In this paper, we investigate the L-fuzzy proximities and the relationships betweenL-fuzzy topologies, L-fuzzy topogenous order and L-fuzzy uniformity. First, we show that the category of-fuzzy topological spaces can be embedded in the category of L-fuzzy quasi-proximity spaces as a coreective full subcategory. Second, we show that the category of L -fuzzy proximity spaces is isomorphic to the ...

D. Molodtsov (1999) introduced the concept of a soft set as a new approach for modeling uncertainties. The aim of this work is to define special kinds of soft sets, namely soft, L-fuzzifying soft, L-soft, and L-fuzzy soft neighborhood sets and to use them in order to give an alternative characterization of categories related to topology: crisp topological, L-topological, L-fuzzifying topologica...

Structure learning in random fields has attracted considerable attention due to its difficulty and importance in areas such as remote sensing, computational biology, natural language processing, protein networks, and social network analysis. We consider the problem of estimating the probabilistic graph structure associated with a Gaussian Markov Random Field (GMRF), the Ising model and the Pott...

Cluster analysis has an important role in analysis of the ElectroEnsepholoGraphy (EEG) signals of the brain activities [Escalona-Moran et al., 2007; Jin S-H. Et al., 2005; Van Hese et al., 2008]. The primary objective of clustering is to simplify statistical analysis by grouping similar objects in a cluster. Clustering methods can be divided into five main groups such as hierarchical, prototype...

This paper presents an online trained Fuzzy logic system based on FPGA to fault detection of broken rotor bar for squirrel cage induction motor. Fuzzy logic approach may help to diagnose induction motor faults in remote site and transmit fault diagnosis (via GSM\GPRS cellular network technology) to maintenance office or a programmed cell phone. The motor current signal is analyzed through the F...

Associative neural memories are models of biological phenomena that allow for the storage of pattern associations and the retrieval of the desired output pattern upon presentation of a possibly noisy or incomplete version of an input pattern. In this paper, we introduce fuzzy swarm particle optimization technique for convergence of associative neural memories based on fuzzy set theory. An FPSO ...

The position tracking control problem of permanent magnet synchronous motors with parameter uncertainties and load torque disturbance is addressed. Fuzzy logic systems are used to approximate nonlinearities and adaptive backstepping technique is employed to construct controllers. The proposed adaptive fuzzy controllers guarantee that the tracking error converges to a small neighborhood of the o...

This paper describes the design of an adaptive direct control scheme for a class of nonlinear systems. The architecture is based on a fuzzy inference system (FIS) of Takagi Sugeno (TS) type to approximate a feedback linearization control law. The parameters of the consequent part of the fuzzy system are adapted and changed according to a law derived using Lyapunov stability theory. The asymptot...

The evaluation of texture in digital remote sensing, is traditionally accomplished by applying statistical, rather than structural models. This approach is partially due to the difficulty in determining structural placement rules for natural scenes, and to early psychophysical texture theories that demonstrated humans were sensitive to second-order statistics. A literature review indicates that...