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The switching behavior of individual non-volatile memory devices thus cannot be described within the mathematical framework proposed for memristor/memristive systems. An extra thermodynamic curiosity arises from the definition that memristors/memristive devices should energetically act like resistors.
Neuromorphic devices have also been demonstrated using nanocrystals, nanowires, and conducting polymers. [27] There also is development of a memristive device for quantum neuromorphic architectures. [28] In 2022, researchers at MIT have reported the development of brain-inspired artificial synapses, using the ion proton (H +), for 'analog deep ...
On the other hand, a cross-point architecture is more compact and may enable vertically stacking memory layers, ideal suited for mass-storage devices. However, in the absence of any transistors, isolation must be provided by a "selector" device, such as a diode, in series with the memory element or by the memory element itself. Such isolation ...
A silver nanowire connectome [10] can be described using graph theory, and have applications ranging from sensors to information storage.Since memristive devices behave as axons in a neuronal network, the theory of memristive networks is the theory of nanoscale electric physical devices whose behavior parallels the one of real neuronal circuits ...
In the paper "Memristive Devices and Systems" by Chua and Kang (1976) the model of memristive systems was shown to be applicable to the Hodgkin-Huxley model describing action potentials in neurons. Greg Snider at HP Labs is also working on designing a neuromorphic architecture based on memristors which was described at the 2008 Memristor and ...
While the memristor is defined in terms of a two-terminal circuit element, there was an implementation of a three-terminal device called a memistor developed by Bernard Widrow in 1960. Memistors formed basic components of a neural network architecture called ADALINE developed by Widrow. [1] [2] The memistor was also used in MADALINE.
These types of devices would allow for a synapse model that could realise a learning rule, by which the synaptic efficacy is altered by voltages applied to the terminals of the device. An example of such a learning rule is spike-timing-dependant-plasticty by which the weight of the synapse, in this case the conductivity, could be modulated ...
An early example of a MEMS device is the resonant-gate transistor, an adaptation of the MOSFET, developed by Robert A. Wickstrom for Harvey C. Nathanson in 1965. [4] Another early example is the resonistor, an electromechanical monolithic resonator patented by Raymond J. Wilfinger between 1966 and 1971.