Default: IEEE Transactions on Neural Networks and Learning Systems

ISSN: 2162-237X

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IEEE Transactions on Neural Networks and Learning Systems Q1 Unclaimed

IEEE Computational Intelligence Society United States
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IEEE Transactions on Neural Networks and Learning Systems is a journal indexed in SJR in Software and Computer Science Applications with an H index of 212. It has an SJR impact factor of 2,882 and it has a best quartile of Q1. It has an SJR impact factor of 2,882.

IEEE Transactions on Neural Networks and Learning Systems focuses its scope in these topics and keywords: neural, learning, network, data, multiple, classification, human, fmri, extensionimproving, expression, ...

Type: Journal

Type of Copyright:

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Publication frecuency: -

Metrics

IEEE Transactions on Neural Networks and Learning Systems

2,882

SJR Impact factor

212

H Index

609

Total Docs (Last Year)

1117

Total Docs (3 years)

22815

Total Refs

14914

Total Cites (3 years)

1107

Citable Docs (3 years)

12,51

Cites/Doc (2 years)

37,46

Ref/Doc

Aims and Scope


neural, learning, network, data, multiple, classification, human, fmri, extensionimproving, expression, informationclipping, intelligence, label, lassocomputational, learningearly, linear, localization, locally, evolving, dynamic, discretetime, boundaries, camerasieee, cascade, caseneurons, computational, correctionmanifoldbased, cortex, crowdsourced, d, decision, delays, design, detection,


Best articles

3-D Quasi-Recurrent Neural Network for Hyperspectral Image Denoising

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A Constrained Backpropagation Approach for the Adaptive Solution of Partial Differential Equations

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A Maximally Split and Relaxed ADMM for Regularized Extreme Learning Machines

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A Maximum Entropy Framework for Semisupervised and Active Learning With Unknown and Label-Scarce Classes

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A Novel Dual Successive Projection-Based Model-Free Adaptive Control Method and Application to an Autonomous Car

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A Novel Learning Algorithm to Optimize Deep Neural Networks: Evolved Gradient Direction Optimizer (EVGO)

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Adaptive Iterative Learning Control for Linear Systems With Binary-Valued Observations

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Adaptive Learning in Complex Reproducing Kernel Hilbert Spaces Employing Wirtinger's Subgradients

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Adaptive Neural Control of a Kinematically Redundant Exoskeleton Robot Using Brain-Machine Interfaces

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Adaptive Neural Network Finite-Time Control for Multi-Input and Multi-Output Nonlinear Systems With Positive Powers of Odd Rational Numbers

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Adaptive Neural Networks Finite-Time Optimal Control for a Class of Nonlinear Systems

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An Improved TA-SVM Method Without Matrix Inversion and Its Fast Implementation for Nonstationary Datasets

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Artificial Electrical Morris-Lecar Neuron

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Autoencoder Constrained Clustering With Adaptive Neighbors

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Automatic Face Naming by Learning Discriminative Affinity Matrices From Weakly Labeled Images

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Benchmarking Neural Networks For Quantum Computations

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Constrained Clustering With Imperfect Oracles

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Context Dependent Encoding Using Convolutional Dynamic Networks

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Continual Multiview Task Learning via Deep Matrix Factorization

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Data Imputation Through the Identification of Local Anomalies

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Data-Driven Multiagent Systems Consensus Tracking Using Model Free Adaptive Control

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Dependent Online Kernel Learning With Constant Number of Random Fourier Features

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Design of State-Dependent Switching Laws for Stability of Switched Stochastic Neural Networks With Time-Delays

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Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Admissibility and Termination Analysis

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