Abstract
The generality of the artificial neural networks models infers the requests based in the totality of the characteristics of the patterns. The RHI model infers just with a limited set of this characteristics, the significant fragment. This reason make RHI really appropriated by resolution of control and active vision problem. Although RHI model present high sensibility to distortion. In this paper it is developed the formalism to obtain the significant fragment in such a way it improve the noise tolerance.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
García-Chamizo, J.M.;Crespo Lorente,A. “Redes Neuronales Heteroasociativas Increméntales”. IFIP Congress’92, Septiembre 1992
García-Chamizo, J.M.; Crespo-Lorente, A.; Rizo Aldeguer,R.. “Extracción de fragmentos significativos de patrones para su posterior reconocimiento mediante Redes Neuronales RHI”. Jornadas sobre Redes Neuronales 26–30 Octubre 1992. Centro Nacional de Microelectrónica (CSIC). Instituto de Neurociencias (UA).
García-Chamizo, J.M.; Crespo-Lorente, A.; Rizo-Aldeguer, R. “Output Pattern Recalling Aided By Themselves: Incremental Heteroassociative Networks”. Proceedings of the IJCNN, Beijing, November 1992
García-Chamizo. “Semicoberturas heterogéneas de regiones bidimensionales morfológicamente no restringidas. Modelado conexionista aplicado”. Doctoral Dissertation, February, 1994
Garcia Chamizo, J.M.; Mora Pascual, J.; Rizo Aldeguer, R.; Ledesma Latorre, B. “An incidence angle detection system for automatic assembly tools using the RHI network model”. IEEE IAS International Conference on Industrial Automation and Control, Hyderabad (India ), 1995.
Grossberg, S. (editor). “The Adaptive Brain”. Elsevier Science Publishing Co., Inc, 1987
Ibarra Pico, F; Garcia Chamizo, J.M. “A Generalized Bidirectional Associative Memory with a Hidden Orthogonal Layer”. ICANN’94, Sorrento, May 1994
Kandel, E. R.; Schwart, J. H. “Principles of Neural Science”. Elsevier Science Publishing Co., Inc., 1985.
Kohomen, T. “Self-Organization and Associative Memory”. Springer-Verlag, 2nd. edition, 1988
Kosko, B. “Adaptive Bidirectional Associative Memories”. Applied Optics, vol 26, n 23, Dec. 1987
Kosko, B. “Bidirectional Associative Memories ”. IEEE Transactions on Systems, Man & Cybernetics, vol 18, n1, Jan./Feb. 1988
Lancaster, P. & Tismenetsky, M. “The Theory of Matrices”. Academic Press, 1985
Pao, Y. “Adaptive Pattern Recognition and Neural Networks”. Addison-Wesley Publishing Company, Inc, 1989
Torregrosa, V. “Modelo Neuronal de Memoria Asociativa Ortonomalizada Adaptativa”. P.F.C. U.P.V., 1993
W. Thomas Miller,III;Richard S.Sutton; Paul I. Werbos. “Neural Networks For Control”. Institute of Technology. Massachusetts, 1990
Zurada, J.M. “Introduction to Artificial Neural Systems”. West Publishing Company, 1992
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1995 Springer-Verlag/Wien
About this paper
Cite this paper
García Chamizo, J.M., Satorre Cuerda, R., Ibarra Picó, F., Cuenca Asensi, S. (1995). Selecting the Best Significant Fragment to the Incremental Heteroassociative Neural Network (RHI). In: Artificial Neural Nets and Genetic Algorithms. Springer, Vienna. https://doi.org/10.1007/978-3-7091-7535-4_49
Download citation
DOI: https://doi.org/10.1007/978-3-7091-7535-4_49
Publisher Name: Springer, Vienna
Print ISBN: 978-3-211-82692-8
Online ISBN: 978-3-7091-7535-4
eBook Packages: Springer Book Archive