Comments on "Backpropagation Algorithms for a Broad Class of Dynamic Networks"
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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.
[1] Christian Endisch,et al. Optimal Brain Surgeon for General Dynamic Neural Networks , 2007, EPIA Workshops.
[2] Martin T. Hagan,et al. Backpropagation Algorithms for a Broad Class of Dynamic Networks , 2007, IEEE Transactions on Neural Networks.