In one-class classification (OCC) tasks, only the target class (class-of-interest (CoI)) samples are well defined during training, whereas other totally absent. OCC algorithms, high dimensional data adds computational overhead apart from its intrinsic property of curse dimensionality. For learning, conventional dimensionality reduction (DR) techniques not suitable due to negligence unique stati...

Prediction method for time series of imagery data on eigen space is proposed. Although the conventional prediction method is defined on the real world space and time domains, the proposed method is defined on eigen space. Prediction accuracy of the proposed method is supposed to be superior to the conventional methods. Through experiments with time series of satellite imagery data, validity of ...

• Decomposition by central characters • Square-integrable cuspforms • Smoothness of cuspforms • Eigen-cuspforms and automorphic representation • Dirichlet series versus zeta and L-functions • L-functions defined via local data • Factoring unitary representations of adele groups • Spherical representations and Satake parameters • Local data, L-groups, higher L-functions References and historical...

Modified group projector technique for induced representations is a powerful tool for calculation and symmetry quantum numbers assignation of a tight binding Hamiltonian energy bands of crystals. Namely, the induced type structure of such a Hamiltonian enables efficient application of the procedure: only the interior representations of the orbit stabilizers are to be considered. Then the genera...

also satisfies condition (v), and let { I} and { 4,, } be each a set of m linearly independent eigen solutions of H* corresponding to the eigen values i and-i, respectively. If we can find a mapping of 6 on to 22(A) of the form (3) which maps the sets of elements (PM, } and { J,J, } on to sets of functions { (p,,(x) I and { +,(x) } satisfying condition (e), then this mapping takes H into a self...

This paper introduces an efficient Eigen values based technique for online iris image compression and identification of a human including the case of identical twins. The iris image is extracted after removing the pupil, eye brow, skin and other noise disturbances from an actual image. The extracted iris image is divided into different blocks of size of 16×16. Now, Eigen values are calculated f...

We propose an agglomerative hierarchical kernel spectral clustering (AH-KSC) model for large scale complex networks. The kernel spectral clustering (KSC) method uses a primal-dual framework to build a model on a subgraph of the network. We exploit the structure of the projections in the eigenspace to automatically identify a set of distance thresholds. These thresholds lead to the different lev...