We consider Bayesian networks (BNs) with discriminatively optimized parameters and structures, i.e. BNs that are optimized to maximize a kind of probabilistic margin. These maximum margin Bayesian networks (MM BNs) are inspired by support vector machines (SVMs) that aim to separate samples from different classes by a large margin in some feature space. MM BNs…
In this dissertation, new methods for audiovisual speech synthesis using Hidden Markov Models (HMMs) are presented and their properties are investigated. The problem of audiovisual speech synthesis is to computationally generate both audible speech as well as a matching facial animation or video (a ?visual speech signal?) for any given input text. This results in…
This work aims at exploiting compressive sensing paradigms in order to reduce the cost of statistical learning tasks. We first provide a reminder of compressive sensing bases and describe some statistical analysis tasks using similar ideas. Then we describe a framework to perform parameter estimation on probabilistic mixture models in a case where training data…
Epilepsy is a neurological condition that manifests in epileptic seizures as a result of an abnormal, synchronous activity of a large group of neurons. Depending on the affected brain regions, seizures produce various severe clinical symptoms. Epilepsy cannot be cured and in many cases is not controlled by medication either. Surgical resection of the region…
This dissertation deals with the distributed processing techniques for parameter estimation and efficient data-gathering in wireless communication and sensor networks. The estimation problem consists in inferring a set of parameters from temporal and spatial noisy observations collected by different nodes that monitor an area or field. The objective is to derive an estimate that is…
Biometric systems consist in the combination of devices, algorithms, and procedures used to recognize the individuals based on the characteristics, physical or behavioral, of their persons. These characteristics are called biometric traits. Nowadays, biometric technologies are becoming more and more widespread, and many people use biometric systems daily. However, in some cases the procedures used…
Multiple-input multiple output (MIMO) systems deploy multiple antennas at either end of a communication link and can provide significant benefits compared to traditional single antenna systems, such as increased data rates through spatial multiplexing gain, and/or improved link reliability through diversity techniques. Recently, the natural extension of utilising multiple antennas in relay networks, known as…
This thesis proposes and discusses aspects of a low-cost wireless network called ?Hopscotch? as a potential solution to the rural broadband problem. Providing broadband internet access to rural locations is challenging due to the long distances between internet backbone and households, the sparse population density and difficult terrain. Hopscotch uses a network of renewable powered…
Multichannel acoustic signal processing has undergone major development in recent years due to the increased complexity of current audio processing applications. People want to collaborate through communication with the feeling of being together and sharing the same environment, what is considered as Immersive Audio Schemes. In this phenomenon, several acoustic effects are involved: 3D spatial…
Modern wireless communication systems utilize complex modulated signals such as OFDM signals to achieve increased data rates and spectral efficiency. These signals are characterized by a high peak-to-average-power ratio (PAPR). Thus, highly linear transmitters are required to provide sufficient transmission signal linearity. Conventional linear PAs, such as Class A or Class AB, produce high efficiency…
