AIMC Topic: Memory

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Emergence of low noise frustrated states in E/I balanced neural networks.

Neural networks : the official journal of the International Neural Network Society Sep 8, 2016
We study emerging phenomena in binary neural networks where, with a probability c synaptic intensities are chosen according with a Hebbian prescription, and with probability (1-c) there is an extra random contribution to synaptic weights. This new te...
Neurons Probability Synapses Animals Noise Monte Carlo Method Nerve Net Memory Random Allocation Cerebral Cortex Neural Networks, Computer
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Extended dissipative state estimation for memristive neural networks with time-varying delay.

ISA transactions Jun 2, 2016
This paper investigates the problem of extended dissipative state estimation for memristor-based neural networks (MNNs) with time-varying delay. Based on both nonsmooth analysis and the construction of a new Lyapunov-Krasovskii functional, the extend...
Computer Simulation Neurons Memory Neural Networks, Computer Nonlinear Dynamics Algorithms
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All Spin Artificial Neural Networks Based on Compound Spintronic Synapse and Neuron.

IEEE transactions on biomedical circuits and systems May 17, 2016
Artificial synaptic devices implemented by emerging post-CMOS non-volatile memory technologies such as Resistive RAM (RRAM) have made great progress recently. However, it is still a big challenge to fabricate stable and controllable multilevel RRAM. ...
Neurons Semiconductors Synapses Neural Networks, Computer Magnetics Memory
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Memory recall and spike-frequency adaptation.

Physical review. E May 13, 2016
The brain can reproduce memories from partial data; this ability is critical for memory recall. The process of memory recall has been studied using autoassociative networks such as the Hopfield model. This kind of model reliably converges to stored p...
Neural Networks, Computer Neurons Memory Humans Behavior
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Is cortical connectivity optimized for storing information?

Nature neuroscience Apr 11, 2016
Cortical networks are thought to be shaped by experience-dependent synaptic plasticity. Theoretical studies have shown that synaptic plasticity allows a network to store a memory of patterns of activity such that they become attractors of the dynamic...
Memory Neural Networks, Computer Models, Neurological Cerebral Cortex Neuronal Plasticity
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Mechanisms of memory storage in a model perirhinal network.

Brain structure & function Mar 12, 2016
The perirhinal cortex supports recognition and associative memory. Prior unit recording studies revealed that recognition memory involves a reduced responsiveness of perirhinal cells to familiar stimuli whereas associative memory formation is linked ...
Perirhinal Cortex Memory Interneurons Action Potentials Neurons Humans Neural Networks, Computer Neuronal Plasticity Models, Neurological Animals
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A new Growing Neural Gas for clustering data streams.

Neural networks : the official journal of the International Neural Network Society Feb 26, 2016
Clustering data streams is becoming the most efficient way to cluster a massive dataset. This task requires a process capable of partitioning observations continuously with restrictions of memory and time. In this paper we present a new algorithm, ca...
Neural Networks, Computer Algorithms Humans Datasets as Topic Databases, Factual Statistics as Topic Cluster Analysis Memory
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Synchronization of Delayed Memristive Neural Networks: Robust Analysis Approach.

IEEE transactions on cybernetics Dec 22, 2015
This paper considers the asymptotic and finite-time synchronization of drive-response memristive neural networks (MNNs) with time-varying delays. It is known that the parameters of MNNs are state-dependent, and hence the traditional robust control an...
Nonlinear Dynamics Neural Networks, Computer Memory Time Factors Models, Theoretical Electrical Equipment and Supplies
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Memory Stacking in Hierarchical Networks.

Neural computation Dec 14, 2015
Robust representations of sounds with a complex spectrotemporal structure are thought to emerge in hierarchically organized auditory cortex, but the computational advantage of this hierarchy remains unknown. Here, we used computational models to stud...
Neural Networks, Computer Memory Brain Humans Computer Simulation Association Learning Neurons Synapses Models, Neurological Action Potentials
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Efficient Associative Computation with Discrete Synapses.

Neural computation Nov 24, 2015
Neural associative networks are a promising computational paradigm for both modeling neural circuits of the brain and implementing associative memory and Hebbian cell assemblies in parallel VLSI or nanoscale hardware. Previous work has extensively in...
Neuronal Plasticity Learning Models, Neurological Humans Synapses Animals Memory Neural Networks, Computer
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