Recurrent neural networks - Scholarpedia

A recurrent neural network (RNN) is any network whose neurons send feedback signals to each other. This concept includes a huge number of possibilities. A number of reviews already exist of some types of RNNs. These include [1], [2], [3], [4]. Typically, these reviews consider RNNs that are artificial neural networks (aRNN) useful in technological applications. To complement these contributions, the present summary focuses on biological recurrent neural networks (bRNN) that are found in the brain. Since feedback is ubiquitous in the brain, this task, in full generality, could include most of the brain's dynamics. The current review divides bRNNS into those in which feedback signals occur in neurons within a single processing layer,  which occurs in networks for such diverse functional roles as storing spatial patterns in short-term memory, winner-take-all decision making, contrast enhancement and normalization, hill climbing, oscillations of multiple types (synchronous, traveling waves

Recurrent neural networks - Scholarpedia Recurrent neural networks From Scholarpedia Stephen Grossberg (2013), Scholarpedia, 8(2):1888. doi:10.4249/scholarpedia.1888 revision #138057 [ link to/cite this article ] Jump to: navigation , search Post-publication activity Curator: Stephen Grossberg Contributors: 1.00 - Trevor Bekolay 0.50 - Nick Orbeck Birgitta Dresp-Langley Baingio Pinna Eugene M. Izhikevich Dr. Stephen Grossberg , Boston University, MA A recurrent neural network (RNN) is any network whose neurons send feedback signals to each other. This concept includes a huge number of possibil

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