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Neurocomputing publishes articles describing recent fundamental contributions in the field of neurocomputing. Neurocomputing theory, practice and applications are the essential topics being covered. NEW! Neurocomputing's Software Track allows you to expose your complete Software work to the community through a novel Publication format: the Original Software Publication Overview: Neurocomputing welcomes theoretical contributions aimed at winning further understanding of neural networks and learning systems, including, but not restricted to, architectures, learning methods, analysis of network dynamics, theories of learning, self-organization, biological neural network modelling, sensorimotor transformations and interdisciplinary topics with artificial intelligence, artificial life, cognitive science, computational learning theory, fuzzy logic, genetic algorithms, information theory, machine learning, neurobiology and pattern recognition. Neurocomputing covers practical aspects with contributions on advances in hardware and software development environments for neurocomputing, including, but not restricted to, simulation software environments, emulation hardware architectures, models of concurrent computation, neurocomputers, and neurochips (digital, analog, optical, and biodevices). Neurocomputing reports on applications in different fields, including, but not restricted to, signal processing, speech processing, image processing, computer vision, control, robotics, optimization, scheduling, resource allocation and financial forecasting. Types of publications: Neurocomputing publishes reviews of literature about neurocomputing and affine fields. Neurocomputing reports on meetings, including, but not restricted to, conferences, workshops and seminars. NEW! The Neurocomputing Software Track Neurocomputing Software Track publishes a new format, the Original Software Publication (OSP) to disseminate exiting and useful software in the areas of neural networks and learning systems, including, but not restricted to, architectures, learning methods, analysis of network dynamics, theories of learning, self-organization, biological neural network modelling, sensorimotor transformations and interdisciplinary topics with artificial intelligence, artificial life, cognitive science, computational learning theory, fuzzy logic, genetic algorithms, information theory, machine learning, neurobiology and pattern recognition. We encourage high-quality original software submissions which contain non-trivial contributions in the above areas related to the implementations of algorithms, toolboxes, and real systems. The software must adhere to a recognized legal license, such as OSI approved licenses. Importantly, the software will be a full peer reviewed publication that is able to capture your software updates once they are released. To fully acknowledge the author's/developers work your software will be fully citable as an Original Software Publication, archived and indexed and available as a complete online "body of work" for other researchers and practitioners to discover. See the detailed Submission instructions, and more information about the process for academically publishing your Software: here
Publishing Model：
ISSN：0925-2312
|EISSN：1872-8286
|Publication Frequency：Twice monthly
|Last updated on 01 Jun 2026 / Current volume： 炆躭蔡 / Current issue：
More Details
Automation Technology
Computer Science
Impact Factor
Journal Impact Factor(JIF) 2024
炆.逦
Journal Citation Indicator(JCI) 2024
声.蔡声
Web of Science Rank 2024:
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# 杚篫/缗蔡鋺
82.11%
Q1
CiteScore Metrics
CiteScore 2024
声杚.炆
=
炆䟕篫䟕篫 Citation （2022-2024）
逦声杚篫 Article （2022-2024）
CiteScore Rank 2024
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# 逦/声缗声
95.87%
Q1
。肃陱卖憗锆蠹㥌 偌桧嚷蠹鵃桧蠹 嵻卖卖⻊嚷桧囹锆嚷肃鵃详
# 炆鋺/䟕鋺篫
93.24%
Q1
嵻㥌锆嚷鯉嚷桧嚷囹⻊ 喊鵃锆蠹⻊⻊嚷茡蠹鵃桧蠹
# 鋺篫/鋺逦蔡
89.56%
Q1
