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    Non-Rigid Medical Image Registration Based on Information Theory

    , M.Sc. Thesis Sharif University of Technology Khorsandi, Rahman (Author) ; Fatemizadeh, Emadoddin (Supervisor)
    Abstract
    The registration of images is a fundamental task in numerous applications in medical image processing. The importance of medical image registraiton due to the imaging systems development in last decades is obvious to every one. Especially the wide employment and different capabilities of these systems has caused more attention to this field of image processing. Th e application of medical image registraiton is extended from clinical diagnosis and treatment evaluation, to image guided surgery. The dimension of images as well as modalities of imaging and imaging subjectshas made a wide variety of problems in this branch of image processing. Registration, briefly speaking, is a geometrical... 

    Designing an Estimation of Distribution Algorithm Based on Data Mining Methods

    , M.Sc. Thesis Sharif University of Technology Akbari Azirani, Elham (Author) ; Beigy, Hamid (Supervisor)
    Abstract
    Estimation of distribution algorithms (EDA) are optimization methods that search the solution space by building and sampling probabilistic models. The linkage tree genetic algorithm (LTGA), which can be considered an estimation of distribution algorithm, uses hierarchical clustering to build a hierarchical linkage model called the linkage tree, and gene-pool optimal mixing algorithm to generate new solutions. While the LTGA performs very well on problems with separable sub-problems, its performance deteriorates on ones with overlapping sub-problems. This thesis presents a comparison of the effect of different pre-constructed models in the LTGA's performance. Several important factors that... 

    Using the Echo of Rotating Parts to Recognize a Radar Target

    , M.Sc. Thesis Sharif University of Technology Johari, Mohammad Mahdi (Author) ; Nayebi, Mohammad Mahdi (Supervisor)
    Abstract
    Target recognition techniques based on micro Doppler phenomenon are popular because they are applicable even on low resolution radars, in contrast to other techniques such as High Resolution Range Profile (HRRP) which need high resolution in range or angle. Usually, main purpose of such techniques is generating robust features against target initial state, velocity, aspect angle, etc. rather than features which exactly identify a target. Main approaches in the literature are based on time-frequency transforms (TFT) such as spectrogram in order to generate features to classify targets, but in this thesis, we propose a totally different method using Recurrence Plot for generating features... 

    Recognizing Center of Siezur with Clustering Algorithm

    , M.Sc. Thesis Sharif University of Technology Akhshi, Amin (Author) ; Rahimitabar, Mohammad Reza (Supervisor)
    Abstract
    Complex systems are composed of a large number of subsystems behaving in a collective manner. In such systems, which are usually far from equilibrium, collective behavior arises due to self-organization and results in the formation of temporal, spatial, spatio-temporall structures. Examples of complex systems are turbulent flow, stock markets, dynamics of a brain, etc. In study of the complex systems, we always encounter with handling and analysing of a Big-Data set. There are several approaches to overcome this problem, among which the most powerful method is the clustering analysis. Clustering algorithm is based on the classifying of dynamics of complex system using some similarity... 

    Quantum Estimation: Properties and Calculation of the Quantum Fisher Information and Adaptive Scheme

    , Ph.D. Dissertation Sharif University of Technology Hassani, Majid (Author) ; Rezakhani, Ali (Supervisor)
    Abstract
    In this thesis , we study quantum estimation , its primary tools and different approaches . To this end , along with reviewing the main concepts of classical and quantum estimation , the Cramer-Rao inequlity which establishes a lower bound on the precision of estimation has been used . This lower bound can be calculated using the quantum Fisher information . In order to explore properties of the quantum Fisher information , we study the continuity relation of this quantity in the most general case and we calculate it for different quantum states . To underline the importance of the continuity relation , one can demonstrate an estimate of the value of the quantum Fisher information... 

