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 196. It has an SJR impact factor of 3,555 and it has a best quartile of Q1.

Type: Journal

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Publication frecuency: -

Categories: Artificial Intelligence (Q1) Computer Networks and Communications (Q1) Computer Science Applications (Q1) Software (Q1)

Price

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Gold OA

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Green OA

- €

Non OA

Metrics

IEEE Transactions on Neural Networks and Learning Systems

3,555

SJR Impact factor

196

H Index

339

Total Docs (Last Year)

1027

Total Docs (3 years)

13698

Total Refs

11088

Total Cites (3 years)

1016

Citable Docs (3 years)

10,52

Cites/Doc (2 years)

40,41

Ref/Doc

Aims and Scope

Other journals with similar parameters

Journal of Statistical Software Q1
IEEE Transactions on Pattern Analysis and Machine Intelligence Q1
Foundations and Trends in Machine Learning Q1
IEEE Transactions on Cybernetics Q1
International Journal of Computer Vision Q1

Best articles

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

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

A Maximally Split and Relaxed ADMM for Regularized Extreme Learning Machines

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

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

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

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

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

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

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

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

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

SHOW MORE ARTICLES

Artificial Electrical Morris-Lecar Neuron

Autoencoder Constrained Clustering With Adaptive Neighbors

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

Benchmarking Neural Networks For Quantum Computations

Constrained Clustering With Imperfect Oracles

Context Dependent Encoding Using Convolutional Dynamic Networks

Continual Multiview Task Learning via Deep Matrix Factorization

Data Imputation Through the Identification of Local Anomalies

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

Dependent Online Kernel Learning With Constant Number of Random Fourier Features

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

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

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