Abstract
In this paper we describe the development of Fuzzy Response Integrators of Modular Neural Networks (MNN) for Face, Fingerprint and Voice Recognition, and their Optimization with a Hierarchical Genetic Algorithm (HGA). The optimization of the integrators consists of optimizing their membership functions, fuzzy rules, type of model (Mamdani or Sugeno), type of fuzzy logic (type-1 or type-2). The MNN architecture consists of three modules; face, fingerprint and voice. Each of the modules is divided again into three sub modules. The same information is used as input to train the sub modules. Once we have trained and tested the MNN modules, we proceed to integrate these modules with an optimized fuzzy integrator. In this paper we show that using a HGA as an optimization technique for the fuzzy integrators is a good option to solve MNN integration problems.
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References
Artificial neural networks fundamentals, models and applications, http://www.monografias.com/trabajos12/redneur/redneur.shtml (December 2008)
Connectionist systems, http://carpanta.dc.fi.udc.es/~cipenedo/cursos/scx/archivospdf/Tema1-0.pdf (December 2008)
Artificial neural networks, http://es.wikipedia.org/wiki/Red_neuronal_artificial (December 2008)
Baldwin, C., Clark, K.: Design Rules, The Power of Modularity, vol. 1. MIT Press, Cambridge (2000)
Kuri, F.: Neural Networks and Genetic Algorithms. PDF document, http://www.inele.ufro.cl/apuntes/Tutores_Inteligentes/RNSyAGS.pdf
Jang, J.S.R., Sun, C.T., Mizutani, E.: Neuro-Fuzzy and Soft Computing. Prentice Hall, New Jersey (1997)
Rodriguez, M.: Optimization of DNA genotyping as a problem of selection of features, thesis, Americas University of Puebla, Puebla Mexico (2005)
Golberg, D.: Genetic Algorithms in search, optimization and machine learning. Addison Wesley, USA (1989)
Alvarado, J.M.: Recognition of the person through his face and fingerprint using modular neural networks and wavelet transform, thesis, Tijuana Institute of Technology, Tijuana Mexico (2006)
Ramos, J.: Neural networks applied to speaker identification by voice using feature extraction, thesis, Tijuana Institute of Technology, Tijuana México (2006)
Hidalgo, D., Castillo, O., Melin, P.: Type-1 and type-2 fuzzy inference systems as integration methods in modular neural networks for multimodal biometry and its optimization with genetic algorithms, thesis, Tijuana Institute of Technology, Tijuana México (2009)
Ripley, B.D.: Pattern Recognition and Neural Networks. Cambridge University Press, Oxford (1996)
Morales, G.: Introduction to Fuzzy Logic, Research center and Advanced studies of the IPN, http://delta.cs.cinvestav.mx/~gmorales/ldifll/node1.html
Castro, J.R.: Tutorial Type-2 Fuzzy Logic: Theory and Applications. UABC University and Tijuana Institute of Technology, Tijuana México (2006)
Fuzzy Logic: Introduction and basic concepts, http://members.tripod.com/jesus_alfonso_lopez/FuzzyIntro2.html (January 2009)
Cristea, M., Dinu, A., McCormick, M., Ghee, J.: Neural and Fuzzy Logic Control of Drives and Power Systems. Elsevier, Oxford (2002)
Genetic Algorithms, http://es.wikipedia.org/wiki/Algoritmo_gen%C3%A9tico (December 2008)
Langari, R.: A Framework for analysis and synthesis of fuzzy linguistic control systems, Ph.D. thesis, University of California, Berkeley (1990)
Alvarado, J.M.: Recognition of the person through his face and fingerprint using modular neural networks and wavelet transform, thesis, Tijuana Institute of Technology, Tijuana Mexico (2006)
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Muñoz, R., Castillo, O., Melin, P. (2009). Optimization of Fuzzy Response Integrators in Modular Neural Networks with Hierarchical Genetic Algorithms: The Case of Face, Fingerprint and Voice Recognition. In: Castillo, O., Pedrycz, W., Kacprzyk, J. (eds) Evolutionary Design of Intelligent Systems in Modeling, Simulation and Control. Studies in Computational Intelligence, vol 257. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04514-1_7
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DOI: https://doi.org/10.1007/978-3-642-04514-1_7
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