Sharif Digital Repository

The most popular system for quantification of the facial behaviors and expressions is the Facial Action Coding System (FACS). FACS provides a description of all possible and visually detectable facial variations in terms of 33 Action Units (AUs). The activation of each AU leads to a slight variation in the facial appearance, and any facial expression can be modeled by a single AU or a combination of AUs. Definition of AUs is such that they are sparse in multiple domains. The goal of this dissertation is utilizing these sparsity properties to develop an effective algorithm for automatic intensity estimation of AUs. One of the sparsity domains of AUs is the spatial domain that means the... 

In this work, we evaluate differernt tensor decomposition methods in application of fECG extraction from abdominal ECG recordings. After selecting proper tensor decomposition tool (Tucker decomposition) we propose a linear source separation algorithm based on a measure of quasi-periodicity. The quasi-periodicity is attained through the use of a constraint on a matrix factorization problem. In practice, we form a three dimensional ”tensor” by stacking the observation matrix and rough estimates obtained by both linear and non-linear subspace reconstruction methods. The method is applied to a database of electrocardiography (ECG) recordings, where rough subspace estimates of maternal and fetal... 

Blind Source Separation (BSS) is a challenging task in signal processing which aims to separate sources from their mixtures when no information is available about the sources or the mixing system. Different approaches have already been proposed for source separation.However, during the last decade, new approaches based on multimodal nature of phenomena have been proposed for source separation. Different aspects of a multimodal phenomenon can be measured by means of different instruments where each of the measured signals is called a modality of that phenomenon. Although the modalities are different signals with different features, due to the same physical origin, they usually have some... 

Nowadays, Electroencephalogram (EEG) is the most common method for brain activity measurement. Event Related Potentials (ERP) which are recorded through EEG, have many applications. Detecting ERP signals is an important task since their amplitudes are quite small compared to the background EEG. The usual way to address this problem is to repeat the process of EEG recording several times and use the average signal. Though averaging can be helpful, there is a need for more complicated filtering. Blind source separation methods are frequently used for ERP denoising. These methods don’t use prior information for extracting sources and their use is limited to 2D problems only. To address these... 

Functional Magnetic Resonance Imaging (fMRI) is one of the imaging techniques that are used to study human brain function and neurological disease diagnosis. Popular techniques in fMRI utilize the blood oxygenation level dependent (BOLD) contrast, which is based on the differing magnetic properties of oxygenated (diamagnetic) and deoxygenated (paramagnetic) blood. In order to analyze fMRI data, hypothesis-driven or data-driven methods can be used. Among data-driven techniques, Independent Component Analysis (ICA) provides a powerful method for the exploratory analysis of fMRI data. In this thesis, we use ICA on fMRI data for detecting active regions in brain, without a-priori knowledge of... 

Structural system identification from vibration data is one of the most interesting research topics in the structural health monitoring area. Recently, realization and detection of the effects of damage when a structure is subjected to strong ground motion has become a great concern in earthquake and structural engineering communities. Seismic signal processing is one of the most reliable methods of detecting the structural damage during earthquakes. The structural responses during earthquakes are nonstationary with respect to both amplitude and frequency. The state-of-the-art time-frequency distributions when applied to vibration records were studied. Different methods of analysis for... 

It is generally accepted that Electronic Warfare has three distinct components: (1) electronic support (ES), (2) electronic attack (EA), and (3) electronic protect (EP). ES is included those measures taken to collect information about an adversary by intercepting radiated emissions. EA refers to attempting to deny adversaries access to their information by radiating energy into their receivers. EP includes activities under taken to prevent an adversary from successfully conducting ES or EA on friendly forces.
The function of Electronic Support Measurement (ESM) System is considered as a part of the first component (i.e. ES). After receiving emitted signals from various radars by ESM... 

Blind separation of mixed graph signals is one of the new topics in the field of graph signal processing. However, similar to the most proposed methods for separating traditional signals, it is assumed that the number of observed signals is equal to or greater than the number of sources. In this thesis, we show that a signal can be uniquely decomposed into the summation of a set of smooth graph signals, up to the indeterminacy of their DC values. From the blind source separation point of view, this is like the separation of a set of graph signals from a single mixture, contrary to traditional blind source separation in which at least two observed mixtures are required. Moreover, we... 

Graph signal separation is a new topic in the field of graph signal processing that aims to recover graph signals from their linear combinations, taking into account the relationship between the signals and their corresponding graphs. Among the existing methods for separating graph signals from observing only one mixture, a recently published approach assumes the smoothness of the signals and minimizes the smoothness criterion of the signals on their related graphs. In this thesis, the closed-form solution of this method is obtained and the reconstruction error of the graph signals is calculated from it and the performance of this method is evaluated. It is also shown by numerical...