Timing of Fuzzy Membership Functions from Data

In this dissertation the generation and tuning of fuzzy membership function parameters are considered as a part of the fuzzy model development process. The automatic generation and tuning of fuzzy membership function parameters are needed for the fast adaptation and tuning of fuzzy models of various nonlinear dynamical systems. The developed methods are especially useful in automatic fuzzy membership function generation and tuning when dynamic of application area is fast enough to exclude manual tuning. The fuzzy model development process and development methods, modelling environment and nature of application area as well as algorithm development parameters are extensively discussed, because each of them sets their own restrictions on the design parts and parameters used in the modelling. The developed methods have been applied in different kinds of applications (in forecasting the demand of signal transmission products, power control and code tracking of cellular phone system, fuzzy reasoning in radio resource functions of cellular phone systems), where other approaches are either very difficult or too time consuming to implement. The professional areas of the thesis are fuzzy modelling and control in telecommunications.