Titlebook: Computational Intelligence; Principles, Techniqu Amit Konar Textbook 2005 Springer-Verlag Berlin Heidelberg 2005 Multi-agent system.artific

BILL

Spirometry

Fuzzy Logic in Process Control,ds the scope of approximate reasoning of fuzzy logic in industrial process control systems. Two distinct models of fuzzy control namely Mamdani’s model and Takagi-Sugeno’s model have been discussed in this chapter with numerical illustrations. One important aspect of controller design for smart proc

Range-Of-Motion

Fuzzy Pattern Recognition,tinctive features of the patterns are correctly identified, the classes can easily be distinguished in the feature space. Unfortunately, features in most pattern recognition problems are selected on an ad hoc basis, consequently causing the pattern classes to overlap, thereby leading to an ambiguity

debble

Mets552

天然熱噴泉

Supervised Neural Learning Algorithms,ts application in realization of binary logic functions. Rosenblatt’s perceptron learning algorithm designed for the McCulloch-Pitts neuronal model is presented next. Application of the perceptron learning model in both linear and nonlinear classification problems is then introduced. The chapter als

Pedagogy

hypnotic

Competitive Learning Using Neural Nets,ng network having a noise-free input realized with an on-center off-surround configuration. An analysis of the model has been presented in detail. The scope of realization of competition by Hebbian learning and the way-out to handle the limitation of Hebbian learning by Oja’s principle have been dis

archenemy

Chromatic

Evolutionary Computing Algorithms,optimization problems. After a brief introduction to this algorithm, the chapter provides a detailed discussion on one such algorithm, called Genetic Algorithm. An analysis of Genetic Algorithm by the well-known Schema theorem and Markov Chains is then presented. The latter part of the chapter is de