@inproceedings{Mitsukura2000,
  _titleaddon = {July 24---27, 2000},
  _venue = {Come, Italy},
  _volume = {5},
  abstract = {In this paper, we propose a method to design a neural network (NN)
	by using a genetic algorithm (GA) and simulated annealing (SA). And
	also, in order to demonstrate the effectiveness of the proposed scheme,
	we apply the proposed scheme to a coin recognition example. In general,
	as a problem becomes complex and large-scale, the number of operations
	increases and hardware implementation to real systems (coin recognition
	machines) using NNs becomes difficult. Therefore, we propose the
	method which makes a small-sized NN system to achieve a cost reduction
	and to simplify hardware implementation to the real machines. The
	coin images used in this paper were taken by a cheap scanner. Then
	they are not perfect, but a part of the coin image could be used
	in computer simulations. Input signals, which are Fourier spectra,
	are learned by a three-layered NN. The inputs to NN are selected
	by using GA with SA to make a small-sized NN. Simulation results
	show that the proposed scheme is effective to find a small number
	of input signals for coin recognition},
  added-at = {2011-03-27T19:35:34.000+0200},
  affiliation = {University of Tokushima, Faculty of Engineering, Department of Information
	Science and Intelligent Systems},
  author = {Mitsukura, Y. and Fukumi, Minoru and Akamatsu, Norio},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  biburl = {https://www.bibsonomy.org/bibtex/217ec0ff9096fd57ad4f5cf8296ea027e/cocus},
  booktitle = {Proceedings of the IEEE-INNS-ENNS International Joint Conference
	on Neural Networks, IJCNN 2000, Neural Computing: New Challenges
	and Perspectives for the New Millennium, Como, Italy, July 24--27,
	2000, Volume 5},
  doi = {10.1109/IJCNN.2000.861454},
  file = {:./mitsukura2000_00861454.pdf:PDF},
  interhash = {0ebc48f23aae6bf9c10d57c5d7647c88},
  intrahash = {17ec0ff9096fd57ad4f5cf8296ea027e},
  keywords = {NNs, SA, algorithms, annealing annealingGA, coin genetic input nets, networks, neural object real recognition, signals, simulated systems,},
  loacation = {#ieeeaddr#},
  owner = {CK},
  pages = {178-183 vol.5},
  publisher = {{IEEE} Computer Society},
  timestamp = {2011-03-27T19:35:41.000+0200},
  title = {Design and evaluation of neural networks for coin recognition by
	using GA and SA},
  url = {http://www.conferences.hu/budapest2004/},
  urldate = {1-25-2008},
  volume = 5,
  volumes = {6},
  xcrossref = {CK:conf/ijcnn/2000e},
  year = 2000
}