Hopfield网络物理模型中能量与计算之间的联系

Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02. Pub Date : 2002-11-18 DOI:10.1109/ICONIP.2002.1202175

A. Kumar, V. Manmohan, M. Uday Shankar, M. Vishwanathan, V. Chakravarthy

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引用次数: 5

摘要

Landauer(1961)通过热力学将信息处理和能量流动联系起来，提出不可逆的计算过程具有不可避免的“热力学成本”。我们在联想记忆的神经网络模型中探讨了这种联系的存在。我们对Hopfield神经网络电子实现的模拟表明，网络性能的增强只能通过增加能量作为热量的耗散来获得。相反，最小化能量耗散的努力会导致性能受损。

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Link between energy and computation in a physical model of Hopfield network

Linking information processing and energy flows via thermodynamics, Landauer (1961) proposed that irreversible computational processes have an inevitable "thermodynamic cost". We explore the existence of such a link in case of a neural network model of associative memory. Our simulations with an electronic implementation of the Hopfield neural network showed that enhanced performance of the network could only be obtained by increased dissipation of energy as heat. Contrarily, efforts to minimize energy dissipation led to impaired performance.

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Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02.

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