The emerging theory of compressed sensing (CS) provides a universal signal detection approach for sparse signals at sub-Nyquist sampling rates. A small number of random projection...
We present a new and computationally efficient scheme for classifying signals into a fixed number of known classes. We model classes as subspaces in which the corresponding data...
—Sparse representations have emerged as a powerful tool in signal and information processing, culminated by the success of new acquisition and processing techniques such as Compr...
This paper proposes a novel subspace approach towards direct identification of a residual model for fault detection and isolation (FDI) in a system with non-uniformly sampled mult...
Independent component analysis (ICA) is possibly the most widespread approach to solve the blind source separation (BSS) problem. Many different algorithms have been proposed, tog...
Jarkko Ylipaavalniemi, Nima Reyhani, Ricardo Vig&a...