Loading...
Search for: statistics
0.009 seconds
Total 916 records

    On statistical learning of simplices: Unmixing problem revisited

    , Article Annals of Statistics ; Volume 49, Issue 3 , 2021 , Pages 1626-1655 ; 00905364 (ISSN) Najafi, A ; Ilchi, S ; Saberi, A. H ; Motahari, S. A ; Hossein Khalaj, B ; Rabiee, H. R ; Sharif University of Technology
    Institute of Mathematical Statistics  2021
    Abstract
    We study the sample complexity of learning a high-dimensional simplex from a set of points uniformly sampled from its interior. Learning of simplices is a long studied problem in computer science and has applications in computational biology and remote sensing, mostly under the name of “spectral unmixing.” We theoretically show that a sufficient sample complexity for reliable learning of a K-dimensional simplex up to a total-variation error of ε is O(Kε2 log Kε ), which yields a substantial improvement over existing bounds. Based on our new theoretical framework, we also propose a heuristic approach for the inference of simplices. Experimental results on synthetic and real-world datasets... 

    A hybrid of statistical and conditional generative adversarial neural network approaches for reconstruction of 3D porous media (ST-CGAN)

    , Article Advances in Water Resources ; Volume 158 , 2021 ; 03091708 (ISSN) Shams, R ; Masihi, M ; Bozorgmehry Boozarjomehry, R ; Blunt, M. J ; Sharif University of Technology
    Elsevier Ltd  2021
    Abstract
    A coupled statistical and conditional generative adversarial neural network is used for 3D reconstruction of both homogeneous and heterogeneous porous media from a single two-dimensional image. A statistical approach feeds the deep network with conditional data, and then the reconstruction is trained on a deep generative network. The conditional nature of the generative model helps in network stability and convergence which has been optimized through a gradient-descent-based optimization method. Moreover, this coupled approach allows the reconstruction of heterogeneous samples, a critical and serious challenge in conventional reconstruction methods. The main contribution of this work is to... 

    Iterative detection for V-BLAST MIMO communication systems based on expectation maximisation algorithm

    , Article Electronics Letters ; Volume 40, Issue 11 , 2004 , Pages 684-685 ; 00135194 (ISSN) Rad, K. R ; Nasiri Kenari, M ; Sharif University of Technology
    2004
    Abstract
    By applying the expectation maximisation algorithm to the maximum likelihood detection of layered space-time codes, the conditional log-likelihood of a single layer is iteratively maximised, rather than maximising the intractable likelihood function of all layers. Computer simulations demonstrate the efficiency of the proposed detection scheme  

    A more accurate prediction of liquid evaporation flux

    , Article Iranian Journal of Chemistry and Chemical Engineering ; Volume 23, Issue 2 , 2004 , Pages 45-53 ; 10219986 (ISSN) Khosravi Darani, K ; Sabzyan, H ; Zeini Isfahani, A ; Parsafar, G ; Sharif University of Technology
    Iranian Journal of Chemistry and Chemical Engineering  2004
    Abstract
    In this work, a more accurate prediction of liquid evaporation flux has been achieved. The statistical rate theory approach, which is recently introduced by Ward and Fang and exact estimation of vapor pressure in the layer adjacent to the liquid-vapor interface have been used for prediction of this flux. Firstly, the existence of an equilibrium layer adjacent to the liquid-vapor interface is considered and the vapor pressure in this layer and its thickness calculated. Subsequently, by using the Fick's second law, an appropriate vapor pressure expression for the pressure of equilibrium layer is derived and by this expression and the statistical rate theory approach, evaporation flux is... 

    Syllable duration prediction for Farsi text-to-speech systems

    , Article Scientia Iranica ; Volume 11, Issue 3 , 2004 , Pages 225-233 ; 10263098 (ISSN) Nazari, B ; Nayebi, K ; Sheikhzadeh, H ; Sharif University of Technology
    Sharif University of Technology  2004
    Abstract
    In this paper, two different statistical approaches are used for duration prediction of the Farsi language. These two statistical models are Neural Networks (NN) and Classification And Regression Trees (CART). The first step in this work was to create a database and develop a flexible feature extraction and selection module. In the next step, the output of the feature selection module was used to train both models. The results of the trained models are further studied to determine the most important parameters affecting the syllable duration in Farsi, The model accuracy is evaluated by using separate training and test data. In the third step of this work, ah automatic rule generator module... 