    On Different Information Theoretic Security Measures in Communication Network

    , M.Sc. Thesis Sharif University of Technology Kavian, Masoud (Author) ; Aref, Mohammad Reza (Supervisor) ; Mirmohseni, Mahtab (Co-Supervisor)
    Abstract
    Reliable and secure communication requires low error probability and low information leakage, respectively. In this thesis we study different security parameters in communication networks. Three important security metrics are noted by weak, strong, and perfect secrecy. A weak condition on secrecy requires the percentage of the message leaked to the adversary vanish as the code length increases, while a strong condition on secrecy requires the total amount of leaked information (not its percentage) vanish as length increases. Perfect secrecy requires absoloutely zero leakage of information for every given block length. An intriguing question is to determine the secrecy rate under secrecy... 

    Multivariate Mutual Information via Secret-key Agreement

    , M.Sc. Thesis Sharif University of Technology Mostafa Zadflah Chobari, Mohammad (Author) ; Ebrahimi, Javad (Supervisor)
    Abstract
    Shannon (1948) for the first time defined the "mutual information'' parameter for two random variables, but still there is no common definition for multivariate mutual information has been agreed upon, despite the multitude of research on the subject and various proposed definitions. In 2015, a study suggested that the maximum rate of secret-key, in the secret-key agreement problem, is a suitable candidate for defining multivariate mutual information. Csiszár and Narayan's research on the secret-key agreement problem provides an accessible bound for the maximum rate of secret-key rate, which in the bivariate case is the shannon's mutual information. The proposed definition has all expected... 

    Predicting the Optimal Operation Pattern of Municipal Wastewater Treatment Plant Using Artificial Intelligence Approaches

    , M.Sc. Thesis Sharif University of Technology Hakimi, Mahdi (Author) ; Torkian, Ayoub (Supervisor)
    Abstract
    With the growth of the population and the significant expansion of industries in the last century, many environmental problems have plagued developed and developing countries. One of these environmental problems is water pollution. Observing the effects of water pollution over time, sanitary and industrial wastewater treatment was proposed as a reliable solution. With technology development, wastewater treatment requirements have become stricter. The increase in energy consumption and wastewater treatment costs due to population growth and industrialization on the one hand and strict regulations, on the other hand, have forced those involved in this field to employ a variety of technical and... 

    Cluster-based sparse topical coding for topic mining and document clustering

    , Article Advances in Data Analysis and Classification ; Volume 12, Issue 3 , 2018 , Pages 537-558 ; 18625347 (ISSN) Ahmadi, P ; Gholampour, I ; Tabandeh, M ; Sharif University of Technology
    Springer Verlag  2018
    Abstract
    In this paper, we introduce a document clustering method based on Sparse Topical Coding, called Cluster-based Sparse Topical Coding. Topic modeling is capable of improving textual document clustering by describing documents via bag-of-words models and projecting them into a topic space. The latent semantic descriptions derived by the topic model can be utilized as features in a clustering process. In our proposed method, document clustering and topic modeling are integrated in a unified framework in order to achieve the highest performance. This framework includes Sparse Topical Coding, which is responsible for topic mining, and K-means that discovers the latent clusters in documents... 

    Blind source separation by adaptive estimation of score function difference

    , Article Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ; Volume 3195 , 2004 , Pages 9-17 ; 03029743 (ISSN); 3540230564 (ISBN); 9783540230564 (ISBN) Samadi, S ; Babaie Zadeh, M ; Jutten, C ; Nayebi, K ; Sharif University of Technology
    Springer Verlag  2004
    Abstract
    In this paper, an adaptive algorithm for blind source separation in linear instantaneous mixtures is proposed, and it is shown to be the optimum version of the EASI algorithm. The algorithm is based on minimization of mutual information of outputs. This minimization is done using adaptive estimation of a recently proposed non-parametric "gradient" for mutual information. © Springer-Verlag 2004  

    Separating convolutive mixtures by mutual information minimization

    , Article 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001, Granada, 13 June 2001 through 15 June 2001 ; Volume 2085 LNCS, Issue PART 2 , 2001 , Pages 834-842 ; 03029743 (ISSN); 9783540422372 (ISBN) Babaie Zadeh, M ; Jutten, C ; Nayebi, K ; Sharif University of Technology
    Springer Verlag  2001
    Abstract
    Blind Source Separation (BSS) is a basic problem in signal processing. In this paper, we present a new method for separating convolutive mixtures based on the minimization of the output mutual information. We also introduce the concept of joint score function, and derive its relationship with marginal score function and independence. The new approach for minimizing the mutual information is very efficient, although limited by multivariate distribution estimations. © Springer-Verlag Berlin Heidelberg 2001  

