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S&T Best Computing Projects
An improved resilient propagation algorithm by introducing deterministic weight modification and magnified gradient function
/sw/zh-hans/islandora/object/stcompfyp%3A113/datastream/OBJ/view
作品集
S&T Best Computing Projects
细节
识别号
stcompfyp:113
题名
An improved resilient propagation algorithm by introducing deterministic weight modification and magnified gradient function
作品类型
Final Year Project/Work
系列 / 集 / 库
S&T Best Computing Projects
创建者
Fung, Alan 馮子鍵 (creator)
Ng, Sin Chun Vanessa 吳倩珍 (supervisor)
学院 / 部门
School of Science and Technology (S&T)
课程
Bachelor of Computing with Honours in Computing
日期
2010
摘要
The aim of project is to improve an existing training algorithm on feed-forward neural network. This algorithm will base on Resilient Propagation (RPROP) and try to improve the global convergence capability and speed up the convergence rate.
资料类型
PDF
语言
English
资料描述
5 pages.
关键词
neural networks; algorithms; Resilient propagation (Rprop); Deterministic weight modification (DWM); Backpropagation (BP) with magnified gradient function (MGFProp); Magnified gradient function (MGF)
存取限制
Public Access
固定连结
https://repository.lib.hkmu.edu.hk/sw/islandora/object/stcompfyp:113
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