    Stochastic analysis and regeneration of rough surfaces

    , Article Physical Review Letters ; Volume 91, Issue 22 , 2003 ; 00319007 (ISSN) Jafari, G.R ; Fazeli, S. M ; Ghasemi, F ; Vaez Allaei, S. M ; Rahimi Tabar, M ; Iraji zad, A ; Kavei, G ; Sharif University of Technology
    2003
    Abstract
    We investigate the Markov property of rough surfaces. Using stochastic analysis, we characterize the complexity of the surface roughness by means of a Fokker-Planck or Langevin equation. The obtained Langevin equation enables us to regenerate surfaces with similar statistical properties compared with the observed morphology by atomic force microscopy. © 2003 The American Physical Society  

    Monte Carlo simulation of 2-ethoxyethanol in continuum configurational biased procedure: Conformational analysis and association in aqueous and non-aqueous media

    , Article Theoretical Chemistry Accounts ; Volume 107, Issue 3 , 2002 , Pages 162-172 ; 1432881X (ISSN) Tafazzoli, M ; Jalili, S ; Sharif University of Technology
    Springer New York  2002
    Abstract
    Monte Carlo simulations have been carried out for 2-ethoxyethanol (C 2E1) in isothermal-isobaric ensemble (NPT) at different temperatures and 1 atm pressure with a continuum configurational biased procedure in water and chloroform media. Hydrogen bond bridges were formed between adjacent oxygen atoms in C2E1 (CH 3CH2OCH2CH2OH) through water molecules. We also found that the stable conformers of C2E 1 in water and CHCl3 are different and the effect of temperature on solute-solvent interaction energies is considerable. The self-association of C2E1 in aqueous and nonaqueous media has been studied by statistical perturbation theory, and the relative free energy has been obtained at different... 

    Adaptive CFAR processor for nonhomogeneous environments

    , Article IEEE Transactions on Aerospace and Electronic Systems ; Volume 36, Issue 3 PART 1 , 2000 , Pages 889-897 ; 00189251 (ISSN) Ali, M ; Mohammad, K ; Bastani, H ; Sharif University of Technology
    2000
    Abstract
    A new constant false alarm rate (CFAR) processor is presented, that exhibits a noticeable detection performance in the presence of interfering targets, as well as an excellent false alarm rate (FAR) regulation at the clutter power transition regions. The presented CFAR processor, which is designed to work on the logarithmic amplified video signals, can also easily adapt itself to new environmental conditions. Furthermore, in the steady state, its performance does not depend on the background noise power. Simulation results show the obvious preference of the presented processor to the conventional GOCA-LOG/CFAR, regarding FAR regulation at the clutter power transition regions. Noncoherent... 

    Fundamental Limits of Population Stratification From an Information Theoretic View

    , M.Sc. Thesis Sharif University of Technology Tahmasebi, Behrooz (Author) ; Maddah-Ali, Mohammad Ali (Supervisor) ; Motahari, Abolfazl (Co-Supervisor)
    Abstract
    This thesis consists of two parts. For the first, we study the identifiability of finite mixtures of finite product measures. This class of mixture models has a large number of applications in real-world data modeling. An important example is the population genetic application of them in modeling of mixed population datasets. The identifiability means that the mapping between the class parameters and the mixture distributions is one to one. In this manuscript, we define some separability metrics inspired by methods used in clustering mixture models and study the fundamental trade off between identifiability and the number of separable variables of the mixture model. For the second part of... 

    Evolving an accurate model based on machine learning approach for prediction of dew-point pressure in gas condensate reservoirs

    , Article Chemical Engineering Research and Design ; Vol. 92, issue. 5 , May , 2014 , p. 891-902 ; ISSN: 02638762 Majidi, S. M. J ; Shokrollahi, A ; Arabloo, M ; Mahdikhani-Soleymanloo, R ; Masihi, M ; Sharif University of Technology
    Abstract
    Over the years, accurate prediction of dew-point pressure of gas condensate has been a vital importance in reservoir evaluation. Although various scientists and researchers have proposed correlations for this purpose since 1942, but most of these models fail to provide the desired accuracy in prediction of dew-point pressure. Therefore, further improvement is still needed. The objective of this study is to present an improved artificial neural network (ANN) method to predict dew-point pressures in gas condensate reservoirs. The model was developed and tested using a total set of 562 experimental data point from different gas condensate fluids covering a wide range of variables. After a... 

