Sharif Digital Repository

Localization of radio sources has various applications in civil and military communications. Some of important localization methods consist of Angle of Arrival (AoA) estimation of the illuminated signals from the interested sources. Between various Direction Finding (DF) methods, subspace based methods are of special importance, because of their high resolution and accuracy. And from beginning of invention, because of new challenges, have been focus of numerous researches. In this thesis, first we explain the most important subspace based DF methods called MUSIC and root-MUSIC. Then a novel modification for root-MUSIC is introduced. In our new method the computational complexity of... 

Sound source localization has been one of the fundamental problems in many areas, including radar, teleconferencing or videoconferencing, localization of earthquake epicenters and underground explosions, microphone arrays, robots, etc. All of sound source localization ideas are like human auditory system. The human auditory system is a complex and organic information processing system. It can feel the intensity and spatial orientation and other information of sound. The distance of the two ears on our head is about 20cm. When the sound reaches each ear, there are small time difference, intensity difference and phase difference. After analyzing these differences by the brain, the human can... 

The ability of human to analyze the environment around them has been an inspiring source for event analysis research. Since human perception of the environment is formed in a multi-modal space, many efforts have been made to fuse information to create an intelligent fusion. In this study, we want to better understand the environment using information fusion. For this purpose, fuzzy fusion of audio and video signals based on ink drop spread operator is performed for recognizing and tracking of the targets using several scenarios of the AV16.3 dataset. We then focused on the fusion of audio data for sound source localization, one of the most important applications in evaluating fusion... 

In most of brain studies, the primary objective is to find dipole activities, an underdetermined problem that requires additional constraints. Adequate constraints can be added by using information from other modalities. This research aims to develop a platform that combines various noninvasive modalities to improve localization accuracy. To accomplish this, two novel general approaches to combining modalities are proposed. In the first approach, the result of localizing by different methods and in different modalities are processed and combined in intervals by Dempster Shaffer's combination law. The final amount of bipolar activity is obtained by cumulating the activities obtained at... 

Electroencephalogram (EEG) brain source localization carries many potential applications in systems and cognitive neuroscience, and for treatment of various neurological problems such as epilepsy. According to some recent studies, determining the spatial extent of sources and estimating their true time courses have proved challenging. This master's thesis proposes a method for localizing extended brain sources. Cortical surface parcellation has been used to reduce the dimension of the inverse problem without losing much information. The active regions are assumed to be sparse and the time course of the sources exhibits a correlation structure. The reduced dimension problem was then solved by... 

Localization of electrical activity in the brain is one of the major problems in cognitive science and neuroscience. Indeed, Source localization is the inverse processing procedure on brain signals to estimate the location and position of resources in the human brain. Current technics for neurological imaging is included fMRI، PET، MEG and ERP. These methods is not appropriated to answer the question that when does each of different components of the brain begin their activity. The EEG signals could be useful to eliminate some of limitations of above methods. The problem with EEG signals collected from the skull is that they don’t refer directly to the location of active neurons. The... 

Over the years, The robots have entered the human community in addition to the factories and industrial centers, and a new branch in the field of robotics called social robots has been created. Such robots can become a personal companion for children and elderly people who accompany that person at home or outside. Social robots can even be used as a platform for health services or as a vendor in stores. The interaction of humans and robots in social robots and communicating with the audience is the main part of this series of robots. Human-robot interaction can be divided into three parts: visual, auditory and facial or body movements. Also, the behavior of a social robot must be as natural... 

Dementia is one of the most common disorders among the elderly population. Statistical analyses show that among several subtypes of dementia, Alzheimer’s disease (AD) is the most frequent cause of dementia and this number is projected to increase. AD not only results in impairment of learning and memory but also in the moderate stages of illness, motor functions are profoundly disturbed, and ultimately will affect the patient's lifetime. The proposed drug treatments for this disease only reduce its progress probability. Therefore, early diagnosis for effective treatment of Alzheimer's disease is one of the critical issues in the field of dementia. This project is an effort to extract... 

Complex networks science have received tremendous attention in recent years and the brain is one of the systems to which graph theoretical tools have been applied. Alzheimer’s disease (AD) is a neurodegenerative disease affecting many of elderly population. AD changes the anatomy of the brain, which subsequently results in changes in its functions. These changes have been frequently reported in signals recorded from the brain (such as MEG, fMRI and EEG). Among these neuroimaging techniques EEG is one of the most aproprate methods for extracting functional connectivites according to high temporal resolution. In this thesis, we aimed at analyzing the properties of EEG-based functional networks... 

Throughout localization algorithms, sound source localization has received much interest using microphone array. Applications like tracking and determining angle of acoustic signal arrival have been combined with array processing techniques in the previous decade. Distributed micro sensor array have been suggested for a wide range of nowaday’s localization algorithms. The major goals are monitoring the environment, distinction, and pursue some phenomenon. This type of networks can be utilized for military application in tracking acoustic sources. Today’s advancement in technology allows implementation of the ultra low cost and low power integrated circuit for such application in the form of...