AIMC Journal:
IEEE transactions on neural networks and learning systems

Showing 491 to 500 of 780 articles

Extended Robust Exponential Stability of Fuzzy Switched Memristive Inertial Neural Networks With Time-Varying Delays on Mode-Dependent Destabilizing Impulsive Control Protocol.

IEEE transactions on neural networks and learning systems Jan 4, 2021
This article investigates the problem of robust exponential stability of fuzzy switched memristive inertial neural networks (FSMINNs) with time-varying delays on mode-dependent destabilizing impulsive control protocol. The memristive model presented ...
Models, Theoretical Computer Simulation Fuzzy Logic Feedback Neural Networks, Computer Algorithms
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A Comprehensive Survey on Graph Neural Networks.

IEEE transactions on neural networks and learning systems Jan 4, 2021
Deep learning has revolutionized many machine learning tasks in recent years, ranging from image classification and video processing to speech recognition and natural language understanding. The data in these tasks are typically represented in the Eu...
Humans Machine Learning Neural Networks, Computer Surveys and Questionnaires Algorithms Data Mining
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Generalized Learning Riemannian Space Quantization: A Case Study on Riemannian Manifold of SPD Matrices.

IEEE transactions on neural networks and learning systems Jan 4, 2021
Learning vector quantization (LVQ) is a simple and efficient classification method, enjoying great popularity. However, in many classification scenarios, such as electroencephalogram (EEG) classification, the input features are represented by symmetr...
Movement Imagination Cues Classification Machine Learning Image Processing, Computer-Assisted Electroencephalography Algorithms Humans Reproducibility of Results Neural Networks, Computer
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Multistability of Fractional-Order Neural Networks With Unbounded Time-Varying Delays.

IEEE transactions on neural networks and learning systems Jan 4, 2021
This article addresses the multistability and attraction of fractional-order neural networks (FONNs) with unbounded time-varying delays. Several sufficient conditions are given to ensure the coexistence of equilibrium points (EPs) of FONNs with conca...
Neural Networks, Computer Algorithms Time Factors Computer Simulation Reproducibility of Results
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Exponential Synchronization of Delayed Memristor-Based Uncertain Complex-Valued Neural Networks for Image Protection.

IEEE transactions on neural networks and learning systems Jan 4, 2021
This article solves the exponential synchronization issue of memristor-based complex-valued neural networks (MCVNNs) with time-varying uncertainties via feedback control. Compared with the traditional control methods, a more practical and general con...
Algorithms Neural Networks, Computer Feedback Computer Security Uncertainty Image Processing, Computer-Assisted
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Global Exponential Synchronization of Coupled Delayed Memristive Neural Networks With Reaction-Diffusion Terms via Distributed Pinning Controls.

IEEE transactions on neural networks and learning systems Jan 4, 2021
This article presents new theoretical results on global exponential synchronization of nonlinear coupled delayed memristive neural networks with reaction-diffusion terms and Dirichlet boundary conditions. First, a state-dependent memristive neural ne...
Diffusion Nonlinear Dynamics Computer Simulation Neural Networks, Computer Feedback Algorithms
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Continual Multiview Task Learning via Deep Matrix Factorization.

IEEE transactions on neural networks and learning systems Jan 4, 2021
The state-of-the-art multitask multiview (MTMV) learning tackles a scenario where multiple tasks are related to each other via multiple shared feature views. However, in many real-world scenarios where a sequence of the multiview task comes, the high...
Models, Theoretical Regression Analysis Machine Learning Algorithms Classification Data Interpretation, Statistical Schools Humans Neural Networks, Computer
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Gradients Cannot Be Tamed: Behind the Impossible Paradox of Blocking Targeted Adversarial Attacks.

IEEE transactions on neural networks and learning systems Jan 4, 2021
Despite their accuracy, neural network-based classifiers are still prone to manipulation through adversarial perturbations. These perturbations are designed to be misclassified by the neural network while being perceptually identical to some valid in...
Neural Networks, Computer Algorithms Classification Reproducibility of Results Pattern Recognition, Automated
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A Neural Network-Based Joint Prognostic Model for Data Fusion and Remaining Useful Life Prediction.

IEEE transactions on neural networks and learning systems Jan 4, 2021
With the rapid development of sensor and information technology, now multisensor data relating to the system degradation process are readily available for condition monitoring and remaining useful life (RUL) prediction. The traditional data fusion an...
Bayes Theorem Algorithms Neural Networks, Computer Linear Models Prognosis Computer Simulation Equipment Failure Reproducibility of Results Models, Statistical
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A Two-Timescale Duplex Neurodynamic Approach to Mixed-Integer Optimization.

IEEE transactions on neural networks and learning systems Jan 4, 2021
This article presents a two-timescale duplex neurodynamic approach to mixed-integer optimization, based on a biconvex optimization problem reformulation with additional bilinear equality or inequality constraints. The proposed approach employs two re...
Computer Simulation Linear Models Neural Networks, Computer Problem Solving Algorithms
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