Neural Networks

杂志介绍

Neural Networks杂志介绍

《Neural Networks》是一本以English为主的未开放获取国际优秀期刊，中文名称神经网络，本刊主要出版、报道计算机科学-COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCIE收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为6，最新CiteScore 指数为13.9。

本刊近期中国学者发表的论文主要有：

• Lifelong learning with Shared and Private Latent Representations learned through synaptic intelligence

  Author: Yang, Yang; Huang, Jie; Hu, Dexiu

• Collaborative-guided spectral abundance learning with bilinear mixing model for hyperspectral subpixel target detection

  Author: Zhu, Dehui; Du, Bo; Hu, Meiqi; Dong, Yanni; Zhang, Liangpei

• Unsupervised graph-level representation learning with hierarchical contrasts

  Author: Ju, Wei; Gu, Yiyang; Luo, Xiao; Wang, Yifan; Yuan, Haochen; Zhong, Huasong; Zhang, Ming

• Monte Carlo Ensemble Neural Network for the diagnosis of Alzheimer's disease

  Author: Liu, Chaoqiang; Huang, Fei; Qiu, Anqi

英文介绍

Neural Networks杂志英文介绍

Neural Networks is the archival journal of the world's three oldest neural modeling societies: the International Neural Network Society (INNS), the European Neural Network Society (ENNS), and the Japanese Neural Network Society (JNNS). A subscription to the journal is included with membership in each of these societies.

Neural Networks provides a forum for developing and nurturing an international community of scholars and practitioners who are interested in all aspects of neural networks and related approaches to computational intelligence. Neural Networks welcomes high quality submissions that contribute to the full range of neural networks research, from behavioral and brain modeling, learning algorithms, through mathematical and computational analyses, to engineering and technological applications of systems that significantly use neural network concepts and techniques. This uniquely broad range facilitates the cross-fertilization of ideas between biological and technological studies, and helps to foster the development of the interdisciplinary community that is interested in biologically-inspired computational intelligence. Accordingly, Neural Networks editorial board represents experts in fields including psychology, neurobiology, computer science, engineering, mathematics, and physics. The journal publishes articles, letters and reviews, as well as letters to the editor, editorials, current events, software surveys, and patent information. Articles are published in one of five sections: Cognitive Science, Neuroscience, Learning Systems, Mathematical and Computational Analysis, Engineering and Applications.