Generalized Self-Organizing Network Algorithms for Cluster Analysis and Classifier Design

Bezdek博士打算扩展广义模糊c均值（FCM） 聚类算法包括Minkowsi范数族， 适用于检测"四四方方"数据分布中的簇。 他 然后将详细说明FCM和Kohonen的 自组织特征映射， 每个人的基础。 这些进展将在 使用来自医学图像分析的数据的标准算法 （放射性核素心血管造影、EEG脑图）和多传感器 目标探测

Dr. Bezdek intends to extend the generalized fuzzy c-means (FCM) clustering algorithm to include the Minkowsi norm family, suitable for detecting clusters in "boxy" data distributions. He will then elaborate the relationship between FCM and Kohonen's self-organizing feature maps, strengthing the theoretical foundations of each. These advances will be tested against standard algorithms using data from medical image analysis (radionuclide angiocardiography, EEG brain maps) and multisensor target detection.