AIMC Journal:
IEEE transactions on neural networks and learning systems

Showing 181 to 190 of 780 articles

Deep Reinforcement Learning on Autonomous Driving Policy With Auxiliary Critic Network.

IEEE transactions on neural networks and learning systems Jul 6, 2023
Deep reinforcement learning (DRL) is a machine learning method based on rewards, which can be extended to solve some complex and realistic decision-making problems. Autonomous driving needs to deal with a variety of complex and changeable traffic sce...
Neural Networks, Computer Machine Learning Policy Reward Reinforcement, Psychology
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Data-Driven H Optimal Output Feedback Control for Linear Discrete-Time Systems Based on Off-Policy Q-Learning.

IEEE transactions on neural networks and learning systems Jul 6, 2023
This article develops two novel output feedback (OPFB) Q -learning algorithms, on-policy Q -learning and off-policy Q -learning, to solve H static OPFB control problem of linear discrete-time (DT) systems. The primary contribution of the proposed alg...
Neural Networks, Computer Algorithms Computer Simulation Feedback Nonlinear Dynamics
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Hessian-Aided Random Perturbation (HARP) Using Noisy Zeroth-Order Oracles.

IEEE transactions on neural networks and learning systems Jul 6, 2023
In stochastic optimization problems where only noisy zeroth-order (ZO) oracles are available, the Kiefer-Wolfowitz algorithm and its randomized counterparts are widely used as gradient estimators. Existing algorithms generate the random perturbations...
Neural Networks, Computer Algorithms Noise
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Local Stability and Convergence Analysis of Neural Network Controllers With Error Integral Inputs.

IEEE transactions on neural networks and learning systems Jul 6, 2023
This article investigates the local stability and local convergence of a class of neural network (NN) controllers with error integrals as inputs for reference tracking. It is formally proved that if the input of the NN controller consists exclusively...
Neural Networks, Computer Algorithms Computer Simulation Feedback Nonlinear Dynamics
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Relaxed Exponential Stabilization for Coupled Memristive Neural Networks With Connection Fault and Multiple Delays via Optimized Elastic Event-Triggered Mechanism.

IEEE transactions on neural networks and learning systems Jul 6, 2023
This article investigates the problem of relaxed exponential stabilization for coupled memristive neural networks (CMNNs) with connection fault and multiple delays via an optimized elastic event-triggered mechanism (OEEM). The connection fault of the...
Neural Networks, Computer Time Factors
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An Improved Finite-Time and Fixed-Time Stable Synchronization of Coupled Discontinuous Neural Networks.

IEEE transactions on neural networks and learning systems Jul 6, 2023
This article focuses on the finite-time and fixed-time synchronization of a class of coupled discontinuous neural networks, which can be viewed as a combination of the Hindmarsh-Rose model and the Kuramoto model. To this end, under the framework of F...
Neural Networks, Computer Algorithms Time Factors
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Direct-Optimization-Based DC Dictionary Learning With the MCP Regularizer.

IEEE transactions on neural networks and learning systems Jul 6, 2023
Direct-optimization-based dictionary learning has attracted increasing attention for improving computational efficiency. However, the existing direct optimization scheme can only be applied to limited dictionary learning problems, and it remains an o...
Neural Networks, Computer Algorithms
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Attribute Augmented Network Embedding Based on Generative Adversarial Nets.

IEEE transactions on neural networks and learning systems Jul 6, 2023
Network embedding is to learn low-dimensional representations of nodes while preserving necessary information for network analysis tasks. Though representations preserving both structure and attribute features have achieved in many real-world applica...
Neural Networks, Computer Algorithms Learning
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Looking at Boundary: Siamese Densely Cooperative Fusion for Salient Object Detection.

IEEE transactions on neural networks and learning systems Jul 6, 2023
Though deep learning-based saliency detection methods have achieved gratifying performance recently, the predicted saliency maps still suffer from the boundary challenge. From the perspective of foreground-background separation, this article attempts...
Neural Networks, Computer Learning Benchmarking
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TRUST-TECH-Based Systematic Search for Multiple Local Optima in Deep Neural Nets.

IEEE transactions on neural networks and learning systems Jul 6, 2023
Training deep neural networks (DNNs) rested heavily on efficient local solvers. Due to their local property, local solvers are sensitive to initialization and hyperparameters. In this article, a systematical method for finding multiple high-quality l...
Neural Networks, Computer Algorithms
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