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    Detecting and Estimating the Time of Single Step Change in Nonlinear Profiles

    , M.Sc. Thesis Sharif University of Technology Ghazizadeh Ahsaei, Ali (Author) ; Mahlooji, Hashem (Supervisor)
    Abstract
    This effort attempts to study the change point problem in the area of non-linear profiles. Two methods for estimating the time of a single step change is proposed. In the first method a model consisting of two networks which is based on artificial neural networks is proposed. These networks are different only in their training data. One network is trained for ascending segments of the profile and the other is trained for descending segments of the profile. In the second method the maximum likelihood estimator (MLE) of the single step change is analyzed. Due to the complexity of estimating the parameters of the non-linear model by MLE, this estimator is based on the difference between the... 

    Low-cost, Non-infrared, MRI-compatible Eye Tracker for Research

    , M.Sc. Thesis Sharif University of Technology Cherakhloo, Mahdi (Author) ; Ghazizadeh, Ali (Supervisor)
    Abstract
    Looking for eye paths is widely used in various research and even commercial areas, Eye trackers that are used commercially today do this by using infrared transmitters and receivers. As the speed and performance of the processors advanced, many efforts have been made to create an eye-tracking device using visible light without any movement restrictions for the subject, and efforts to increase the accuracy and speed of sampling are still ongoing; The initial methods proposed in this area are feature-based, but newer papers and researches have used Deep learning methods to do this. The commonly used methods for eye tracking in visible light are three main steps: 1. Fetching frames from the... 

    Effect of Reward Training on Visual Representation of Objects in the Brain

    , M.Sc. Thesis Sharif University of Technology Sharifi, Kiomars (Author) ; Ghazizadeh, Ali (Supervisor)
    Abstract
    Sight is probably our most important sense. Every day, humans are exposed to many visual stimuli in their surroundings. The human brain is able to identify and prioritize important and valuable stimuli and memorize them. Identifying and remembering these valuable stimuli is vital to meeting the needs and maintaining survival. The aim of the proposed research is to find the effect of reward learning on the coding of visual objects in the human brain. Previous results have shown that long-term reward-object association make valuable objects more recognizable behaviorally. Studies have also shown that visual stimuli and the pattern of activity of primary visual cortex neurons are closely... 

    Design and Implementation of True Time Delay (TTD) Circuits in 0.18μm CMOS for Transceiver Module Application

    , Ph.D. Dissertation Sharif University of Technology Ghazizadeh, Mohammad Hossein (Author) ; Medi, Ali (Supervisor)
    Abstract
    In order to improve the performance of radar systems, encouraging the movement towards multifunctional applications, wider frequency span is required to be considered for phased array systems constituting radars. The conventional approach of phase shifting is not applicable to wideband phased array system, and the need for phased array systems based on time delay is apparent. In active phased array systems where a transceiver module is placed before each radiating element, the task of controlling the delay and gain variation of each path is assigned to individual core chips residing in the transceiver modules. A typical core chip consists of several amplifying blocks along, with delay and... 

    Analysis and Comparison of the Role of SNr and vlPFC in Value Learning and Memory and Value Guided Saccade

    , M.Sc. Thesis Sharif University of Technology Kheirkhah Ravandi, Mohammad Ali (Author) ; Ghazizadeh, Ali (Supervisor)
    Abstract
    Learning the value of the objects in the living environment of animals has a great significance in guiding the behavior of animals. Therefore, understanding the mechanisms and structures involved in this phenomenon in the brain is one of the topics of interest in modern neuroscience. One of the most important structures known in the mammalian brain that plays an important role in learning the value of objects is the Basal ganglia. The value signal of objects has been observed in different areas of this structure. Another important area of the brain, whose role in learning the value of objects has recently been investigated, is the area of the Ventrolateral Prefrontal Cortex (vlPFC). On the... 

