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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: -

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

Price

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NPD

Embargoed OA

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Non OA

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

Other journals with similar parameters

Journal of Statistical Software Q1
Foundations and Trends in Machine Learning Q1
IEEE Transactions on Pattern Analysis and Machine Intelligence Q1
IEEE Transactions on Evolutionary Computation Q1
IEEE Transactions on Cybernetics Q1

Compare this journals

Aims and Scope

Best articles by citations

Stochastic Stability of Delayed Neural Networks With Local Impulsive Effects

Singularities of Three-Layered Complex-Valued Neural Networks With Split Activation Function

Error Analysis for Matrix Elastic-Net Regularization Algorithms

Selection and Optimization of Temporal Spike Encoding Methods for Spiking Neural Networks

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

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

Fault Identification in Distributed Sensor Networks Based on Universal Probabilistic Modeling

Context Dependent Encoding Using Convolutional Dynamic Networks

Greedy Methods, Randomization Approaches, and Multiarm Bandit Algorithms for Efficient Sparsity-Constrained Optimization

First-Spike-Based Visual Categorization Using Reward-Modulated STDP

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

Solving Partial Least Squares Regression via Manifold Optimization Approaches

SHOW MORE ARTICLES

Extreme Learning Machine With Affine Transformation Inputs in an Activation Function

Autoencoder Constrained Clustering With Adaptive Neighbors

Improving the Quality of Self-Organizing Maps by Self-Intersection Avoidance

Domain-Weighted Majority Voting for Crowdsourcing

Naive Gabor Networks for Hyperspectral Image Classification

Feedback Solution to Optimal Switching Problems With Switching Cost

Evolving Deep Neural Networks via Cooperative Coevolution With Backpropagation

Robust One-Class Kernel Spectral Regression

Hyperparameter Selection for Gaussian Process One-Class Classification

Inverting the Generator of a Generative Adversarial Network

Fast Neuromimetic Object Recognition Using FPGA Outperforms GPU Implementations

Diverse Instance-Weighting Ensemble Based on Region Drift Disagreement for Concept Drift Adaptation

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