This paper introduces an automated medical data classification method using wavelet transformation (WT) and interval type-2 fuzzy logic system (IT2FLS). Wavelet coefficients, which serve as inputs to the IT2FLS, are a compact form of original data but they exhibits highly discriminative features. The integration between WT and IT2FLS aims to cope with both high-dimensional data challenge and un...

In this paper, we present a channel equalization scheme for time-division multiple access (TDMA) satellite communications with burst digital transmission. We show that each channel states of multipath satellite channel follows a Gaussian distribution, which means a Bayesian equalization can be implemented. The parameters of the Bayesian equalization are determined using an unsupervised clusteri...

Instruments for microanalysis are now able to provide several images of the same specimen area. In this paper, two groups of methods are described for handling these multivariate maps. One group concerns dimensionality reduction, i.e., the projection of N-dimensional data sets onto a M-dimensional parameter space (M<N). It is shown that, in addition to linear mapping which can be performed by M...

In this paper, we study a new type of clustering problem, called Chromatic Clustering, in high dimensional space. Chromatic clustering seeks to partition a set of colored points into groups (or clusters) so that no group contains points with the same color and a certain objective function is optimized. In this paper, we consider two variants of the problem, chromatic k-means clustering (denoted...

A new method for segmentation of the carotid artery for classifying it as diseased or normal towards plaque diagnosis is proposed in this paper. Kernel Fuzzy CMeans clustering is used for segmenting the longitudinal section of the carotid artery using which the wall layers of the artery are identified for classifying it as diseased or normal. As a pre-processing step a–nonlinear mean filter is ...

Most Gene Regulatory Network (GRN) studies ignore the impact of the noisy nature of gene expression data despite its significant influence upon inferred results. This paper presents an innovative Collateral-Fuzzy Gene Regulatory Network Reconstruction (CF-GeNe) framework for Gene Regulatory Network (GRN) inference. The approach uses the Collateral Missing Value Estimation (CMVE) algorithm as it...

In current study, a particle swarm clustering method is suggested for clustering triangular fuzzy data. This clustering method can find fuzzy cluster centers in the proposed method, where fuzzy cluster centers contain more points from the corresponding cluster, the higher clustering accuracy. Also, triangular fuzzy numbers are utilized to demonstrate uncertain data. To compare triangular fuzzy ...

A novel high-order fuzzy time series model for stock price forecasting is presented based on the fuzzy cmeans (FCM) discretization method and artificial neural networks (ANN). In the proposed model, the FCM discretization method obtained reliable interval lengths. In addition, the fuzzy relation matrix was obtained from ANN, mooting the need for complex and time-consuming matrix operations. The...