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IEEE Transactions on Neural Networks Template

Write in a clean editor, then format for IEEE Transactions on Neural Networks in one click — DocuGuru applies the official IEEE template with numbered references and exports a submission-ready PDF plus the editable LaTeX source. Free to start.

About the IEEE Transactions on Neural Networks format

IEEE Transactions on Neural Networks is a peer-reviewed journal published by IEEE, covering Neural Networks and Applications, Face and Expression Recognition, Blind Source Separation Techniques.

PublisherIEEE
Reference styleNumbered (IEEE)
Numbered — [1], [2] in the text
[1] A. Smith, B. Jones, and C. Lee, "A representative article title," IEEE Transactions on Neural Networks, vol. 12, no. 3, pp. 45–58, 2023.

Formats any DOI in IEEE Transactions on Neural Networks style. No sign-up.

Publishes research inNeural Networks and Applications Face and Expression Recognition Blind Source Separation Techniques Advanced Memory and Neural Computing Fuzzy Logic and Control Systems
ISSN1045-9227
h-index266
i10-index2,841
Total citations469,139
Top institutions publishing hereNanyang Technological University
Journal websiteieeexplore.ieee.org
You getA submission-ready PDF and the editable LaTeX source — ready to submit.

Papers published in IEEE Transactions on Neural Networks per year

217
2007
273
2008
243
2009
251
2010
262
2011
2
2012
1
2013
25
2016
69
2017
2
2018
1
2021
1
2023

Citation impact of IEEE Transactions on Neural Networks by publication year

13.1K
2007
25.3K
2008
17.3K
2009
17.6K
2010
19K
2011
0
2012
4
2013
1
2016
0
2017
7
2018
0
2021
275
2023

Citations each year’s papers have accumulated so far — the most recent years are still building up.

Most-cited papers in IEEE Transactions on Neural Networks

Reinforcement Learning: An Introduction

Sutton, Richard S, Barto, Andrew G · 1 Jan 2005

An account of key ideas and algorithms in reinforcement learning. The discussion ranges from the history of the field's intellectual foundations to recent developments and applications. Areas studied include reinforcement learning problems in terms of Markov decision problems and solution methods.

25,794 citations Cite SaveGo to paper →
The Graph Neural Network Model

Franco Scarselli, M. Gori, Ah Chung Tsoi et al. · 10 Dec 2008

Many underlying relationships among data in several areas of science and engineering, e.g., computer vision, molecular chemistry, molecular biology, pattern recognition, and data mining, can be represented in terms of graphs. In this paper, we propose a new neural network model, called graph neural network (GNN) model, that extends existing neural network methods for processing…

9,439 citations Cite SaveGo to paper →
Learning long-term dependencies with gradient descent is difficult

Yoshua Bengio, P. Simard, Paolo Frasconi · 1 Mar 1994

Recurrent neural networks can be used to map input sequences to output sequences, such as for recognition, production or prediction problems. However, practical difficulties have been reported in training recurrent neural networks to perform tasks in which the temporal contingencies present in the input/output sequences span long intervals. We show why gradient based learning algorithms…

8,514 citations Cite SaveGo to paper →
Identification and control of dynamical systems using neural networks

Kumpati S. Narendra, K. Parthasarathy · 1 Mar 1990

It is demonstrated that neural networks can be used effectively for the identification and control of nonlinear dynamical systems. The emphasis is on models for both identification and control. Static and dynamic backpropagation methods for the adjustment of parameters are discussed. In the models that are introduced, multilayer and recurrent networks are interconnected in novel…

8,018 citations Cite SaveGo to paper →

IEEE Transactions on Neural Networks template — frequently asked questions

How do I write a paper in the IEEE Transactions on Neural Networks format?
In DocuGuru you write your manuscript in a normal editor — no LaTeX setup required — and select the IEEE Transactions on Neural Networks template. When you export, DocuGuru compiles the paper into the official IEEE format and hands you a submission-ready PDF along with the editable LaTeX source.
What reference style does IEEE Transactions on Neural Networks use?
IEEE Transactions on Neural Networks uses Numbered (IEEE) references, shown as numbered [1], [2] markers in the text. DocuGuru formats every in-text citation and the reference list in this exact style automatically. A reference appears like this: [1] A. Smith, B. Jones, and C. Lee, "A representative article title," IEEE Transactions on Neural Networks, vol. 12, no. 3, pp. 45–58, 2023.
Do I need to know LaTeX to submit to IEEE Transactions on Neural Networks?
No. DocuGuru generates the IEEEtran LaTeX class and compiles the PDF for you in the background, so you get a IEEE-ready IEEE Transactions on Neural Networks document without writing any LaTeX. If you do want it, the LaTeX source is included in the export.
Can I import an existing draft into the IEEE Transactions on Neural Networks template?
Yes. Paste or upload your current manuscript — Word, LaTeX, Markdown, or plain text — and DocuGuru reflows it into the IEEE Transactions on Neural Networks format with correct headings, figures, tables, and numbered citations.
Who publishes IEEE Transactions on Neural Networks?
IEEE Transactions on Neural Networks is a engineering and computer science journal published by IEEE. DocuGuru's IEEE Transactions on Neural Networks template matches IEEE's official submission format.
Can I export a submission-ready IEEE Transactions on Neural Networks PDF?
Yes — DocuGuru produces a PDF built with the official IEEE Transactions on Neural Networks template (the IEEEtran class) that is ready to submit to IEEE, together with the matching LaTeX source files.
How much does the IEEE Transactions on Neural Networks template cost?
You can start writing in the IEEE Transactions on Neural Networks template for free. Exporting the final submission-ready IEEE Transactions on Neural Networks PDF and LaTeX source is part of DocuGuru's paid plans — see the app for current pricing.
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