Classification of Electromyographic Hand Gesture Signals Using Modified Fuzzy C-Means Clustering and Two-Step Machine Learning Approach

Bulgarian Hand-Printed Character Recognition Using Fuzzy C-Means Clustering

Audio signal segmentation and classification using fuzzy c-means clustering

This paper proposes an audio signal segmentation and classification method using fuzzy c-means clustering. Recently, high performance of the audio signal segmentation and classification is required for audio-visual indexing because of the popular use of the Internet, higher bandwidth access to the network, widespread of digital recording and storage; and several methods have been proposed. They...

OPTIMIZATION OF FUZZY CLUSTERING CRITERIA BY A HYBRID PSO AND FUZZY C-MEANS CLUSTERING ALGORITHM

This paper presents an efficient hybrid method, namely fuzzy particleswarm optimization (FPSO) and fuzzy c-means (FCM) algorithms, to solve the fuzzyclustering problem, especially for large sizes. When the problem becomes large, theFCM algorithm may result in uneven distribution of data, making it difficult to findan optimal solution in reasonable amount of time. The PSO algorithm does find ago...

Genetic Approach for Fuzzy Mining Using Modified K-Means Clustering

A fuzzy-genetic data-mining algorithm for extracting both association rules and membership functions from quantitative transactions is shown in this paper. It used a combination of large 1-itemsets and membershipfunction suitability to evaluate the fitness values of chromosomes. The calculation for large 1itemsets could take a lot of time, especially when the database to be scanned could not to...

Bilateral Weighted Fuzzy C-Means Clustering

Nowadays, the Fuzzy C-Means method has become one of the most popular clustering methods based on minimization of a criterion function. However, the performance of this clustering algorithm may be significantly degraded in the presence of noise. This paper presents a robust clustering algorithm called Bilateral Weighted Fuzzy CMeans (BWFCM). We used a new objective function that uses some k...