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}}</ref> The [[memristors]] (memory resistors) are implemented by thin film materials in which the resistance is electrically tuned via the transport of ions or oxygen vacancies within the film. [[DARPA]]'s [[SyNAPSE|SyNAPSE project]] has funded IBM Research and HP Labs, in collaboration with the Boston University Department of Cognitive and Neural Systems (CNS), to develop neuromorphic architectures that may be based on memristive systems.
[[Memristive networks]] are a particular type of [[physical neural network]] that have very similar properties to (Little-)Hopfield networks, as they have continuous dynamics, a limited memory capacity and natural relaxation via the minimization of a function which is asymptotic to the [[Ising model]]. In this sense, the dynamics of a memristive circuit have the advantage compared to a Resistor-Capacitor network to have a more interesting non-linear behavior. From this point of view, engineering analog memristive networks account for a peculiar type of [[neuromorphic engineering]] in which the device behavior depends on the circuit wiring or topology.
The evolution of these networks can be studied analytically using variations of the [[
=== Continuous-time ===
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