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    • 88. 发明申请
    • THERMODYNAMIC COMPUTING
    • 热力计算机
    • US20150019468A1
    • 2015-01-15
    • US14323451
    • 2014-07-03
    • KnowmTech, LLC
    • Alex NugentTimothy Molter
    • G06N3/08G06N99/00
    • G06N3/063G06N3/0418Y10S901/46
    • 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.
    • 基于挥发性耗散电子的吸引子动力学的热力学计算方法和系统试图最大化电路功耗。 基于亚稳开关集合的回忆装置的一般模型,可以由差分对的忆阻器形成自适应突触重量,并根据反比较和hebbian可塑性进行修改。 可以使用突触权重的阵列来构建具有吸引子状态的神经节点电路,所述神经节点电路被显示为形成计算完整集合的逻辑功能。 通过以不同的方式配置计算构建块的吸引子状态,可以为实际应用演示高级机器学习功能。