AIMC Journal:
IEEE transactions on neural networks and learning systems

Showing 331 to 340 of 780 articles

Dynamic Learning From Adaptive Neural Control for Discrete-Time Strict-Feedback Systems.

IEEE transactions on neural networks and learning systems Aug 3, 2022
This article first investigates the issue on dynamic learning from adaptive neural network (NN) control of discrete-time strict-feedback nonlinear systems. To verify the exponential convergence of estimated NN weights, an extended stability result is...
Neural Networks, Computer Algorithms Computer Simulation Feedback Nonlinear Dynamics
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Comparative Convolutional Dynamic Multi-Attention Recommendation Model.

IEEE transactions on neural networks and learning systems Aug 3, 2022
Recently, an attention mechanism has been used to help recommender systems grasp user interests more accurately. It focuses on their pivotal interests from a psychology perspective. However, most current studies based on it only focus on part of user...
Neural Networks, Computer Learning
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Fixed-Time Synchronization of Competitive Neural Networks With Multiple Time Scales.

IEEE transactions on neural networks and learning systems Aug 3, 2022
In this brief, we investigate the fixed-time synchronization of competitive neural networks with multiple time scales. These neural networks play an important role in visual processing, pattern recognition, neural computing, and so on. Our main contr...
Neural Networks, Computer Algorithms Computer Simulation Feedback Time Factors
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Sampled-Data Synchronization of Stochastic Markovian Jump Neural Networks With Time-Varying Delay.

IEEE transactions on neural networks and learning systems Aug 3, 2022
In this article, sampled-data synchronization problem for stochastic Markovian jump neural networks (SMJNNs) with time-varying delay under aperiodic sampled-data control is considered. By constructing mode-dependent one-sided loop-based Lyapunov func...
Neural Networks, Computer Algorithms Computer Simulation Markov Chains Stochastic Processes
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Link Prediction Based on Stochastic Information Diffusion.

IEEE transactions on neural networks and learning systems Aug 3, 2022
Link prediction (LP) in networks aims at determining future interactions among elements; it is a critical machine-learning tool in different domains, ranging from genomics to social networks to marketing, especially in e-commerce recommender systems....
Neural Networks, Computer Machine Learning Genomics Diffusion
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Temporal Encoding and Multispike Learning Framework for Efficient Recognition of Visual Patterns.

IEEE transactions on neural networks and learning systems Aug 3, 2022
Biological systems under a parallel and spike-based computation endow individuals with abilities to have prompt and reliable responses to different stimuli. Spiking neural networks (SNNs) have thus been developed to emulate their efficiency and to ex...
Humans Neural Networks, Computer Artificial Intelligence Pattern Recognition, Visual
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Adaptive Neural Network Control for Full-State Constrained Robotic Manipulator With Actuator Saturation and Time-Varying Delays.

IEEE transactions on neural networks and learning systems Aug 3, 2022
This article proposes an adaptive neural network (NN) control method for an n -link constrained robotic manipulator. Driven by actual demands, manipulator and actuator dynamics, state and input constraints, and unknown time-varying delays are taken i...
Neural Networks, Computer Computer Simulation Feedback Robotic Surgical Procedures Nonlinear Dynamics
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Boundary Stabilization of Stochastic Delayed Cohen-Grossberg Neural Networks With Diffusion Terms.

IEEE transactions on neural networks and learning systems Aug 3, 2022
This study considers the boundary stabilization for stochastic delayed Cohen-Grossberg neural networks (SDCGNNs) with diffusion terms by the Lyapunov functional method. In the realization of NNs, sometimes time delays and diffusion phenomenon cannot ...
Neural Networks, Computer Algorithms Time Factors Diffusion
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Scalable Inverse Reinforcement Learning Through Multifidelity Bayesian Optimization.

IEEE transactions on neural networks and learning systems Aug 3, 2022
Data in many practical problems are acquired according to decisions or actions made by users or experts to achieve specific goals. For instance, policies in the mind of biologists during the intervention process in genomics and metagenomics are often...
Neural Networks, Computer Learning Reproducibility of Results Bayes Theorem Reinforcement, Psychology
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Granger Causality Inference in EEG Source Connectivity Analysis: A State-Space Approach.

IEEE transactions on neural networks and learning systems Jul 6, 2022
This article addresses the problem of estimating brain effective connectivity from electroencephalogram (EEG) signals using a Granger causality (GC) characterized on state-space models, extended from the conventional vector autoregressive (VAR) proce...
Humans Neural Networks, Computer Brain Computer Simulation Least-Squares Analysis Electroencephalography
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