1er. Seminario Nacional de Aprendizaje e Inteligencia Computacional 2013
Conferencias Magistrales
Design of Hybrid Intelligent Systems with Modular Neural Networks and Type-2 Fuzzy Systems for Pattern Recognition: The case of multimodal biometric systems.
Dra. Patricia Melin
Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Mexico
This talk describes hybrid intelligent systems using type-2 fuzzy logic and modular neural networks for pattern recognition applications. Hybrid intelligent systems combine several intel-ligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful pattern recognition systems. Type-2 fuzzy logic is an extension of traditional type-1 fuzzy logic that enables managing higher levels of uncertainty in complex real world problems, which are of particular importance in the area of pattern recognition. The first part of the talk describes theory and design algorithms, which are the basis for achieving intelligent pattern recognition. The second part of the talk describes type-2 fuzzy models and modular neural networks with the aim of designing intelligent systems for complex pattern recognition problems, including iris, ear, face and voice recognition. The third part of the talk describes evolutionary optimization of type-2 fuzzy systems and modular neural networks in the area of intelligent pattern recognition, which in-cludes the application of genetic and bio-inspired algorithms for obtaining optimal type-2 fuzzy integration systems and ideal neural network architectures for solving problems in this area.
Dra. Patricia Melin CV.
Bio-Inspired Optimization of Type-2 Fuzzy Systems in Intelligent Control Applications
Dr. Oscar Castillo
Division of Graduate Studies, Tijuana Institute of Technology, Tijuana, Mexico
Hybrid intelligent systems based on type-2 fuzzy logic for achieving intelligent control are of crucial importance in practice to manage the high degrees of uncertainty present in real world processes. Hybrid intelligent systems usually combine several intelligent computing paradigms, including fuzzy logic, and bio-inspired optimization algorithms, which can be used to produce powerful automatic control systems. This talk will cover evolutionary optimization of type-2 fuzzy systems in intelligent control with the aim of designing optimal type-2 fuzzy controllers for complex control problems in diverse areas of application, including mobile robotics, aircraft dynamic systems and hardware implementations. This talk will also deal with the theme of bio-inspired optimization of type-2 fuzzy systems in intelligent control, which includes the application of particle swarm intelligence and ant colony optimization algorithms for obtaining optimal type-2 fuzzy controllers.
Dr. Oscar Castillo CV.