Titlebook: Handbook of Memristor Networks; Leon Chua,Georgios Ch. Sirakoulis,Andrew Adamatzky Book 2019 Springer Nature Switzerland AG 2019 Memristor

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,Memristors and Memristive Devices for?Neuromorphic Computing, memistor framework developed by Leon Chuan nearly 40 years ago, and examine resistive switching phenomena as the quintessential example of physical memristive systems. A special focus is given to the hardware emulation of biological synapses using memristors and groundbreaking results in the field

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,Self-organization and Emergence of?Dynamical Structures in?Neuromorphic Atomic Switch?Networks,context of modern trends in neuromorphic engineering, this work introduces an effort toward the construction of purpose-built dynamical systems. Known as?atomic switch networks (ASN), these systems consist of highly interconnected, physically?recurrent networks of inorganic synapses (atomic switches

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,Spike-Timing-Dependent-Plasticity with?Memristors,ically, we are linking one type of memristor nano technology devices to the biological synaptic update rule known as Spike-Time-Dependent-Plasticity found in real biological synapses. Understanding this link allows neuromorphic engineers to develop circuit architectures that use this type of memrist

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Designing Neuromorphic Computing Systems with Memristor Devices, applications. One way to implement neuromorphic systems in hardware is to use the new emerging devices such as Resistive RAM (ReRAM or Memristor), because of the promising features these devices provide, such as low feature size, extremely low power consumption, synaptic like behavior, and scalabil

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Brain-Inspired Memristive Neural Networks for Unsupervised Learning,sticity in the human brain. This fascinating analogy has provided the inspiration for many recent research advances, involving memristive devices and their use as artificial electronics synapses in neuromorphic circuits with learning capability. In particular, RRAM-based artificial synapses are extr

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Neuromorphic Devices and Networks Based on Memristors with Ionic Dynamics,mputation, e.g. nonstructured data processing, where memristors are considered as promising building blocks for the construction of neuromorphic networks. However, the lack of clear understanding on memristive switching dynamics (especially for oxide memristors), the undesirable nonlinearity in cond

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Leon Chua,Georgios Ch. Sirakoulis,Andrew AdamatzkyCovers all aspects of memristor networks in detail.Explains how to realise computing devices from memristors.Presents the latest developments in the field of memristor networks

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替代品

https://doi.org/10.1007/978-3-319-76375-0Memristor Networks; Two-terminal device; State-dependent Ohm‘s law; Computation; Electronic component