Search Results for "Bio Memristor"

12:38 EDT 30th May 2015 | BioPortfolio

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New memristor technology could bring us closer to brain-like computing

SOURCE April 8, 2015 (Nanowerk News) Researchers are always searching for improved technologies, but the most efficient computer possible already exists. It can learn and adapt without needing to be p...

Giant switchable photovoltaic effect in organometal trihalide perovskite devices

The direction of the current photogenerated in organic–inorganic perovskite films can be switched by poling the material with low electric fields that induce a reversible ion drift. Hybrid perovskit...

Training and operation of an integrated neuromorphic network based on metal-oxide memristors

Despite much progress in semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex, with its approximately 1014 synapses, makes the hardware implementation of ne...

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Experimental Demonstration of a Second-Order Memristor and Its Ability to Biorealistically Implement Synaptic Plasticity.

Memristors have been extensively studied for data storage and low-power computation applications. In this study, we show that memristors offer more than simple resistance change. Specifically, the dyn...

Memristor Models for Machine Learning.

In the quest for alternatives to traditional complementary metal-oxide-semiconductor, it is being suggested that digital computing efficiency and power can be improved by matching the precision to the...

Quasi-Linear Vacancy Dynamics Modeling and Circuit Analysis of the Bipolar Memristor.

The quasi-linear transport equation is investigated for modeling the bipolar memory resistor. The solution accommodates vacancy and circuit level perspectives on memristance. For the first time in lit...

Finite-time synchronization control of a class of memristor-based recurrent neural networks.

This paper presents a global and local finite-time synchronization control law for memristor neural networks. By utilizing the drive-response concept, differential inclusions theory, and Lyapunov func...

Memristor-Based Multilayer Neural Networks With Online Gradient Descent Training.

Learning in multilayer neural networks (MNNs) relies on continuous updating of large matrices of synaptic weights by local rules. Such locality can be exploited for massive parallelism when implementi...

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