    A statistical inference approach for the identification of dominant parameters in immiscible nitrogen injection

    , Article Energy Sources, Part A: Recovery, Utilization and Environmental Effects ; Vol. 36, Issue. 12 , 2014 , Pages 1285-1295 ; ISSN: 15567036 Moradi, S ; Ghazvini, M. G ; Dabir, B ; Emadi, M. A ; Rashtchian, D ; Sharif University of Technology
    Abstract
    Screening analysis is a useful guideline that helps us with proper field selection for different enhanced oil recovery processes. In this work, reservoir simulation is combined with experimental design to estimate the effect of reservoir rock and fluid properties on performance of immiscible nitrogen injection. Reservoir dip, thickness, and horizontal permeability are found to be the most influential parameters. Possible interactions of parameters are also discussed to increase reliability and robustness of screening results. Finally, significance of both main effects and interactions are evaluated by employing a statistical inference approach (hypothesis testing) and results are compared to... 

    Dependency of codon usage on protein sequence patterns: A statistical study

    , Article Theoretical Biology and Medical Modelling ; Vol. 11, issue. 1 , 2014 ; ISSN: 17424682 Foroughmand-Araabi, M. H ; Goliaei, B ; Alishahi, K ; Sadeghi, M ; Sharif University of Technology
    Abstract
    Background: Codon degeneracy and codon usage by organisms is an interesting and challenging problem. Researchers demonstrated the relation between codon usage and various functions or properties of genes and proteins, such as gene regulation, translation rate, translation efficiency, mRNA stability, splicing, and protein domains. Researchers usually represent segments of proteins responsible for specific functions or structures in a family of proteins as sequence patterns or motifs. We asked the question if organisms use the same codons in pattern segments as compared to the rest of the sequence. Methods. We used the likelihood ratio test, Pearson's chi-squared test, and mutual information... 

    A hybrid root transformation and decision on belief approach to monitor multiattribute Poisson processes

    , Article International Journal of Advanced Manufacturing Technology ; Volume 75, Issue 9-12 , December , 2014 , Pages 1651-1660 ; ISSN: 02683768 Niaki, S. T. A ; Javadi, S ; Fallahnezhad, M. S ; Sharif University of Technology
    Abstract
    Most of industrial applications of statistical process control involve more than one quality characteristics to be monitored. These characteristics are usually correlated, causing challenges for the monitoring methods. These challenges are resolved using multivariate quality control charts that have been widely developed in recent years. Nonetheless, multivariate process monitoring methods encounter a problem when the quality characteristics are of the attribute type and follow nonnormal distributions such as multivariate binomial or multivariate Poisson. Since the data analysis in the latter case is not as easy as the normal case, more complexities are involved to monitor multiattribute... 

    Functional process capability analysis in mechanical systems

    , Article International Journal of Advanced Manufacturing Technology ; Vol. 73, issue. 5-8 , July , 2014 , p. 899-912 ; 02683768 Khodaygan, S ; Movahhedy, M. R ; Sharif University of Technology
    Abstract
    Functional quality in the mechanical products is governed mainly by the degree of satisfaction of the design requirements, which itself depends on the variations in the effective variables. The functional parameters cannot be easily measured in mass production, and thus, are not usually considered as a direct inspection objective. Process capability indices are useful tools for evaluating the ability of a process to produce the dependent variables of a product that meet certain specifications. In this paper, the conventional process capability concept is extended to develop a computational tool for analysis of the functional quality of a mechanical product. Through defining new proper... 

