We propose to cluster class-wise covariance matrices in order to identify different groups of covariances contributing to the same condition. Each cluster represents a different brain pattern associated with one class. Further, we present Clustered Common Spatial Patterns, a new algorithm that applies this technique prior to CSP. We show that CCSP can outperform CSP in a binary imagery movement...

metropolitan regions as a result of the steady stream of urbanization in industrial period which have occurred during 20th century, become the engine of countries growth and development. in the process of formation and development in these areas, spatial structuring that define through two elements of population and activity with the communication structure interacting between them, has been ef...

background geographic information system (gis) software has been used in health care systems to display and analyze spatial pattern of diseases and health services. objectives this study was performed to assess spatial patterns of colon’s pathologic lesions based on the pathologic reports and assess whether it is possible to use gis software in health services. patients and methods archives of ...

The common spatial patterns (CSP) algorithm is the most popular filtering method applied to extract electroencephalogram (EEG) features for motor imagery (MI) based brain-computer interface (BCI) systems. effectiveness of CSP depends on optimal selection frequency band and time window from EEG. Many algorithms have been designed optimize CSP, while few seek window. This study proposes a novel f...