网络上实现联想记忆。该算法可以很容易地在硬件上实现或在数字计算机上模拟,没有数值误差。这些吸引人的特点来自于连接权值的有限精度,自动考虑作为设计约束;此外,权重计算不需要乘法。
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