Functional near infrared spectroscopy (fNIRS) needs a standardization in signal processing tools before it is recognized as a reliable neuroimaging modality. This thesis study tries to present a comprehensive analysis of the feasibility of applying statistical inference methods to fNIRS signals. Using hierarchical linear models, both classical and Bayesian techniques are pursued and performance of…
In this thesis, a general solution to the component separation problem in images is introduced. Unlike most existing works, the spatial dependencies of images are modelled in the separation process with the use of Markov random fields (MRFs). In the MRFs model, Cauchy density is used for the gradient images. We provide a general Bayesian…
This work is focused on the synthesis of Digital Signal Processing (DSP) circuits usingc specific hardware architectures. Due to its complexity, the design process has been subdivided into separate tasks, thus hindering the global optimization of the resulting systems. The author proposes the study of the combination of two major design tasks, Word-Length Allocation (WLA)…
Cryptography and biometrics have been identified as two of the most important aspects of digital security environment. For various types of security problems the merging between cryptography and biometrics has led to the development of Bio crypt technology. The new technology suffers from several limitations and this thesis, addresses the biometric information quality and the…
This dissertation presents a general method and eight algebraic methods for constructing high performance and efficiently encodable non-binary quasi-cyclic LDPC codes based on arrays of special circulant permutation matrices. Two design techniques, array masking and array dispersion, for constructing both regular and irregular LDPC codes with desired specifications are also proposed. Codes constructed based on…
The thesis addresses the problem of space-time codebook design for communication in multiple-input multiple-output (MIMO) wireless systems. The realistic and challenging non-coherent setup (channel state information is absent at the receiver) is considered. A generalized likelihood ratio test (GLRT)-like detector is assumed at the receiver and contrary to most existing approaches, an arbitrary correlation structure…
In recent years, advances in signal processing have led the wireless sensor networks to be capable of mobility. The signal processing in a wireless sensor network differs from that of a traditional wireless network mainly in two important aspects. Unlike traditional wireless networks, in a sensor network the signal processing is performed in a fully…
The objective of this thesis is to develop and validate robust approaches for the semi-automatic extraction of road networks in dense urban areas from very high resolution (VHR) optical satellite images. Our models are based on the recently developed higher-order active contour (HOAC) phase field framework. The problem is difficult for two main reasons: VHR…
This thesis deals with problems of Pattern Recognition in the framework of Machine Learning (ML) and, specifically, Statistical Learning Theory (SLT using Support Vector Machines (SVMs). The focus of this work is on the geometric interpretation of SVMs, which is accomplished through the notion of Reduced Convex Hulls (RCHs), and its impact on the derivation…
Over the last centuries, hearing aids have evolved from crude and bulky horn-shaped instruments to lightweight and almost invisible digital signal processing devices. While most of the research has focused on the design of monaural apparatus, the use of a wireless link has been recently advocated to enable data transfer between hearing aids such as…
