A novel framework for neural net learning

Intelligent Engineering Systems Through Artificial Neural Networks

Volumn 6, Issue , 1996, Pages 169-174

  Chang, Tsu Shuan ^a   Hwang, Jenq Neng ^b  

^a University of California   (United States)

^b University of Washington   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; EFFICIENCY; ERROR COMPENSATION; IMPROVEMENT; NEURAL NETWORKS; PERFORMANCE;

LEARNING SYSTEMS;

EID: 0030308739     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Article

References (4)

1. Chang, T.S., Abdel-Ghaffar, K. A. S., (1992). A universal neural net with guaranteed convergence to zero system error, IEEE transactions on Signal Processing, 40(12), Dec, 3022-3031.
2. Yu, M., Chang, T.S., (1995). An adaptive step size for backpropagation using linear lower bounding functions, IEEE transactions on Signal Processing, 43 (5), May, 1243-1248.
3. Wang, X., Chang, T.S., (1996). An improved univariate global optimization algorithm with improved linear bounding functions, Journal of Global Optimization, 8, 393-411.
4. Chang, T.S., (1996). A framework of using linear programming for manufacturing scheduling, to appear at Proceedings of the 35th IEEE Conference on Decision and Control, Kobe, Japan, Dec.