Guest Editorial Special Issue on Neurodynamic Systems for Optimization and Applications

Zhigang Zeng, Andrzej Cichocki, Long Cheng, Youshen Xia, Xiaolin Hu

    Research output: Contribution to journalReview articlepeer-review

    5 Citations (Scopus)

    Abstract

    Recurrent neural networks, as neurodynamic systems, are a class of connectionist models that capture the dynamics of sequences via cycles in artificial neurons. Since the invention of Hopfield neural network, recurrent neural networks have attracted considerable attention, which marks the beginning of the modern age of neural network studies. Thanks to their inherent nature of parallel and distributed information processing, many computationally intensive applications can be solved by recurrent neural networks in the real-Time environment.

    Original languageEnglish
    Article number7384894
    Pages (from-to)210-213
    Number of pages4
    JournalIEEE Transactions on Neural Networks and Learning Systems
    Volume27
    Issue number2
    DOIs
    Publication statusPublished - Feb 2016

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