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Design of associative memories using cellular neural networks

机译:基于细胞神经网络的联想记忆设计

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摘要

Cellular neural networks (CNNs) have locally connected neurons. This characteristic makes CNNs adequate for hardware implementation and, consequently, for their employment on a variety of applications as real-time image processing and construction of efficient associative memories. Adjustments of CNN parameters is a complex problem involved in the configuration of CNN for associative memories. This paper reviews methods of associative memory design based on CNNs, and provides comparative performance analysis of these approaches.
机译:细胞神经网络(CNN)具有本地连接的神经元。此特性使CNN足够用于硬件实现,因此适合在多种应用中用作实时图像处理和有效的关联存储器的构造。 CNN参数的调整是关联存储器CNN配置中涉及的一个复杂问题。本文回顾了基于CNN的联想记忆设计方法,并对这些方法进行了比较性能分析。

著录项

  • 来源
    《Neurocomputing》 |2009年第12期|2180-2188|共9页
  • 作者单位

    Institute of Mathematical and Computer Sciences-ICMC, University of Sao Paulo-USP, Postal 668, 13560-970 Sao Carlos, SP, Brazil;

    Institute of Mathematical and Computer Sciences-ICMC, University of Sao Paulo-USP, Postal 668, 13560-970 Sao Carlos, SP, Brazil;

    Institute of Mathematical and Computer Sciences-ICMC, University of Sao Paulo-USP, Postal 668, 13560-970 Sao Carlos, SP, Brazil;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    cellular neural networks; associative memories; performance comparison;

    机译:细胞神经网络联想记忆;性能比较;
  • 入库时间 2022-08-18 02:08:30

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