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mutual-informations
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Electrode selection for noninvasive fetal electrocardiogram extraction using mutual information criteria
, Article AIP Conference Proceedings ; Volume 872 , 2006 , Pages 97-104 ; 0094243X (ISSN) ; Vrins, F ; Parmentier, F ; Hérail, C ; Vigneron, V ; Verleysen, M ; Jutten, C ; Shamsollahi, M. B ; Sharif University of Technology
2006
Abstract
Blind source separation (BSS) techniques have revealed to be promising approaches for the noninvasive extraction of fetal cardiac signals from maternal abdominal recordings. From previous studies, it is now believed that a carefully selected array of electrodes well-placed over the abdomen of a pregnant woman contains the required 'information' for BSS, to extract the complete fetal components. Based on this idea, previous works have involved array recording systems and sensor selection strategies based on the Mutual Information (MI) criterion. In this paper the previous works have been extended, by considering the 3-dimensional aspects of the cardiac electrical activity. The proposed method...
Three easy ways for separating nonlinear mixtures?
, Article Signal Processing ; Volume 84, Issue 2 , 2004 , Pages 217-229 ; 01651684 (ISSN) ; Babaie Zadeh, M ; Hosseini, S ; Sharif University of Technology
2004
Abstract
In this paper, we consider the nonlinear Blind Source Separation BSS and independent component analysis (ICA) problems, and especially uniqueness issues, presenting some new results. A fundamental difficulty in the nonlinear BSS problem and even more so in the nonlinear ICA problem is that they are nonunique without a suitable regularization. In this paper, we mainly discuss three different ways for regularizing the solutions, that have been recently explored. © 2003 Elsevier B.V. All rights reserved
Differential of the Mutual Information
, Article IEEE Signal Processing Letters ; Volume 11, Issue 1 , 2004 , Pages 48-51 ; 10709908 (ISSN) ; Jutten, C ; Nayebi, K ; Sharif University of Technology
2004
Abstract
In this letter, we compute the variation of the mutual information, resulting from a small variation in its argument. Although the result can be applied in many problems, we consider only one example: the result is used for deriving a new method for blind source separation in linear mixtures. The experimental results emphasize the performance of the resulting algorithm
Robust blind separation of smooth graph signals using minimization of graph regularized mutual information
, Article Digital Signal Processing: A Review Journal ; Volume 132 , 2022 ; 10512004 (ISSN) ; Hajipour Sardouie, S ; Sharif University of Technology
Elsevier Inc
2022
Abstract
The smoothness of the graph signals on predefined/constructed graphs appears in many natural applications of processing unstructured (i.e., graph-based) data. In the case of latent sources being smooth graph signals, blind source separation (BSS) quality can be significantly improved by exploiting graph signal smoothness along with the classic measures of statistical independence. In this paper, we propose a BSS method benefiting from the minimization of mutual information as a well-known independence criterion and also graph signal smoothness term of the estimated latent sources, and show that its performance is superior and fairly robust to the state-of-the-art classic and Graph Signal...
Landmark and intensity based image registration using free form deformation
, Article 2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2012 ; 2012 , Pages 768-771 ; 9781467316668 (ISBN) ; Khorsandi, R ; Fatemizadeh, E ; University Malaya; CBMTI University Malaya; Tourism Malaysia; Kumpulan ABEX Sdn Bhd; AMAN kampus ; Sharif University of Technology
2012
Abstract
The registration of images is a fundamental task in numerous applications in medical image processing. In this paper, a novel registration technique is proposed which combines landmark and intensity based approaches. In this framework, the free form deformation (FFD) is used as transformation which is the key point of our algorithm. Landmarks with FFD transformation define the guidance surface which increases robustness of intensity based registration to bias field (bias noise). In fact, the performance of registration is improved by matching both landmark and intensity information. The experimental results show that the proposed method is more accurate than only intensity based method...
On hypercontractivity and the mutual information between Boolean functions
, Article 2013 51st Annual Allerton Conference on Communication, Control, and Computing, Allerton 2013, Monticello, IL ; Oct , 2013 , Pages 13-19 ; 9781479934096 (ISBN) ; Gohari, A. A ; Kamath, S ; Nair, C ; Sharif University of Technology
IEEE Computer Society
2013
Abstract
Hypercontractivity has had many successful applications in mathematics, physics, and theoretical computer science. In this work we use recently established properties of the hypercontractivity ribbon of a pair of random variables to study a recent conjecture regarding the mutual information between binary functions of the individual marginal sequences of a sequence of pairs of random variables drawn from a doubly symmetric binary source
ICA by Mutual Information minimization: An approach for avoiding local minima
, Article 13th European Signal Processing Conference, EUSIPCO 2005, Antalya, 4 September 2005 through 8 September 2005 ; 2005 , Pages 253-256 ; 1604238216 (ISBN); 9781604238211 (ISBN) ; Bahmani, B ; Jutten, C ; Sharif University of Technology
2005
Abstract
Using Mutual Information (MI) minimization is very common in Blind Source Separation (BSS). However, it is known that gradient descent approaches may trap in local minima of MI in constrained models. In this paper, it is proposed that this problem may be solved using a 'poor' estimation of the derivative of MI
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) ; 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) ; 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
Sensitivity of the secrecy capacity of a wiretap channel to the channel gains with imperfect channel information
, Article IWCIT 2017 - Iran Workshop on Communication and Information Theory, 3 May 2017 through 4 May 2017 ; 2017 ; 9781509047833 (ISBN) ; Bafghi, H. G ; Seyfe, B ; Sharif University of Technology
Abstract
In this paper, the impact of a small variations in the channel gains on the secrecy rate of the wiretap channel is studied, in which it is assumed that the imperfect channel knowledge is available at the transmitter. First, we consider general additive noise model for both legitimate and eavesdropper channels in the wiretap channel, and compute the variation of the secrecy rate resulting from the small variations in the channel gains. Then, we focus on the Gaussian wiretap channel, as a special case and calculate the sensitivity of the secrecy capacity to the channel gains with imperfect channel knowledge. Interestingly, it is shown that in some situations the effect of the channel variation...
