This paper presents partitional fuzzy clustering methods based on adaptive quadratic distances. The methods presented furnish a fuzzy partition and a prototype for each cluster by optimizing an adequacy criterion based on adaptive quadratic distances. These distances change at each algorithm iteration and can either be the same for all clusters or different from one cluster to another. Moreover...

7 This paper presents partitional fuzzy clustering methods based on adaptive quadratic distances. The methods presented furnish a fuzzy partition and a prototype for each cluster by optimizing an adequacy criterion based on adaptive quadratic distances. These 9 distances change at each algorithm iteration and can either be the same for all clusters or different from one cluster to another. More...

In this paper, we develop fuzzy, possibilistic hypothesis tests for testing crisp hypotheses a distribution parameter from data. these tests, fuzzy statistics are used, which produced by the possibility of estimated parameter, constructed known confidence intervals. The results in much better agreement with than ones respective popular book on statistics, uses critical values. We also present a...

Abstract: An adaptive identifier for neuro-fuzzy control system nonlinear dynamic object operating in conditions of uncertainty intrinsic properties and the environment. The algorithms of structural and parametric identification in real time are a combination of an identification algorithm coefficients of linear management and methods of the theory of interactive adaptation. Adaptive neuro-fuzz...

This paper deals with the design of adaptive fuzzy sliding-mode controllers for the T-S fuzzy model based on the Lyapunov function. It is shown that the Lyapunov function can be used to establish fuzzy sliding surfaces by solving a set of linear matrix inequalities (LMIs). The design of the fuzzy sliding surfaces and the adaptive fuzzy sliding-mode controllers is proposed. The adaptive mechanis...

Though traditional neural networks and fuzzy logic are powerful universal approximators, however without some refinements, they may not, in general, be good approximators for adaptive systems. By extending fuzzy sets to qualitative fuzzy sets, fuzzy logic may become universal approximators for adaptive systems. Similar considerations can be extended to neural networks.

 This paper proposes a fuzzy line of sight (LOS)/non-line of sight (NLOS) smoother based on an adaptive Kalman filter, which can be used for mobile location estimation with the time of arrival (TOA) measurement data in cellular networks to meet the Federal Communications Commission (FCC) requirement for phase . A fuzzy inference scheme is used by the proposed location estimator to detect LOS c...

In this paper, we study the control of chaotic systems with unknown parameters. A stable adaptive control scheme is used to guarantee that the parameter estimator converges to stabilizing values such that the controlled chaotic system asymptotically approaches a reference point. A Lyapunov function approach is used to prove a global result which guarantees the stability of both controlled chaot...

In this paper, we present a combined direct and indirect adaptive control scheme for adjusting an adaptive fuzzy controller, and an adaptive fuzzy identification model parameters. First, using adaptive fuzzy building blocks, with a common set of parameters, we design and study an adaptive controller and an adaptive identification model that have been proposed for a general class of the uncertai...

The dynamics of the Autonomous Underwater Vehicles (AUVs) are highly nonlinear and time varying and the hydrodynamic coefficients of vehicles are difficult to estimate accurately because of the variations of these coefficients with different navigation conditions and external disturbances. This study presents the on-line system identification of AUV dynamics to obtain the coupled nonlinear dyna...