background: epilepsy is a severe disorder of the central nervous system that predisposes  the person to recurrent seizures. fifty million people worldwide suffer from  epilepsy; after alzheimer's and stroke, it is the third widespread nervous disorder. objective: in this paper, an algorithm to detect the onset of epileptic seizures  based on the analysis of brain electrical signals (eeg) has be...

Background: Epilepsy is a severe disorder of the central nervous system that predisposes the person to recurrent seizures. Fifty million people worldwide suffer from epilepsy; after Alzheimer’s and stroke, it is the third widespread nervous disorder.Objective: In this paper, an algorithm to detect the onset of epileptic seizures based on the analysis of brain electrical signals (EEG) has b...

BACKGROUND Epilepsy is a severe disorder of the central nervous system that predisposes the person to recurrent seizures. Fifty million people worldwide suffer from epilepsy; after Alzheimer's and stroke, it is the third widespread nervous disorder. OBJECTIVE In this paper, an algorithm to detect the onset of epileptic seizures based on the analysis of brain electrical signals (EEG) has been ...

Graph-based Fisher Analysis (GbFA) is proposed recently for dimensionality reduction, which has the powerful discriminant ability. However, GbFA is based on the matrix-to-vector way, which not only costs much but also loses spatial relations of pixels in images. Therefore, Tensor Graph-based Linear Discriminant Analysis (TGbLDA) is proposed in the paper. TGbLDA regards samples as data in tensor...

To study incremental machine learning in tensor space, this paper proposes incremental tensor discriminant analysis. The algorithm employs tensor representation to carry on discriminant analysis and combine incremental learning to alleviate the computational cost. This paper proves that the algorithm can be unified into the graph framework theoretically and analyzes the time and space complexit...

We develop a supervised dimensionality reduction method, called Lorentzian discriminant projection (LDP), for feature extraction and classification. Our method represents the structures of sample data by a manifold, which is furnished with a Lorentzian metric tensor. Different from classic discriminant analysis techniques, LDP uses distances from points to their within-class neighbors and globa...

This paper develops a supervised dimensionality reduction method, Lorentzian Discriminant Projection (LDP), for discriminant analysis and classification. Our method represents the structures of sample data by a manifold, which is furnished with a Lorentzian metric tensor. Different from classic discriminant analysis techniques, LDP uses distances from points to their within-class neighbors and ...

Most existing color-based tracking algorithms utilize the statistical color information of the object as the tracking clues, without maintaining the spatial structure within a single chromatic image. Recently, the researches on the multilinear algebra provide the possibility to hold the spatial structural relationship in a representation of the image ensembles. In this paper, a third-order colo...