verified COP 8,0 · D1 • database Scopus / SJR & Web of Science indexed

United Kingdom · Elsevier Ltd

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Neural Networks

Neural Networks is a journal indexed in SJR in Cognitive Neuroscience and Artificial Intelligence with an H index of 186. It has a COP Index of 8,0 (best band D1). It is published in English. It has a COP Index of 8,0.

Neural Networks focuses its scope in these topics and keywords: neural, learning, networks, network, convolutional, modeling, multiple, development, implementation, algorithmdgcnn, ...

ISSN: 0893-6080

Publisher: Elsevier Ltd

Category: Cognitive Neuroscience

Indexation: verifiedScopus / SJR verifiedWeb of Science

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COP Index trending_up

8,0 D1 Top 10%

5 of 91 journals in Cognitive Neuroscience

H-index · SJR 186 · 1,491

Acceptance rate pie_chart

21% Selective

Source Acceptance_Rate

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Field NPD

Publication cost (APC) payments

NPD Subscription

Non-OA path NPD

Metrics

Scimago and CountryOfPapers database fields

Scopus / SJR Web of Science

COP Index

8,0

D1 Top 10%

SJR Impact

1,491

H-index

186

Docs (year)

739

Docs 3y

1298

Total refs

42095

Cites 3y

10227

Citable 3y

1289

Cites/Doc 2y

7.66

Ref/Doc

56.96

Immediate OA

—

Embargoed OA

NPD

Non OA / Submission

—

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Best articles by citations

A neural network for 500 word vocabulary word spotting using non-uniform units

The POP learning algorithms: reducing work in identifying fuzzy rules

An Efficient EM-based Training Algorithm for Feedforward Neural Networks

Adaptive response organizer network for space-time patterns in low level vision

Adaptive Resonance Theory Microchips: Circuit Design Techniques

Adaptive critic for sigma-pi networks

A What-and-Where fusion neural network for recognition and tracking of multiple radar emitters

A small-size neural network for computing with strange attractors

A remark on 'On stability of nonlinear continuous-time neural networks with delays'

A real-time, unsupervised neural network for the low-level control of a mobile robot in a nonstationary environment

A quantitative study of experimental evaluations of neural network learning algorithms: Current research practice

A New Approach to the Analysis of Multidimensional Neuronal Activity: Markov Random Fields

SHOW MORE ARTICLES

A new algorithm for learning in piecewise-linear neural networks

A connectionist model for convex-hull of a planar set

A neural network classifier with disjunctive fuzzy information

A Neural Algorithm for MAX-2SAT: Performance Analysis and Circuit Implementation

A network of chaotic elements for information processing

A modified fuzzy ARTMAP architecture for the approximation of noisy mappings

A modified back-propagation method to avoid false local minima

A massively parallel resistive network for "weak rod": A double-layer architecture with nearest-neighbor connections

A learning algorithm for oscillatory cellular neural networks

A learning algorithm for applying synthesized stable dynamics to system identification

A global learning algorithm for a RBF network

A flexible multicomputer algorithm for artificial neural networks

FAQs

Neural Networks has a COP Index of 8,0 (D1), ranked 5 of 91 in Cognitive Neuroscience. SJR: 1,491.

Immediate OA APC is not available (NPD).

The acceptance rate recorded for Neural Networks is 21%.

Neural Networks

Metrics

Name good journals. Call out predatory ones.

Researcher reviews

Best articles by citations

FAQs

What is the COP Index of Neural Networks?

What is the APC / publication cost?

What is the acceptance rate?