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Randomized Recurrent Neural Networks. [PDF]
, 2018 Neural Networks (NNs) with random weights represent nowadays a topic of consolidated use in the Machine Learning research community. In this contribution we focus in particular on recurrent NN models, which in a randomized setting represent a case of particular interest per se, entailing a number of intriguing research challenges primarily related to ...
Claudio Gallicchio +2 more
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Recurrent neural networks for syllabification
Speech Communication, 1993Abstract An important procedure in many prosodic analysis systems is locating syllables. The location of syllables is used in the identification of stress and of pitch accents, which in turn form the basis for the analysis of rhythm and intonation. This paper presents a novel syllabification system utilising recurrent neural networks which operates ...
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Recurrent Neural Network Architectures
2017In this chapter, we present three different recurrent neural network architectures that we employ for the prediction of real-valued time series. All the models reviewed in this chapter can be trained through the previously discussed backpropagation through time procedure.
Bianchi, Filippo Maria +4 more
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Selective Recurrent Neural Network
Neural Processing Letters, 2012It is known that recurrent neural networks may have difficulties remembering data over long time lags. To overcome this problem, we propose an extended architecture of recurrent neural networks, which is able to deal with long time lags between relevant input signals.
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Recurrent Neural Networks for Edge Intelligence
ACM Computing Surveys, 2022Varsha S Lalapura, J Amudha
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A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks
IEEE Transactions on Neural Networks and Learning Systems, 2014Huaguang Zhang, Zhanshan Wang
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Linking Connectivity, Dynamics, and Computations in Low-Rank Recurrent Neural Networks
Neuron, 2018Srdjan Ostojic +1 more
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Memory analysis for memristors and memristive recurrent neural networks
IEEE/CAA Journal of Automatica Sinica, 2020Zhigang Zeng, Yide Zhang
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Simple framework for constructing functional spiking recurrent neural networks
Proceedings of the National Academy of Sciences of the United States of America, 2019Terrence Sejnowski, , Yinghao Li
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