Abstract--We describe in this paper an audio denoising technique based on sparse linear regression with structured priors. The noisy signal is decomposed as a linear combination of...
In this paper, sparse representation (factorization) of a data matrix is first discussed. An overcomplete basis matrix is estimated by using the K−means method. We have proved ...
Yuanqing Li, Andrzej Cichocki, Shun-ichi Amari, Se...
We propose a new method for estimating the mixing matrix, A, in the linear model x(t) = As(t), t = 1, . . . , T, for the problem of underdetermined Sparse Component Analysis (SCA)....
Nima Noorshams, Massoud Babaie-Zadeh, Christian Ju...
It is now common practice in machine vision to define the variability in an object's appearance in a factored manner, as a combination of shape and texture transformations. I...
The adaptive estimation of a time-varying parameter vector in a linear Gaussian model is considered where we a priori know that the parameter vector belongs to a known arbitrary s...