    Extension and Comparing the PSTH and ICA in Order to Extract Information from Neural Point Processes

    , Ph.D. Dissertation Sharif University of Technology Heidarieh, Mohsen (Author) ; Jahed, Mehran (Supervisor) ; Ghazizadeh, Ali (Co-Supervisor)
    Abstract
    The quantity and quality of information extracted from the brain, in addition to data collection methods, is also related to the statistical tools used. As extracting maximum information in both temporal and spatial dimension require electrophysiological approaches on the physical side, the statistical methods should be optimized to that end, on the theoretical side. The time histogram method is the most basic tool for capturing a time-dependent rate of neuronal spikes. Generally, in the neurophysiological literature, the bin size that critically determines the goodness of the fit of the time histogram to the underlying spike rate has been subjectively selected by individual researchers.... 

    Designing an Emotion Capturing System Using Eeg Signals and Human-obot Interaction Platform Based on the Captured Emotion

    , M.Sc. Thesis Sharif University of Technology Nazemi Harandi, Hamed (Author) ; Taheri, Alireza (Supervisor) ; Meghdari, Ali (Supervisor) ; Ghazizadeh, Ali (Co-Supervisor)
    Abstract
    Emotions are one of the most important issues which affects daily life and activities. On the other hand, robots play an increasing role in human life and play a fundamental role in meeting our needs. One of these basic roles is empathy and verbal interaction between the robot and human. In this research, participant's emotions were stimulated in two ways: by using OASIS and GAPED image data sets and by instructing the participants to remind about their good or bad memories. During emotional stimulation, EEG signals have been recorded for the training and testing process. The preprocessing of training data includes filtering, removing bad parts of data, removing bad channels and... 

    Effective Connectivity Analysis in Neural circuitry Underlying Perceptual and Value-based Memory

    , M.Sc. Thesis Sharif University of Technology Fakharian, Mohammad Amin (Author) ; Amini, Arash (Supervisor) ; Ghazizadeh, Ali (Co-Supervisor)
    Abstract
    Perceptual memory used in novel vs familiar discrimination is not only vital for the evaluation of environmental variations but also essential for learning, perception, and correcting behavioral policies. On the other hand, value-based memory which allows for discrimination of valuable objects among equally familiar ones also drives behavioral interactions and decision making. Although many studies have been conducted to address the neuronal association regarding each separately, the neural correspondence between perceptual and value-based memory is not scrutinized adequately. To this end, the differential neural activation in two macaque monkeys to unrewarded novel vs familiar fractals (>100... 

    Feedback Alignment in Bio-Inspired Artificial Neural Networks

    , M.Sc. Thesis Sharif University of Technology Rahman Setayesh, Alireza (Author) ; Marvasti, Farokh (Supervisor) ; Ghazizadeh, Ali (Supervisor)
    Abstract
    The mechanism by which plasticity in millions of synapses in the brain is orchestrated to achieve behavioral and cognitive goals is a fundamental question in neuroscience. In this regard, insights from learning methods in artificial neural networks and in particular the idea of backpropagation seem inspiring. However, the implementation of BP requires exact matching of forward and backward weights, which is unrealistic given the known connectivity pattern in the brain (known as "weight transport problem"). Notably, it is recently shown that under certain conditions, error backpropagation through random backward weights, can lead to partial alignment of forward and backward weights... 

    Design and Implementation of an Optical Intrinsic Signal Imaging System for Brain by Using Intensity Magnification Algorithm

    , M.Sc. Thesis Sharif University of Technology Alemohammad, Mohammad Amin (Author) ; Fardmanesh, Mahdi (Supervisor) ; Ghazizadeh Ehsaee, Ali (Supervisor)
    Abstract
    In many neuroscience studies, the aim is to investigate the functional role of a population of neurons in response to a certain stimulus. Electrophysiology methods usually can only record from a small population of neurons and this is not sufficient for studying functional properties of the cortex. An alternative is to use functional neuroimaging methods. However, some of these methods are expensive and also they do not offer suitable spatial and temporal resolutions. Optical imaging systems can solve these problems because they are low-cost, easy to design, and also have good temporal and spatial resolutions. These systems can generate functional maps from the brain. In this study, a... 

