Finite iteration DT-CNN - new design and operating principles

C. Merkwirth, Jochen Bröcker, M. Ogorzałek, J. Wichard
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引用次数: 7

Abstract

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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有限迭代DT-CNN -新的设计和工作原理
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。
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