AIMC Journal:
IEEE transactions on neural networks and learning systems

Showing 711 to 720 of 817 articles

Mode-Dependent Stochastic Synchronization for Markovian Coupled Neural Networks With Time-Varying Mode-Delays.

IEEE transactions on neural networks and learning systems Jan 20, 2015
This paper investigates the stochastic synchronization problem for Markovian hybrid coupled neural networks with interval time-varying mode-delays and random coupling strengths. The coupling strengths are mutually independent random variables and the...
Stochastic Processes Neural Networks, Computer Computer Simulation Time Factors Markov Chains
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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...
Humans Nerve Net Models, Neurological Neural Networks, Computer Neurons Algorithms
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Stability criteria for recurrent neural networks with time-varying delay based on secondary delay partitioning method.

IEEE transactions on neural networks and learning systems Jan 15, 2015
A secondary delay partitioning method is proposed to study the stability problem for a class of recurrent neural networks (RNNs) with time-varying delay. The total interval of the time-varying delay is first divided into two parts, and then each part...
Nonlinear Dynamics Humans Computer Simulation Neural Networks, Computer Time Factors Algorithms Models, Theoretical
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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...
Humans Signal Processing, Computer-Assisted Neurons Online Systems Synapses Neural Networks, Computer Algorithms Computer Simulation Learning
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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...
Models, Statistical Color Nonlinear Dynamics Neurons Algorithms 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 ...
Neurons Synapses Nerve Net Action Potentials Astrocytes Neural Networks, Computer Humans Models, Neurological
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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 Algorithms Computer Simulation Nonlinear Dynamics Neurons Markov Chains Humans Neural Networks, Computer
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Passivity of switched recurrent neural networks with time-varying delays.

IEEE transactions on neural networks and learning systems Jan 6, 2015
This paper is concerned with the passivity analysis for switched neural networks subject to stochastic disturbances and time-varying delays. First, using the multiple Lyapunov functions method, a state-dependent switching law is designed to present a...
Neural Networks, Computer Artificial Intelligence Time Factors Mathematical Computing Algorithms Computer Simulation
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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...
Stochastic Processes Humans Neural Networks, Computer Neurons Nerve Net Models, Neurological
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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...
Neural Networks, Computer Algorithms Humans Cluster Analysis Learning Models, Neurological Time Factors Neurons
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