Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/19615
Title: Efficient learning in neural networks
Authors: Yin, Tong.
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Issue Date: 1998
Abstract: In studies of neural networks, the Multilavered Feedforward Network is the most widely used network architecture while the Backpropagation (BP)algo-rithm is the prime learning algorithm for this kind of networks. Although the BP algorithm is thought to be based on a solid theoretical background, some of its drawbacks hamper its use in solving problems efficiently. These draw-backs include slow convergence, the problem of local minima, and the degra-dation in performance due to practical constraints such as limited weight precision in real implementation of the algorithm.
URI: http://hdl.handle.net/10356/19615
Rights: NANYANG TECHNOLOGICAL UNIVERSITY
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Theses

Files in This Item:
File Description SizeFormat 
YinTong1998.pdf
  Restricted Access
Main report20.86 MBAdobe PDFView/Open

Page view(s) 20

201
checked on Sep 30, 2020

Download(s) 20

5
checked on Sep 30, 2020

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.