Conventional remote sensing classification techniques that model the data in each class with a multivariate Gaussian distribution are inefficient, as this assumption is generally ...
Chintan A. Shah, Manoj K. Arora, Stefan A. Robila,...
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
We present a simple and efficient entropy coder that combines run-length and Golomb-Rice encoders. The encoder automatically switches between the two modes according to simple rul...
A generalized ICA model allowing overcomplete bases and additive noises in the observables is applied to natural image data. It is well known that such a model produces independen...
This paper introduces a simple and very general theory of compressive sensing. In this theory, the sensing mechanism simply selects sensing vectors independently at random from a ...