AIMC Topic:
Neurons

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Deep and shallow architecture of multilayer neural networks.

IEEE transactions on neural networks and learning systems Jan 15, 2015
This paper focuses on the deep and shallow architecture of multilayer neural networks (MNNs). The demonstration of whether or not an MNN can be replaced by another MNN with fewer layers is equivalent to studying the topological conjugacy of its hidde...
Algorithms Humans Neurons Models, Neurological Neural Networks, Computer Nerve Net
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Effects of long-term representations on free recall of unrelated words.

Learning & memory (Cold Spring Harbor, N.Y.) Jan 15, 2015
Human memory stores vast amounts of information. Yet recalling this information is often challenging when specific cues are lacking. Here we consider an associative model of retrieval where each recalled item triggers the recall of the next item base...
Young Adult Adult Models, Neurological Models, Statistical Adolescent Humans Neural Networks, Computer Memory, Long-Term Neurons Mental Recall
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Memristor-based multilayer neural networks with online gradient descent training.

IEEE transactions on neural networks and learning systems Jan 14, 2015
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 implementing MNNs in hardware. However, these update rules r...
Online Systems Neurons Synapses Humans Computer Simulation Neural Networks, Computer Learning Algorithms Signal Processing, Computer-Assisted
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Lag Synchronization of Switched Neural Networks via Neural Activation Function and Applications in Image Encryption.

IEEE transactions on neural networks and learning systems Jan 14, 2015
This paper investigates the problem of global exponential lag synchronization of a class of switched neural networks with time-varying delays via neural activation function and applications in image encryption. The controller is dependent on the outp...
Neurons Models, Statistical Algorithms Nonlinear Dynamics Color Neural Networks, Computer Image Processing, Computer-Assisted
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On the role of astroglial syncytia in self-repairing spiking neural networks.

IEEE transactions on neural networks and learning systems Jan 6, 2015
It has been shown that brain-like self-repair can arise from the interactions between neurons and astrocytes where endocannabinoids are synthesized and released from active neurons. This retrograde messenger feeds back to local synapses directly and ...
Nerve Net Neurons Models, Neurological Astrocytes Humans Action Potentials Neural Networks, Computer Synapses
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Energy-to-peak state estimation for Markov jump RNNs with time-varying delays via nonsynchronous filter with nonstationary mode transitions.

IEEE transactions on neural networks and learning systems Jan 6, 2015
In this paper, the problem of energy-to-peak state estimation for a class of discrete-time Markov jump recurrent neural networks (RNNs) with randomly occurring nonlinearities (RONs) and time-varying delays is investigated. A practical phenomenon of n...
Time Factors Models, Neurological Markov Chains Nonlinear Dynamics Neurons Neural Networks, Computer Algorithms Computer Simulation Humans
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Stochastic stability of delayed neural networks with local impulsive effects.

IEEE transactions on neural networks and learning systems Dec 25, 2014
In this paper, the stability problem is studied for a class of stochastic neural networks (NNs) with local impulsive effects. The impulsive effects considered can be not only nonidentical in different dimensions of the system state but also various a...
Humans Nerve Net Models, Neurological Neural Networks, Computer Stochastic Processes Neurons
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Learning-regulated context relevant topographical map.

IEEE transactions on neural networks and learning systems Dec 24, 2014
Kohonen's self-organizing map (SOM) is used to map high-dimensional data into a low-dimensional representation (typically a 2-D or 3-D space) while preserving their topological characteristics. A major reason for its application is to be able to visu...
Humans Neural Networks, Computer Algorithms Cluster Analysis Models, Neurological Neurons Learning Time Factors
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Inhibition facilitates direction selectivity in a noisy cortical environment.

Journal of computational neuroscience Nov 18, 2014
In a broad class of models, direction selectivity in primary visual cortical neurons arises from the linear summation of spatially offset and temporally lagged inputs combined with a spike threshold. Here, we characterize the robustness of this class...
Models, Neurological Noise Neurons Neural Networks, Computer Algorithms Neural Inhibition Cerebral Cortex Photic Stimulation
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Passivity and Passification of Memristor-Based Recurrent Neural Networks With Additive Time-Varying Delays.

IEEE transactions on neural networks and learning systems Nov 13, 2014
This paper presents a new design scheme for the passivity and passification of a class of memristor-based recurrent neural networks (MRNNs) with additive time-varying delays. The predictable assumptions on the boundedness and Lipschitz continuity of ...
Humans Neural Networks, Computer Memory Models, Neurological Algorithms Reaction Time Time Factors Neurons
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