    End-to-end speech recognition using lattice-free MMI

    , Article 19th Annual Conference of the International Speech Communication, INTERSPEECH 2018, 2 September 2018 through 6 September 2018 ; Volume 2018-September , 2018 , Pages 12-16 ; 2308457X (ISSN) Hadian, H ; Sameti, H ; Povey, D ; Khudanpur, S ; Sharif University of Technology
    International Speech Communication Association  2018
    Abstract
    We present our work on end-to-end training of acoustic models using the lattice-free maximum mutual information (LF-MMI) objective function in the context of hidden Markov models. By end-to-end training, we mean flat-start training of a single DNN in one stage without using any previously trained models, forced alignments, or building state-tying decision trees. We use full biphones to enable context-dependent modeling without trees, and show that our end-to-end LF-MMI approach can achieve comparable results to regular LF-MMI on well-known large vocabulary tasks. We also compare with other end-to-end methods such as CTC in character-based and lexicon-free settings and show 5 to 25 percent... 

    Zero error coordination

    , Article ITW 2015 - 2015 IEEE Information Theory Workshop, 11 October 2015 through 15 October 2015 ; 2015 , Pages 202-206 ; 9781467378529 (ISBN) Abroshan, M ; Gohari, A ; Jaggi, S ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2015
    Abstract
    In this paper, we consider a zero error coordination problem wherein the nodes of a network exchange messages to be able to perfectly coordinate their actions with the individual observations of each other. While previous works on coordination commonly assume an asymptotically vanishing error, we assume exact, zero error coordination. Furthermore, unlike previous works that employ the empirical or strong notions of coordination, we define and use a notion of set coordination. This notion of coordination bears similarities with the empirical notion of coordination. We observe that set coordination, in its special case of two nodes with a one-way communication link is equivalent with the Hide... 

    ECG denoising using mutual information based classification of IMFs and interval thresholding

    , Article 2015 38th International Conference on Telecommunications and Signal Processing, TSP 2015, 9 July 2015 through 11 July 2015 ; July , 2015 , Page(s): 1 - 6 ; 9781479984985 (ISBN) Taghavi, M ; Shamsollahi, M. B ; Senhadji, L ; Molnar K ; Herencsar N ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2015
    Abstract
    The Electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Therefore, the quality of information extracted from the ECG has a vital role. In real recordings, ECG is corrupted by artifacts such as prolonged repolarization, respiration, changes of electrode position, muscle contraction, and power line interface. In this paper, a denoising technique for ECG signals based on Empirical Mode Decomposition (EMD) is proposed. We use Ensemble Empirical Mode Decomposition (EEMD) to overcome the limitations of EMD. Moreover, to overcome the limitations of thresholding methods we use the combination of mutual information and two EMD based interval thresholding approaches. Our new method... 

    On the duality of additivity and tensorization

    , Article IEEE International Symposium on Information Theory - Proceedings, 14 June 2015 through 19 June 2015 ; Volume 2015-June , 2015 , Pages 2381-2385 ; 21578095 (ISSN) ; 9781467377041 (ISBN) Beigi, S ; Gohari, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2015
    Abstract
    A function is said to be additive if, similar to mutual information, expands by a factor of n, when evaluated on n i.i.d. repetitions of a source or channel. On the other hand, a function is said to satisfy the tensorization property if it remains unchanged when evaluated on i.i.d. repetitions. Additive rate regions are of fundamental importance in network information theory, serving as capacity regions or upper bounds thereof. Tensorizing measures of correlation have also found applications in distributed source and channel coding problems as well as the distribution simulation problem. Prior to our work only two measures of correlation, namely the hypercontractivity ribbon and maximal... 

