Design and evaluation of single-electron associative memory circuit
Design and evaluation of single-electron associative memory circuit
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单电子联想存储电路的设计与评估
DOI：
10.1080/17445760.2016.1165219
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
and Oya T.
中科院分区：
文献类型：
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作者：
Takano M.;Asai T.;and Oya T.
近年来，神经网络因其具有并行处理、噪声抑制等优点而受到广泛关注。神经网络由许多神经元组成，这些神经元并行工作，每个神经元随机工作。虽然每个神经元对噪声敏感并且行为随机，但是基于神经元的网络可以以高可靠性运行。此外，已知该网络表现出各种复杂的功能。在这项研究中，我们试图通过纳米电子电路-即单电子（SE）电路来模拟NN的这些有用功能。由于概率电子隧穿现象，SE电路也像生物神经元一样随机运行。因此，它可以用于实现随机神经元操作。在这项工作中，我们提出了一种方法，用于硬件NN的SE电路的实现，并确认它可以通过计算机模拟执行的联想记忆功能。首先，我们模拟了无噪声的电路操作。这个模拟表明，我们的电路可以存储一些模式，并从给定的噪声或相关模式中调用它们。然而，它不能回忆一些输入模式。在下一步中，我们模拟电路中的热噪声。因此，我们可以改善召回失败率，提高电路性能。
Recently, neural networks (NN) have attracted much attention because they have many advantages such as parallel-processing and noise-harnessing functions. An NN is composed of many neurons, which operate in parallel and each one operates stochastically. Although each neuron is sensitive to noise and behaves randomly, a network based on the neurons can operate with high reliability. Moreover, it is known that the network exhibits various complicated functions. In this study, we attempt to mimic such useful functions of the NN by nanoelectronic circuits – i.e. single-electron (SE) circuits. The SE circuit also operates stochastically, like a biological neuron, because of the probabilistic electron tunneling phenomenon. Therefore, it can be used for implementing the stochastic neuron operation. In this work, we propose a method for hardware NN implementation on the SE circuit and confirm that it can perform the associative memory function by computer simulation. First, we simulate the circuit operation without noise. This simulation demonstrates that our circuit can store some patterns and recall them from a given noisy or related pattern. However, it fails to recall some input patterns. In the next step, we simulate thermal noise in the circuit. As a result, we can improve the failure rate in recall and increase circuit performance.