Spectral analysis represents a key component in signal processing. The on-chip implementation of classical spectral estimation techniques is generally not considered as a viable B...
Vincent Fresnaud, Lilian Bossuet, Dominique Dallet...
Spectral clustering is a powerful clustering method for document data set. However, spectral clustering needs to solve an eigenvalue problem of the matrix converted from the simil...
Spectral unmixing is an important task for remotely sensed hyperspectral data exploitation. Linear spectral unmixing relies on two main steps: 1) identification of pure spectral c...
We study H(div) preconditioning for the saddle-point systems that arise in a stochastic Galerkin mixed formulation of the steady-state diffusion problem with random data. The key i...
Howard C. Elman, Darran G. Furnival, Catherine E. ...
A real-time audio segmentation and indexing scheme is presented in this paper. Audio recordings are segmented and classified into basic audio types such as silence, speech, music,...