    Structural image representation for image registration

    , Article 2015 International Symposium on Artificial Intelligence and Signal Processing, AISP 2015, 3 March 2015 through 5 March 2015 ; March , 2015 , Pages 95-100 ; 9781479988174 (ISBN) Aghajani, K ; Shirpour, M ; Manzuri, M. T ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2015
    Abstract
    Image registration is an important task in medical image processing. Assuming spatially stationary intensity relation among images, conventional area based algorithms such as CC (Correlation Coefficients) and MI (Mutual Information), show weaker results alongside spatially varying intensity distortion. In this research, a structural representation of images is introduced. It allows us to use simpler similarity metrics in multimodal images which are also robust against the mentioned distortion field. The efficiency of this presentation in non-rigid image registration in the presence of spatial varying distortion field is examined. Experimental results on synthetic and real-world data sets... 

    Comments on 'Information-Theoretic Key Agreement of Multiple Terminals - Part I'

    , Article IEEE Transactions on Information Theory ; Volume 63, Issue 8 , 2017 , Pages 5440-5442 ; 00189448 (ISSN) Gohari, A ; Anantharam, V ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2017
    Abstract
    Theorem 5 of A. Gohari, V. Anantharam, IEEE Transactions on Information Theory, vol. 56, no. 8, pp. 3973-3996, 2010, states an upper bound on the secrecy capacity for the source model problem. It has a three page proof given in Appendix B of the paper. Unfortunately, we show that this bound does not provide any improvement over the simpler bound given in Corollary 1 of the paper. We also provide an example of a family of two agent source model problems where the one-way secrecy rate in each direction is zero, but the secrecy rate is nonzero and can be determined exactly as a conditional mutual information. © 1963-2012 IEEE  

    Flat-Start single-stage discriminatively trained hmm-based models for asr

    , Article IEEE/ACM Transactions on Audio Speech and Language Processing ; Volume 26, Issue 11 , 2018 , Pages 1949-1961 ; 23299290 (ISSN) Hadian, H ; Sameti, H ; Povey, D ; Khudanpur, S ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2018
    Abstract
    In recent years, end-to-end approaches to automatic speech recognition have received considerable attention as they are much faster in terms of preparing resources. However, conventional multistage approaches, which rely on a pipeline of training hidden Markov models (HMM)-GMM models and tree-building steps still give the state-of-the-art results on most databases. In this study, we investigate flat-start one-stage training of neural networks using lattice-free maximum mutual information (LF-MMI) objective function with HMM for large vocabulary continuous speech recognition. We thoroughly look into different issues that arise in such a setup and propose a standalone system, which achieves... 

    Image registration based on low rank matrix: rank-regularized SSD

    , Article IEEE Transactions on Medical Imaging ; January , 2018 , Pages 138-150 ; 02780062 (ISSN) Ghaffari, A ; Fatemizadeh, E ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2018
    Abstract
    Similarity measure is a main core of image registration algorithms. Spatially varying intensity distortion is an important challenge, which affects the performance of similarity measures. Correlation among the pixels is the main characteristic of this distortion. Similarity measures such as sum-of-squared-differences (SSD) and mutual information ignore this correlation; hence, perfect registration cannot be achieved in the presence of this distortion. In this paper, we model this correlation with the aid of the low rank matrix theory. Based on this model, we compensate this distortion analytically and introduce rank-regularized SSD (RRSSD). This new similarity measure is a modified SSD based... 

    Φ-Entropic measures of correlation

    , Article IEEE Transactions on Information Theory ; Volume 64, Issue 4 , 2018 , Pages 2193-2211 ; 00189448 (ISSN) Beigi, S ; Gohari, A ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2018
    Abstract
    A measure of correlation is said to have the tensorization property if it does not change when computed for i.i.d. copies. More precisely, a measure of correlation between two random variables X, Y denoted by rho (X, Y), has the tensorization property if ρ(Xn, Yn)=ρ (X, Y) where (Xn, Yn) denotes n i.i.d. copies of (X, Y). Two well-known examples of such measures are the maximal correlation and the hypercontractivity ribbon (HC ribbon). We show that the maximal correlation and the HC ribbon are special cases of the new notion of Φ-ribbons, defined in this paper for a class of convex functions Φ. Φ-ribbon reduces to the HC ribbon and the maximal correlation for special choices of Φ, and is a...