    Finding assignable cause in medium voltage network by statistical process control

    , Article IET Conference Publications ; Volume 2013, Issue 615 CP , 2013 ; 9781849197328 (ISBN) Eini, B. J ; Mirzavand, M ; Mahdloo, F ; Sharif University of Technology
    2013
    Abstract
    The current of outgoing feeders are very important data transmitted over SCADA system. Monitoring of these currents can help dispatching engineers to detect abnormality in energy consumption trend and minor faults in distribution network. Statistical process control (SPC) is one of the capable approaches which can be used for this purpose. Statistical process control is based on categorizing variations into assignable causes and random causes. In current paper we described the methods which were used for finding assignable causes in load trend and short time load variation in Alborz province power distribution company pilot project. Although this approach is not developed completely and some... 

    Static statistical MPSoC power optimization by variation-aware task and communication scheduling

    , Article Microprocessors and Microsystems ; Volume 37, Issue 8 PART B , 2013 , Pages 953-963 ; 01419331 (ISSN) Momtazpour, M ; Goudarzi, M ; Sanaei, E ; Sharif University of Technology
    2013
    Abstract
    Corner-case analysis is a well-known technique to cope with occasional deviations occurring during the manufacturing process of semiconductors. However, the increasing amount of process variation in nanometer technologies has made it inevitable to move toward statistical analysis methods, instead of deterministic worst-case-based techniques, at all design levels. We show that by statically considering statistical effects of random and systematic process variation on performance and power consumption of a Multiprocessor System-on-Chip (MPSoC), significant power improvement can be achieved by static software-level optimizations such as task and communication scheduling. Moreover, we analyze... 

    Modeling the effect of process variations on the delay and power of the digital circuit using fast simulators

    , Article 2013 21st Iranian Conference on Electrical Engineering, ICEE 2013 ; 2013 , 14-16 May ; 9781467356343 (ISBN) Amirsoleimani, A ; Soleimani, H ; Ahmadi, A ; Bavandpour, M ; Zwolinski, M ; Sharif University of Technology
    2013
    Abstract
    Process variation has an increasingly dramatic effect on delay and power as process geometries shrink. Even if the amount of variation remains the same as in previous generations, it accounts for a greater percentage of process geometries as they get smaller. So an accurate prediction of path delay and power variability for real digital circuits in the current technologies is very important; however, its main drawback is the high runtime cost. In this paper, we present a new fast EDA tool which accelerates Monte Carlo based statistical static timing analysis (SSTA) for complex digital circuit. Parallel platforms like Message Passing Interface and POSIX® Threads and also the GPU-based CUDA... 

    Optimization of biodiesel production from Iranian bitter almond oil using statistical approach

    , Article Waste and Biomass Valorization ; Volume 4, Issue 3 , September , 2013 , Pages 467-474 ; 18772641 (ISSN) Atapour, M ; Kariminia, H. R ; Sharif University of Technology
    2013
    Abstract
    Response surface methodology (RSM) was applied to optimize the process of biodiesel production from Iranian bitter almond oil. Design of experiments was performed by application of a 5-level-3-factor central composite design in order to study the effect of different factors on the product yield, biodiesel yield and biodiesel purity. These factors were reaction temperature (30-70°C), catalyst concentration (0.3-1.7% w/w) and methanol to oil molar ratio (4.4-13.6 mol/mol). A quadratic model was suggested for the prediction of the biodiesel yield. Analysis of variance revealed that the factors were significant on the production process of biodiesel. For each factor, the optimum value was... 

    Sufficient statistics, classification, and a novel approach for frame detection in OFDM systems

    , Article IEEE Transactions on Vehicular Technology ; Volume 62, Issue 6 , 2013 , Pages 2481-2495 ; 00189545 (ISSN) Abdzadeh Ziabari, H ; Shayesteh, M. G ; Sharif University of Technology
    2013
    Abstract
    This paper addresses the problem of frame detection in orthogonal frequency-division multiplexing (OFDM) systems. Using fourth-order statistics, a novel approach is presented for detection of a preamble composed of two identical parts in the time domain. First, it is demonstrated that sufficient statistics for detection of a periodic preamble do not exist, and conventional methods are not optimal. Next, looking at the detection of a preamble from the viewpoints of hypothesis testing and classification, a new method is presented based on the idea that fourth-order statistics can increase class separability (between-class distance) and consequently improve detection performance. It is proven...