AIMC Journal:
IEEE transactions on neural networks and learning systems

Showing 341 to 350 of 780 articles

Observer-Based Fixed-Time Neural Control for a Class of Nonlinear Systems.

IEEE transactions on neural networks and learning systems Jul 6, 2022
This article is concerned with an issue of fixed time adaptive neural control for a class of uncertain nonlinear systems subject to hysteresis input and immeasurable states. The state observer and neural networks (NNs) are used to estimate the immeas...
Neural Networks, Computer Computer Simulation Feedback Nonlinear Dynamics Uncertainty
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Efficient Approximation of High-Dimensional Functions With Neural Networks.

IEEE transactions on neural networks and learning systems Jul 6, 2022
In this article, we develop a framework for showing that neural networks can overcome the curse of dimensionality in different high-dimensional approximation problems. Our approach is based on the notion of a catalog network, which is a generalizatio...
Neural Networks, Computer
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Synaptic Scaling-An Artificial Neural Network Regularization Inspired by Nature.

IEEE transactions on neural networks and learning systems Jul 6, 2022
Nature has always inspired the human spirit and scientists frequently developed new methods based on observations from nature. Recent advances in imaging and sensing technology allow fascinating insights into biological neural processes. With the obj...
Humans Neural Networks, Computer Learning
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Explicit Duration Recurrent Networks.

IEEE transactions on neural networks and learning systems Jul 6, 2022
Recurrent neural networks (RNNs) can be used to operate over sequences of vectors and have been successfully applied to a variety of problems. However, it is hard to use RNNs to model the variable dwell time of the hidden state underlying an input se...
Neural Networks, Computer
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Sequence Learning in a Single Trial: A Spiking Neurons Model Based on Hippocampal Circuitry.

IEEE transactions on neural networks and learning systems Jul 6, 2022
In contrast with our everyday experience using brain circuits, it can take a prohibitively long time to train a computational system to produce the correct sequence of outputs in the presence of a series of inputs. This suggests that something import...
Neural Networks, Computer Models, Neurological Action Potentials Neurons Hippocampus
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Spatio-Spectral Feature Representation for Motor Imagery Classification Using Convolutional Neural Networks.

IEEE transactions on neural networks and learning systems Jul 6, 2022
Convolutional neural networks (CNNs) have recently been applied to electroencephalogram (EEG)-based brain-computer interfaces (BCIs). EEG is a noninvasive neuroimaging technique, which can be used to decode user intentions. Because the feature space ...
Humans Neural Networks, Computer Algorithms Electroencephalography Neuroimaging Brain-Computer Interfaces
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Dynamically Weighted Balanced Loss: Class Imbalanced Learning and Confidence Calibration of Deep Neural Networks.

IEEE transactions on neural networks and learning systems Jul 6, 2022
Imbalanced class distribution is an inherent problem in many real-world classification tasks where the minority class is the class of interest. Many conventional statistical and machine learning classification algorithms are subject to frequency bias...
Neural Networks, Computer Machine Learning Algorithms Probability Calibration
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Agglomerative Neural Networks for Multiview Clustering.

IEEE transactions on neural networks and learning systems Jul 6, 2022
Conventional multiview clustering methods seek a view consensus through minimizing the pairwise discrepancy between the consensus and subviews. However, pairwise comparison cannot portray the interview relationship precisely if some of the subviews c...
Neural Networks, Computer Algorithms Cluster Analysis
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Low-Latency In Situ Image Analytics With FPGA-Based Quantized Convolutional Neural Network.

IEEE transactions on neural networks and learning systems Jul 6, 2022
Real-time in situ image analytics impose stringent latency requirements on intelligent neural network inference operations. While conventional software-based implementations on the graphic processing unit (GPU)-accelerated platforms are flexible and ...
Humans Neural Networks, Computer Software Algorithms Leukocytes, Mononuclear Image Processing, Computer-Assisted
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BiCoSS: Toward Large-Scale Cognition Brain With Multigranular Neuromorphic Architecture.

IEEE transactions on neural networks and learning systems Jul 6, 2022
The further exploration of the neural mechanisms underlying the biological activities of the human brain depends on the development of large-scale spiking neural networks (SNNs) with different categories at different levels, as well as the correspond...
Humans Neural Networks, Computer Brain Cognition Neurons
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