A fast noise filtering algorithm for time series prediction using recurrent neural networks

• URL: http://arxiv.org/abs/2007.08063v3
• Date: Tue, 6 Oct 2020 14:53:56 GMT
• Title: A fast noise filtering algorithm for time series prediction using recurrent neural networks
• Authors: Boris Rubinstein
• Abstract summary: We examine the internal dynamics of RNNs and establish a set of conditions required for such behavior. We propose a new approximate algorithm and show that it significantly speeds up the predictive process without loss of accuracy.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recent research demonstrate that prediction of time series by recurrent neural networks (RNNs) based on the noisy input generates a smooth anticipated trajectory. We examine the internal dynamics of RNNs and establish a set of conditions required for such behavior. Based on this analysis we propose a new approximate algorithm and show that it significantly speeds up the predictive process without loss of accuracy.

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