    Cloud computing based technologies, applications and structure in U-learning

    , Article Proceedings 2012 17th IEEE International Conference on Wireless, Mobile and Ubiquitous Technology in Education, WMUTE 2012, 27 March 2012 through 30 March 2012 ; March , 2012 , Pages 196-198 ; 9780769546629 (ISBN) Ghazizadeh, A ; Manouchehry, M ; Sharif University of Technology
    2012
    Abstract
    This article mainly focuses on the characteristic, technologies and applications of cloud computing in mobile and electronic learning, and analyzes the features of this concept. We firstly tried to clarify the meaning of cloud computing as well as its features, secondly, proposed different models of using cloud computing in different learning environments, including web-based learning, mobile video learning and observational learning  

    Common coding of expected value and value uncertainty memories in the prefrontal cortex and basal ganglia output

    , Article Science Advances ; Volume 7, Issue 20 , 2021 ; 23752548 (ISSN) Ghazizadeh, A ; Hikosaka, O ; Sharif University of Technology
    American Association for the Advancement of Science  2021
    Abstract
    Recent evidence implicates both basal ganglia and ventrolateral prefrontal cortex (vlPFC) in encoding value memories. However, comparative roles of cortical and basal nodes in value memory are not well understood. Here, single-unit recordings in vlPFC and substantia nigra reticulata (SNr), within macaque monkeys, revealed a larger value signal in SNr that was nevertheless correlated with and had a comparable onset to the vlPFC value signal. The value signal was maintained for many objects (>90) many weeks after reward learning and was resistant to extinction in both regions and to repetition suppression in vlPFC. Both regions showed comparable granularity in encoding expected value and value... 

    Salience memories formed by value, novelty and aversiveness jointly shape object responses in the prefrontal cortex and basal ganglia

    , Article Nature Communications ; Volume 13, Issue 1 , 2022 ; 20411723 (ISSN) Ghazizadeh, A ; Hikosaka, O ; Sharif University of Technology
    Nature Research  2022
    Abstract
    Ecological fitness depends on maintaining object histories to guide future interactions. Recent evidence shows that value memory changes passive visual responses to objects in ventrolateral prefrontal cortex (vlPFC) and substantia nigra reticulata (SNr). However, it is not known whether this effect is limited to reward history and if not how cross-domain representations are organized within the same or different neural populations in this corticobasal circuitry. To address this issue, visual responses of the same neurons across appetitive, aversive and novelty domains were recorded in vlPFC and SNr. Results showed that changes in visual responses across domains happened in the same rather... 

    60 GHz Omni-directional segmented loop antenna

    , Article 2016 IEEE Antennas and Propagation Society International Symposium, APSURSI 2016, 26 June 2016 through 1 July 2016 ; 2016 , Pages 1653-1654 ; 9781509028863 (ISBN) Ghazizadeh, M. H ; Fakharzadeh, M ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2016
    Abstract
    The design, simulation and fabrication of a planar fragmented loop antenna with capacitive loads at 60 GHz frequency band is reported in this paper. The loop antenna has a nearly omni-directional radiation pattern required for many IEEE 802.11ad applications, a simulated bandwidth of 6 GHz, and a realized gain of 2 dBi. The measured input matching bandwidth without deembedding the connector effect is nearly 2 GHz. The HPBW in azimuth plane is 360°.s  

    A 125-ps 8-18-GHz CMOS integrated delay circuit

    , Article IEEE Transactions on Microwave Theory and Techniques ; Volume 67, Issue 1 , 2019 , Pages 162-173 ; 00189480 (ISSN) Ghazizadeh, M. H ; Medi, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Abstract
    A wideband integrated delay chain chip with 5-bit main delay control, two error correction bits, maximum delay of 125-and 3.9-ps delay resolution, designed and fabricated in a 0.18-μ m CMOS technology is presented. This delay chain is a cascade of seven passive internal-switched delay blocks which the five main bits are based on novel delay structures. The proposed delay structures are similar to second-, fourth-, and sixth-order all-pass networks and are robust to mismatch effects of resistive parasitics of transistor switches. Measurement results of the fabricated delay chain show 15.2-23.3-dB insertion loss and less than 3.3-ps rms delay error over the intended frequency band from 8-18... 

