Literature DB >> 19211353

Comments on "Backpropagation algorithms for a broad class of dynamic networks".

Christian Endisch1, Peter Stolze, Christoph Hackl, Dierk Schroder.   

Abstract

In a recent paper, De Jesús proposed a general framework for describing dynamic neural networks. Gradient and Jacobian calculations were discussed based on backpropagation-through-time (BPTT) algorithm and real-time recurrent learning (RTRL). Some errors in the paper of De Jesús bring difficulties for other researchers who want to implement the algorithms. This comments paper shows the critical parts of the publication and gives errata to facilitate understanding and implementation.

Mesh:

Year:  2009        PMID: 19211353     DOI: 10.1109/TNN.2009.2013243

Source DB:  PubMed          Journal:  IEEE Trans Neural Netw        ISSN: 1045-9227


  1 in total

1.  A Novel Recurrent Neural Network-Based Ultra-Fast, Robust, and Scalable Solver for Inverting a "Time-Varying Matrix".

Authors:  Vahid Tavakkoli; Jean Chamberlain Chedjou; Kyandoghere Kyamakya
Journal:  Sensors (Basel)       Date:  2019-09-16       Impact factor: 3.576

  1 in total

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