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.
|Number of pages||4|
|Journal||IEEE Transactions on Neural Networks and Learning Systems|
|Publication status||Published - Feb 2016|