Aug 16, 2016 - Maintainer Frauke Guenther. Depends R (>= 2.9.0). Imports grid, MASS, grDevices, stats, utils. Description Training of neural networks using backpropagation, resilient backpropagation with (Riedmiller, 1994) or without weight backtracking (Riedmiller and Braun, 1993) or the.

README.md Backpropagation-C Designer: Junbo Zhao, Wuhan University, Working in Tsinghua National lab of intelligent images and documents processing. Rompe Claves Wifi Para Psp. Letro Automatic Filler Owners Manual here. Email: +5683 Introduction: This package implements the famous backpropagation algorithm.

You can use it when training a Neural Network, or an Autoencoder. Relationship with Deep Learning Likewise, you can increase the number of layers to implement a deeper structure, to follow the trend of 'Deep Learning'. But bear in mind that DL has lots of beautiful tricks, and merely making it deeper will not yield good results!! Important I just write bp.cpp as an example. In practice, you should use your own training data and reset the macros. Also you could modify it by simply repeating some main steps, if you want to increase the number of layers.