2006

The present doctoral thesis aims towards the development of new long-term, multi-channel, audio-visual processing techniques for the analysis of bioacoustics phenomena. The effort is focused on the study of the physiology of the gastrointestinal system, aiming at the support of medical research for the discovery of gastrointestinal motility patterns and the diagnosis of functional disorders….

Over the last decade, the massive demand for high data-rate wireless applications has motivated the study and design of new communication technologies. Among all of them, multi-antenna schemes have been shown to provide remarkable benefits in terms of spectral efficiency. In order to achieve channel capacity bounds, some sort of pre-processing on the transmit side…

Today, adaptive algorithms represent one of the most frequently used computational tools for the processing of digital speech signals. This work investigates and analyzes the properties of adaptive algorithms in speech communication applications where rigorous conditions apply, such as noise and echo cancelation. Like other theses in this field do, it tries to tackle the…

A large variety of important tasks in low?-level vision, image analysis and pat?tern recognition can be formulated as discrete labeling problems where one seeks to optimize some measure of the quality of the labeling. For example such is the case in optical flow estimation, stereo matching, image restoration to men?tion only a few of them….

In this work we develop and study a framework for tracking and prediction of multipath components for wireless MIMO channels. The proposed methodology is a multi-stage procedure that relies on the concept of hypermodels, which capture the dynamics for each multipath. First the individual multipaths are resolved and extracted. In this work we also develop…

Single channel source separation is a quite recent problem of constantly growing interest in the scientific world. However, this problem is still very far to be solved, and even more, it cannot be solved in all its generality. Indeed, since this problem is highly underdetermined, the main difficulty is that a very strong knowledge about…

Super-resolution (SR) is a filtering technique that combines a sequence of under-sampled and degraded low-resolution images to produce an image at a higher resolution. The reconstruction takes advantage of the additional spatio-temporal data available in the sequence of images portraying the same scene. The fundamental problem addressed in super-resolution is a typical example of an…

In nowadays communication systems, error correction provides robust data transmission through imperfect (noisy) channels. Error correcting codes are a crucial component in most storage and communication systems ? wired or wireless ?, e.g. GSM, UMTS, xDSL, CD/DVD. At least as important as the data integrity issue is the recent realization that error correcting codes fundamentally…

We consider fitting data by linear and nonlinear models. The specific problems that we aim at, although they encompass classic formulations, have as common ground the fact that we attack a special situation: the ill-posed problems. In the linear case, we consider the total least squares problem. There exist special methods to approach the so-called…

In order to find more sophisticated trends in data, potential correlations between larger and larger groups of variables must be considered. Unfortunately, the number of such correlations generally increases exponentially with the number of input variables and, as a result, brute force approaches become unfeasible. So, the data needs to be simplified sufficiently. Yet, the…