    Novel trombone topology for wideband true-time-delay implementation

    , Article IEEE Transactions on Microwave Theory and Techniques ; Volume 68, Issue 4 , 2020 , Pages 1542-1552 Ghazizadeh, M. H ; Medi, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    Abstract
    A novel trombone topology has been introduced for achieving controllable true time delay. The prominent aspect of the proposed topology is the ability to provide discrete variable delay with minimum insertion loss variation with delay settings. Furthermore, the effects of source impedance, output load, and line-terminating loads' impedance mismatch on group delay variation are theoretically investigated for the proposed trombone topology. Moreover, based on this new topology, a prototype trombone delay circuit has been designed and fabricated in 0.18- mu ext{m} CMOS technology, operating over the frequency bandwidth of 8-18 GHz. This 3-bit delay integrated circuit provides a maximum delay... 

    High precision CMOS integrated delay chain for X-Ku band applications

    , Article IEEE Transactions on Microwave Theory and Techniques ; Volume 68, Issue 4 , 2020 , Pages 1553-1563 Ghazizadeh, M. H ; Medi, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2020
    Abstract
    A high-precision delay chain circuit integrated in a 0.18- mu ext{m} CMOS technology working in the frequency bandwidth of 8-18 GHz has been designed and tested. The designed delay control integrated circuit with 5-bit delay control provides a maximum delay of 125 ps and has a delay resolution of 3.9 ps. Measured delay error of the fabricated chip is less than 9.3%, making it a considerably accurate delay control circuit. Low delay-error performance has resulted from incorporating a novel delay cell in this delay chain circuit. This newly proposed delay cell is a lumped-element coupled transmission line loaded with a second-order all-pass network (APN). The APN-loaded coupled line delay... 

    A 125-ps 8-18-GHz CMOS integrated delay circuit

    , Article IEEE Transactions on Microwave Theory and Techniques ; Volume 67, Issue 1 , 2019 , Pages 162-173 ; 00189480 (ISSN) Ghazizadeh, M. H ; Medi, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Abstract
    A wideband integrated delay chain chip with 5-bit main delay control, two error correction bits, maximum delay of 125-and 3.9-ps delay resolution, designed and fabricated in a 0.18-μ m CMOS technology is presented. This delay chain is a cascade of seven passive internal-switched delay blocks which the five main bits are based on novel delay structures. The proposed delay structures are similar to second-, fourth-, and sixth-order all-pass networks and are robust to mismatch effects of resistive parasitics of transistor switches. Measurement results of the fabricated delay chain show 15.2-23.3-dB insertion loss and less than 3.3-ps rms delay error over the intended frequency band from 8-18... 

    Derating of distribution transformers under non-linear loads using a combined analytical-finite elements approach

    , Article IET Electric Power Applications ; Volume 10, Issue 8 , 2016 , Pages 779-787 ; 17518660 (ISSN) Ghazizadeh, M ; Faiz, J ; Oraee, H ; Sharif University of Technology
    Institution of Engineering and Technology  2016
    Abstract
    Supplying non-linear loads causes increased losses in transformers which eventually leads to their reduced life spans. Therefore, transformers are derated in order to protect them against premature loss of life. To do this, load losses including ohmic loss and winding eddy current (WEC) loss need to be estimated. This study suggests an improved analytical approach using finite element method (FEM) which includes all material characteristics and geometrical structures in order to calculate WEC loss under non-sinusoidal load current in each winding individually. By adopting this procedure, harmonic loss factor as a dominant parameter in transformers derating is estimated. By emphasising the... 

    Brain activity estimation using EEG-only recordings calibrated with joint EEG-fMRI recordings using compressive sensing

    , Article 13th International Conference on Sampling Theory and Applications, SampTA 2019, 8 July 2019 through 12 July 2019 ; 2019 ; 9781728137414 (ISBN) Ataei, A ; Amini, A ; Ghazizadeh, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2019
    Abstract
    Electroencephalogram (EEG) is a noninvasive, low-cost brain recording tool with high temporal but poor spatial resolution. In contrast, functional magnetic resonance imaging (fMRI) is a rather expensive brain recording tool with high spatial and poor temporal resolution. In this study, we aim at recovering the brain activity (source localization and activity-intensity) with high spatial resolution using only EEG recordings. Each EEG electrode records a linear combination of the activities of various parts of the brain. As a result, a multi-electrode EEG recording represents the brain activities via a linear mixing matrix. Due to distance attenuation, this matrix is almost sparse. Using...