Methods are investigated in order to partition in k groups a set of n multivariate observation vectors located at neighboring geographic sites; applications include image segmentation, ecological or soil data cartography. In this perspective, the deterministic variant of the EM procedure described in Zhang (1992) for hidden Markov random fields is shown to be equivalent to the optimization of a...

In this paper, the problems of stability and control for a class of uncertain nonlinear systems with unknown state time-delay are studied by using the fuzzy logic systems. Because the dynamic surface control technique is introduced to deal with the uncertain time-delay systems, the designed adaptive fuzzy controller can avoid the issue of “explosion of complexity”, which comes from the traditio...

This paper presents a fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on urban development is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. A defuzzification process converts the development potential to the required neighborhood development level, which is taken by cellular au...

The primary issue involved in image and signal processing is to efficiently remove noise from a digital color image while preserving its features. A fuzzy filter is presented for the reduction of additive noise for digital color images. The filter consists of two sub filters. The first sub filter computes fuzzy distances among the color components of the central pixel and its neighborhood. Thes...

This paper considers the adaptive fuzzy robust control problem for a class of single-input and single-output (SISO) stochastic nonlinear systems in strict-feedback form. The systems under study possess unstructured uncertainties, unknown dead-zone, uncertain dynamics and unknown gain functions. In the controller design, fuzzy logic systems are adopted to approximate the unknown functions, and t...

Social network data has been modeled with several approaches, including Sociogram and Sociomatrices, which are popular and comprehensive. Similar to these we have developed here a novel modeling technique based on granular computing theory and fuzzy neighborhood systems, which provides a uniform framework to represent social networks. In this model, a social network is represented with a collec...

This paper deals with a problem of minimizing total weighted tardiness of jobs in a real-world single batch-processing machine (SBPM) scheduling in the presence of fuzzy due date. In this paper, first a fuzzy mixed integer linear programming model is developed. Then, due to the complexity of the problem, which is NP-hard, we design two hybrid metaheuristics called GA-VNS and VNS-SA applying the...

This paper proposes a novel adaptive fuzzy decentralized output-feedback control approach for a class of uncertain nonlinear large-scale systems. The considered nonlinear systems possess the unknown nonlinear functions, unmeasured states and unknown time-varying delays. Fuzzy logic systems are employed to approximate the unknown nonlinear functions, and adaptive high-gain filters are presented ...

The selection of genes from microarray gene expression datasets has become an important research in cancer classification because such data typically consist of a large number of genes and a small number of samples. In this work, Neighborhood mutual information is retrieved to evaluate the relevance between genes and is used to stop information loss. Firstly, an improved Relief Feature Selectio...