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, ...

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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 by citations

Stochastic Stability of Delayed Neural Networks With Local Impulsive Effects

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

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Error Analysis for Matrix Elastic-Net Regularization Algorithms

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

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

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

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Fault Identification in Distributed Sensor Networks Based on Universal Probabilistic Modeling

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Context Dependent Encoding Using Convolutional Dynamic Networks

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

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

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

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Solving Partial Least Squares Regression via Manifold Optimization Approaches

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Extreme Learning Machine With Affine Transformation Inputs in an Activation Function

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Autoencoder Constrained Clustering With Adaptive Neighbors

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

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Domain-Weighted Majority Voting for Crowdsourcing

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Naive Gabor Networks for Hyperspectral Image Classification

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Feedback Solution to Optimal Switching Problems With Switching Cost

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Evolving Deep Neural Networks via Cooperative Coevolution With Backpropagation

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Robust One-Class Kernel Spectral Regression

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Hyperparameter Selection for Gaussian Process One-Class Classification

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Inverting the Generator of a Generative Adversarial Network

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Fast Neuromimetic Object Recognition Using FPGA Outperforms GPU Implementations

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

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