THERMODYNAMIC COMPUTING
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United States of America Patent
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Issued Date -
Jan 15, 2015
app pub date -
Jul 3, 2014
filing date -
Jul 9, 2013
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Abstract
Methods and systems for thermodynamic computing based on the attractor dynamics of volatile dissipative electronics attempting to maximize circuit power consumption. A general model of memristive devices based on collections of metastable switches, adaptive synaptic weights can be formed from a differential pair of memristors and modified according to anti-hebbian and hebbian plasticity. The arrays of synaptic weights can be employed to build a neural node circuit with attractor states that are shown to be logic functions forming a computationally complete set. By configuring the attractor states of the computational building block in different ways, high-level machine learning functions can be demonstrated for real-world applications.
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