標題: Constructing hysteretic memory in neural networks
作者: Wei, JD
Sun, CT
資訊工程學系
Department of Computer Science
關鍵字: hysteresis;hysteretic memory;rate independence;recurrent network;reinforcement learning;time delay neural network
公開日期: 1-Aug-2000
摘要: Hysteresis is a unique type of dynamic, which contains an important property, rate-independent memory. In addition to other memory-related studies such as time delay neural networks, recurrent networks, and reinforcement learning, rate-independent memory deserves further attention owing to its potential applications. In this work, we attempt to define hysteretic memory (rate-independent memory) and examine whether or not it could be modeled in neural networks. Our analysis results demonstrate that other memory-related mechanisms are not hysteresis systems. A novel neural cell, referred to herein as the propulsive neural unit, is then proposed. The proposed cell is based on a notion related the submemory pool, which accumulates the stimulus and ultimately assists neural networks to achieve model hysteresis. In addition to training by backpropagation, a combination of such cells can simulate given hysteresis trajectories.
URI: http://dx.doi.org/10.1109/3477.865179
http://hdl.handle.net/11536/30354
ISSN: 1083-4419
DOI: 10.1109/3477.865179
期刊: IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
Volume: 30
Issue: 4
起始頁: 601
結束頁: 609
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