有限迭代DT-CNN -新的设计和工作原理

2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512) Pub Date : 2004-05-23 DOI:10.1109/ISCAS.2004.1329696

C. Merkwirth, Jochen Bröcker, M. Ogorzałek, J. Wichard

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引用次数: 7

摘要

本文提出在有限迭代模式下使用离散时间细胞神经网络(DT-CNN)。在这种操作模式下，不需要对模板的稳定性有特殊要求。提出了一种基于建设性反向传播的模板设计算法。对于给定的迭代次数，我们可以为要解决的给定问题找到最优的模板序列。我们的新方法通过数字识别DT-CNN的设计来证明。

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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Finite iteration DT-CNN - new design and operating principles

In this paper we propose to use the discrete-time cellular neural network (DT-CNN) in a finite iterate mode. In such a mode of operation no special requirements on template stability properties are needed. We propose a constructive back propagation based algorithm for template design. For a given number of iterations we can find optimal sequence of templates for a given problem to be solved. Our novel approach is demonstrated by a design of a digit recognition DT-CNN.

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2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512)

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