Multiple access wiretap channels with strong secrecy
, Article 2010 IEEE Information Theory Workshop, ITW 2010 - Proceedings, 30 August 2010 through 3 September 2010, Dublin ; 2010 ; 9781424482641 (ISBN) ; Aref, M. R ; Sharif University of Technology
2010
Abstract
The problem of secure communication over multiple-Access Wiretap channel (MAC-WTC) under strong secrecy criterion is investigated. A new technique based on channel output statistics approximation is developed for establishing the strong security over multi-user channels. In particular, this technique shows that how simple wiretap coding results in secure communication under strong secrecy criterion instead of weak secrecy criterion. As a side result of the paper, two results on the output statistics of MAC are provided. Such results can be used to approximate the mutual information between input and output of MAC with respect to a given codebook of arbitrary rate
Blind separation of bilinear mixtures using mutual information minimization
, Article Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009, 2 September 2009 through 4 September 2009, Grenoble ; 2009 ; 9781424449484 (ISBN) ; Babaie Zadeh, M ; Jutten, C ; Sharif University of Technology
Abstract
In this paper an approach for blind source separation in bilinear (or linear quadratic) mixtures is presented. The proposed algorithm employs the same recurrent structure as [Hosseini and Deville, 2003) for separating these mixtures . However, instead of maximal likelihood, our algorithm is based on minimizing the mutual information of the outputs for recovering the independent components. Simulation results show the efficiency of the proposed algorithm. © 2009 IEEE
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) ; 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
A correlation measure based on vector-valued Lp norms
, Article 2019 IEEE International Symposium on Information Theory, ISIT 2019, 7 July 2019 through 12 July 2019 ; Volume 2019-July , 2019 , Pages 1132-1136 ; 21578095 (ISSN); 9781538692912 (ISBN) ; Beigi, S ; Gohari, A ; Yassaee, M. H ; Aref, M. R ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2019
Abstract
In this paper, a new measure of correlation is introduced. This measure depends on a parameter α, and is defined in terms of vector-valued Lp norms. The measure is within a constant of the exponential of α-Rényi mutual information, and reduces to the trace norm (total variation distance) for α = 1. We provide some properties and applications of this measure of correlation. In particular, we establish a bound on the secrecy exponent of the wiretap channel (under the total variation metric) in terms of the α-Rényi mutual information according to Csiszár's proposal. © 2019 IEEE
A new method for estimating Score Function Difference (SFD) and its application to Blind Source Separation
, Article 13th European Signal Processing Conference, EUSIPCO 2005, Antalya, 4 September 2005 through 8 September 2005 ; 2005 , Pages 1507-1510 ; 1604238216 (ISBN); 9781604238211 (ISBN) ; Babaie Zadeh, M ; Jutten, C ; Sharif University of Technology
2005
Abstract
Score Function Difference (SFD) is a recently proposed "gradient" for mutual information which can be used in Blind Source Separation algorithms based on minimization of mutual information. To be applied to practical problems, SFD must be estimated from the data samples. In this paper, a new method for estimating SFD is proposed. To compare the performance of this new estimator with other proposed SFD estimation methods, we have applied them in separating linear instantaneous mixtures. It will be seen that our method performs superior to all other methods previously proposed for estimation of SFD
Non-Rigid Medical Image Registration Based on Information Theory
, M.Sc. Thesis Sharif University of Technology ; 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...
Recognizing Center of Siezur with Clustering Algorithm
, M.Sc. Thesis Sharif University of Technology ; 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 ; 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...
Mono-modal image registration via correntropy measure
, Article Iranian Conference on Machine Vision and Image Processing, MVIP ; Sept , 2013 , Pages 223-226 ; 21666776 (ISSN) ; 9781467361842 (ISBN) ; Fatemizadeh, E ; Sharif University of Technology
IEEE Computer Society
2013
Abstract
The registration of images is a fundamental task in numerous applications in medical image processing. Similarity measure is an important key in intensity based image registration. Here, we propose correntropy measure as similarity measure in mono modal setting. Correntropy is a important measure between two random variables based on information theoretic learning and kernel methods. This measure is useful in non-Gaussian signal processing. In this paper, this measure is used in image registration. Here, we analytically illustrate that this measure is robust in presence of spiky noise (impulsive noise). The experimental results show that the proposed similarity has better performance than...
Filter-bank design based on dependencies between frequency components and phoneme characteristics
, Article European Signal Processing Conference, 29 August 2011 through 2 September 2011 ; Septembe , 2011 , Pages 2142-2145 ; 22195491 (ISSN) ; Sameti, H ; Tavanaei, A ; Soltani Farani, A ; Sharif University of Technology
2011
Abstract
Mel-frequency Cepstral coefficients are widely used for feature extraction in speech recognition systems. These features use Mel-scaled filters. A new filter-bank based on dependencies between frequency components and phoneme characteristics is proposed. F-ratio and mutual information are used for this purpose. A new filter-bank is designed in which frequency resolution of sub-band filters is inversely proportional to the computed dependency values. These new filterbank is used instead of Mel-scaled filters for feature extraction. A phoneme recognition experiment on FARSDAT Persian language database showed that features extracted using the proposed filter-bank reach higher accuracy (63.92%)...