Title :
An incremental network construction algorithm for approximating discontinuous functions
Author :
Lee, Hyukjoon ; Mehrotra, Kishan ; Mohan, Chilukuri K. ; Ranka, Sanjay
Author_Institution :
Sch. of Comput. & Inf. Sci., Syracuse Univ., NY, USA
fDate :
27 Jun-2 Jul 1994
Abstract :
Traditional neural network training techniques do not work well on problems with many discontinuities, such as those that arise in multicomputer communication cost modeling. We develop a new algorithm to solve this problem. This algorithm incrementally adds modules to the network, successively expanding the `window´ in the data space where the current module works well. The need for a new module is automatically recognized by the system. This algorithm performs very well on problems with many discontinuities, and requires fewer computations than traditional backpropagation
Keywords :
approximation theory; feedforward neural nets; function approximation; functional analysis; learning (artificial intelligence); attentive modular construction and training algorithm; data space; discontinuous function approximation; incremental network construction algorithm; learning algorithm; modules; neural network; Approximation algorithms; Backpropagation algorithms; Computational Intelligence Society; Computer networks; Cost function; Feedforward neural networks; Information science; Multi-layer neural network; Neural networks; Surface reconstruction;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374556
