Systolic implementation of 2D block-based Hopfield neural network for efficient pattern association

Ming-Jung Seow; Hau Ngo; Vijayan K. Asari

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Systolic implementation of 2D block-based Hopfield neural network for efficient pattern association

机译：基于二维块的Hopfield神经网络的脉动实现，可实现有效的模式关联

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摘要

A systolic array implementation of block-based Hopfield neural network architecture using completely digital circuits is presented in this paper. The design is based on modelling the energy equation of Hopfield neural network to a systolic (or modular) form. It is shown mathematically that the modified energy equation converges in all circumstances. In addition, it is shown that the architecture provides massive parallelism and can be extended to a larger network by cascading identical chips. The performance of the proposed architecture is evaluated by applying various binary inputs and it is observed that it exhibits the same characteristics of block-based Hopfield neural network in terms of convergence and pattern association.

机译：本文提出了使用完全数字电路的基于块的Hopfield神经网络架构的脉动阵列实现。该设计基于将Hopfield神经网络的能量方程建模为收缩（或模块化）形式。数学上表明，修正的能量方程在所有情况下都收敛。此外，还显示出该架构提供了巨大的并行性，并且可以通过级联相同的芯片将其扩展到更大的网络。通过应用各种二进制输入来评估所提出的体系结构的性能，并且观察到它在收敛性和模式关联方面展现出基于块的Hopfield神经网络的相同特征。

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来源
《Microprocessors and microsystems》 |2003年第8期|p.359-366|共8页
作者
Ming-Jung Seow; Hau Ngo; Vijayan K. Asari;
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作者单位

Department of Electrical and Computer Engineering, Old Dominion University, Norfolk, VA 23529, USA;

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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
中图分类计算技术、计算机技术;
关键词
hopfield network; pattern association; modular architecture; systolic implementation;

机译：Hopfield网络;模式关联;模块化架构;脉动实现;

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1. Hardware implementation of evolvable block-based neural networks utilizing a cost efficient sigmoid-like activation function [J] . Nambiar Vishnu P., Khalil-Hani Mohamed, Sahnoun Riadh, Neurocomputing . 2014,第sepa22期

机译：可扩展的基于块的神经网络的硬件实现，其使用了具有成本效益的类Sigmoid激活函数
2. Hopfield neural networks for state estimation: parameters, efficient implementation and results [J] . F. Garcia-Lagos, G. Joya, F. J. Marin, Elektrotechnik und Informationstechnik . 2000,第1期

机译：Hopfield神经网络用于状态估计：参数，有效的实现和结果
3. Efficient modeling of vector hysteresis using a novel Hopfield neural network implementation of Stoner–Wohlfarth-like operators [J] . Amr A. Adly, Salwa K. Abd-El-Hafiz Journal of Advanced Research . 2013,第4期

机译：使用类似于Stoner–Wohlfarth算子的新型Hopfield神经网络实现的矢量磁滞有效建模
4. Systolic array implementation of block based Hopfield neural network for pattern association [C] . Ming-Jung Seow, Hau Ngo, Asari, . 2003

机译：基于块的Hopfield神经网络模式关联的脉动阵列实现
5. Mathematical analysis of hopfield networks and neural networks implementation of steering controls for semilinear systems. [D] . Pandit, Purnima. 2007

机译：Hopfield网络和神经网络对半线性系统转向控制的数学分析。
6. Efficient modeling of vector hysteresis using a novel Hopfield neural network implementation of Stoner–Wohlfarth-like operators [O] . Amr A. Adly, Salwa K. Abd-El-Hafiz 2013

机译：使用类似于Stoner–Wohlfarth算子的新型Hopfield神经网络实现的矢量磁滞有效建模
7. Systolic Array Implementation of Block Based Hopfield Neural Network for Pattern Association [O] . Ming-jung Seow, Hau Ngo, Vijayan Asari 2008

机译：基于块的Hopfield神经网络模式关联的脉动阵列实现
8. Analysis of the Hopfield Neural Networks and Their Application to Pattern Recognition [R] . Gerasimas, B. F. 1988

机译：Hopfield神经网络分析及其在模式识别中的应用

Systolic implementation of 2D block-based Hopfield neural network for efficient pattern association

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