Файл:A tutorial on training recurrent neural networks covering BPPT RTRL EKF and the echo state network approach ESNTutorialRev.pdf

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A_tutorial_on_training_recurrent_neural_networks_covering_BPPT_RTRL_EKF_and_the_echo_state_network_approach_ESNTutorialRev.pdf(0 × 0 пикселей, размер файла: 3,09 МБ, MIME-тип: application/pdf)

Herbert Jaeger Fraunhofer Institute for Autonomous Intelligent Systems (AIS) since 2003: International University Bremen First published: Oct. 2002 First revision: Feb. 2004 Second revision: March 2005 Third revision: April 2008 Forth revision: July 2013 Fifth revision: Dec 2013

Abstract:

This tutorial is a worked-out version of a 5-hour course originally held at AIS in September/October 2002. It has two distinct components. First, it contains a mathematically-oriented crash course on traditional training methods for recurrent neural networks, covering back-propagation through time (BPTT), real-time recurrent learning (RTRL), and extended Kalman filtering approaches (EKF). This material is covered in Sections 2 – 5. The remaining sections 1 and 6 – 9 are much more gentle, more detailed, and illustrated with simple examples. They are intended to be useful as a stand-alone tutorial for the echo state network (ESN) approach to recurrent neural network training.

The author apologizes for the poor layout of this document: it was transformed from an html file into a Word file...

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