In order to better identify the fault of rotor system,one new method based on local fuzzy clustering margin fisher discriminant (LFCMFD) was proposed. For each point on manifold, the farthest point in local neighborhood and the nearest point outside local neighborhood usually constituted the local margin. LFCMFD introduced fuzzy cluster analysis algorithm, eliminated the influence of pseudo-mar...

Although the rough set and intuitionistic fuzzy set both capture the same notion, imprecision, studies on the combination of these two theories are rare. Rule extraction is an important task in a type of decision systems where condition attributes are taken as intuitionistic fuzzy values and those of decision attribute are crisp ones. To address this issue, this paper makes a contribution of th...

unknown noise and artifacts present in medical signals with  non-linear fuzzy filter will be estimate and then removed. an adaptive neuro-fuzzy interference system which has a nonlinear  structure presented  for the noise function prediction by before samples. this paper is about a neuro-fuzzy method to estimate unknown noise of electrocardiogram (ecg) signal. adaptive neural combined with fuzz...

In this paper, the performance of the various fuzzy based algorithms for medical image segmentation is presented. Fuzzy c-means (FCM) algorithm has proved its effectiveness for image segmentation. However, still it lacks in getting robustness to noise and outliers, especially in the absence of prior knowledge of the noise. To overcome this problem, different types of fuzzy algorithms are introd...

The interface between combinatorial optimization and fuzzy sets-based methodologies is the subject of very active and increasing research. In this context we describe FANS, a fuzzy adaptive neighborhood search optimization heuristic that uses a fuzzy valuation to qualify solutions and adapts its behavior as a function of the search state. FANS may also be regarded as a local search framework. W...

Abstract Multi-label feature selection, a crucial preprocessing step for multi-label classification, has been widely applied to data mining, artificial intelligence and other fields. However, most of the existing selection methods dealing with mixed have following problems: (1) These rarely consider importance features from multiple perspectives, which analyzes not comprehensive enough. (2) sel...

Wireless Sensor Networks have critical resource constraints and minimizing resources usage is crucial to extend the network lifetime. Energy saving in WSNs can be achieved through several techniques, such as topology control and clustering, to provide a longer lifetime and scalability to the network. In this paper we propose a semantic clustering model based on a fuzzy inference system to find ...

In this paper, a direct adaptive fuzzy backstepping control approach for a class of unknown nonlinear systems is developed. By a special design scheme, the controller singularity problems are avoided perfectly in this approach. Furthermore, the closed-loop signals are guaranteed to be semiglobally uniformly ultimately bounded and the outputs of the system are proved to converge to a small neigh...

This work describes a hand gesture recognition system using an optimized Image Processing-Fuzzy C-Means (FCM) algorithm. The parameters of the image processing and clustering algorithm were simultaneously found using a neighborhood parameter search routine, resulting in solutions within 1-2% of optimal. Comparison of user dependent and user independent systems, when tested with their own traine...