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Cheng-Yuan Liou, Jau-Chi Huang and Yen-Ting Kuo
Department of Computer Science and Information Engineering
National Taiwan University
Taipei, 106 Taiwan
E-mail: cyliou@csie.ntu.edu.tw
This paper constructs a geometrical perspective to justify the slow learning period
and fast learning period during training. It plots the error surfaces and the solution spaces
in the input space for a single neuron with two inputs. It records various training paths in
this space using the back-propagation (BP) training algorithm [6]. It finds the relations
between the learning curve and training path.
Received August 28, 2003; revised May 14, 2004; accepted January 6, 2005.
Communicated by Chin-Teng Lin.
*This paper was supported in part by the National Science Council of Taiwan, R.O.C., under project NSC
93-2213-E-002-081.