Guest Editorial Special Issue on Neurodynamic Systems for Optimization and Applications

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

    Результат исследований: Вклад в журналОбзорная статьярецензирование

    5 Цитирования (Scopus)

    Аннотация

    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.

    Язык оригиналаАнглийский
    Номер статьи7384894
    Страницы (с-по)210-213
    Число страниц4
    ЖурналIEEE Transactions on Neural Networks and Learning Systems
    Том27
    Номер выпуска2
    DOI
    СостояниеОпубликовано - февр. 2016

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