线性图像滤波中模拟VLSI神经网络的随机参数变化

Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94) Pub Date : 1994-06-27 DOI:10.1109/ICNN.1994.374453

Bertram E. Shi, T. Roska, L. Chua

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引用次数: 5

摘要

本文介绍了一种分析方法来确定用于线性图像滤波的模拟VLSI神经网络结构对随机参数变化的灵敏度。作者比较了几种不同的电路结构对低通滤波的鲁棒性。此方法还可以确定应该最精确地指定特定体系结构中的哪些组件。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Random parameter variation in analog VLSI neural networks for linear image filtering

This paper introduces an analytic method to determine the sensitivity to random parameter variations of analog VLSI neural network architectures for linear image filtering. The authors compare the robustness of several different circuit architectures for low pass filtering. This method can also determine which components within a particular architecture should specified the most precisely.<>

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Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)

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