The Experts below are selected from a list of 303 Experts worldwide ranked by ideXlab platform
Adriana Vlad - One of the best experts on this subject based on the ideXlab platform.
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The Statistical Independence for Words in Printed Romanian Language
2020 13th International Conference on Communications (COMM), 2020Co-Authors: Alexandru Dinu, Adriana Vlad, Bogdan Hanu, Adrian MitreaAbstract:The paper revisits the notion of Statistical Independence for printed Romanian when the language is considered as a chain of words. The analysis is carried out on a literary corpus of approx. 6 million words. We aim to improve the perception of the concept of Statistical Independence for natural texts and to use this concept to evaluate the numerical properties of the printed language. One main objective is to estimate the minimum distance in words that ensures Statistical Independence.Here, we followed up on an idea previously researched by the authors - the investigation of Statistical Independence for m-grams (m successive letters). The previous results showed that 100 characters are enough to ensure Statistical Independence for letter m-grams (m = 1, 2, 3) either for the 32-symbol corpus or when the 47-symbol corpus was analyzed. In the present research, we could notice that 100 words can be considered practically enough for the minimum Statistical Independence sampling distance. As there is a huge number of distinct words to be considered, detailed investigations have been conducted regarding the creation of one or more Artificial Words consisting of groups of the low probability words (based on previous findings on the type II Statistical error in word probability investigation) and the results support the above-mentioned minimum Statistical Independence distance.
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A mean test on the autocorrelation function of a chaotic signal aiming to support the Statistical Independence sampling distance
2019 International Symposium on Signals Circuits and Systems (ISSCS), 2019Co-Authors: Corina Macovei, Alexandru Vaduva, Adriana Vlad, Marta ZamfirAbstract:This paper presents an analysis on two skew tent map chaotic signals mostly used in communications and cryptography applications. We inspect the autocorrelation function of tent map and how it relates to the Statistical Independence sampling distance. A Statistical mean test on the autocorrelation function is presented in order to highlight the effect of the control tent map parameter when the autocorrelation function is computed for a distance value corresponding to Statistical Independence. The results are derived from a complex experimental study that included a Monte Carlo analysis on several Statistical autocorrelation functions and simulations using double and extended precision.
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Evaluating the performance of a test-method for Statistical Independence decision in the context of chaotic signals
2016 International Conference on Communications (COMM), 2016Co-Authors: Alexandru Vaduva, Adriana Vlad, Bogdan BadeaAbstract:The current paper addresses the larger field of signal processing, communications and cryptography with an orientation on chaotic signals. We reconsider some aspects concerning the Statistical Independence issue in the context of chaotic signals. We developed a test tool in order to make decisions without the human observer involvement concerning the Statistical Independence of two data sets coming out from continuous random variables with a known or unknown probability law.
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computational measurements of the transient time and of the sampling distance that enables Statistical Independence in the logistic map
International Conference on Computational Science and Its Applications, 2009Co-Authors: Adriana Vlad, Adrian Luca, Madalin FrunzeteAbstract:The paper presents an original Statistical approach dedicated to the evaluation of two time intervals which are useful in various chaotic applications, namely: the transient time and the minimum Statistical Independence sampling distance. The overall procedure relies on Smirnov tests based on two-sample statistic, Kolmogorov-Smirnov tests based on one-sample statistic, a Monte Carlo analysis and an original Statistical Independence test. The experimental study was performed on the logistic map for different values of its parameter, values considered of much interest in the literature. The proposed Statistical approach may guide another experimenter to extend the analysis for other logistic map parameters and also for other chaotic maps.
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ICCSA (2) - Computational Measurements of the Transient Time and of the Sampling Distance That Enables Statistical Independence in the Logistic Map
Computational Science and Its Applications – ICCSA 2009, 2009Co-Authors: Adriana Vlad, Adrian Luca, Madalin FrunzeteAbstract:The paper presents an original Statistical approach dedicated to the evaluation of two time intervals which are useful in various chaotic applications, namely: the transient time and the minimum Statistical Independence sampling distance. The overall procedure relies on Smirnov tests based on two-sample statistic, Kolmogorov-Smirnov tests based on one-sample statistic, a Monte Carlo analysis and an original Statistical Independence test. The experimental study was performed on the logistic map for different values of its parameter, values considered of much interest in the literature. The proposed Statistical approach may guide another experimenter to extend the analysis for other logistic map parameters and also for other chaotic maps.
Shusaku Tsumoto - One of the best experts on this subject based on the ideXlab platform.
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Statistical Independence and determinants in a contingency table interpretation of pearson residuals based on linear algebra
Fundamenta Informaticae, 2009Co-Authors: Shusaku Tsumoto, Shoji HiranoAbstract:This paper analyzes pearson residuals, which is an important element of chi-square test statistic, in a contingency table from the viewpoint of matrix theory as follows. First, a given contingency table is viewed as a matrix and the residual of each element in a matrix are obtained as the difference bewteen observed values and expected values calculated by marginal distributions. Then, each residual σ$_{ij}$ is decomposed into the linear sum of the 2 × 2 subderminants of a original matrix, except for i-th column and j-th row. Furthermore, the number of the determinants is equal to the degree of freedom for the chi-square test statistic for a given contingency table. Thus, 2 × 2 subdeterminants in a contingencymatrix determine the degree of Statistical Independence of two attributes as elementary granules.
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Statistical Independence of multivariate contingency tables
NAFIPS 2009 - 2009 Annual Meeting of the North American Fuzzy Information Processing Society, 2009Co-Authors: Shusaku Tsumoto, Shoji Hirano, Hidenao AbeAbstract:This paper focuses on Statistical Independence of multiple variables from the viewpoint of linear algebra. While information granules of Statistical Independence of two variables can be viewed as determinants of 2 × 2- submatrices, those of three variables consist of several combination s of determinants. However, this combination can be viewed as a linear sum over the all combinarial pairs of 2×2 -matrix, where 2×2 matrix form can be viewed as a fundamental granule for Statistical Independence.
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GrC - Multivariate Statistical Independence and contingency tables
2009 IEEE International Conference on Granular Computing, 2009Co-Authors: Shusaku Tsumoto, Shoji Hirano, Hidenao AbeAbstract:This paper focuses on Statistical Independence of multiple variables from the viewpoint of linear algebra. The residual for odds ratio, which can be viewed as an extension of the determinant of two dimensional contingency matrix, plays an important role in decomposition of multivariate data tables.
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Statistical Independence and contingency matrix
International Conference on Data Mining, 2008Co-Authors: Shusaku Tsumoto, Shoji HiranoAbstract:This paper shows the meaning of Pearson residuals as an indicator of Statistical Independence. While information granules of Statistical Independence of two variables can be viewed as determinants of 2times2-submatrices, those of three variables consist of several combinations of linear equations which will become residuals for odds ratio (outer products) when they are equal to 0. Interestingly, the residuals can be an expansion series of the product of marginal distributions and the residuals for odds ratio (outer products).
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partial Statistical Independence in contingency matrix
IEEE International Conference on Fuzzy Systems, 2008Co-Authors: Shusaku Tsumoto, Shoji HiranoAbstract:This paper focuses on how Statistical Independence can be observed in a contingency table when the table is viewed as a matrix. Statistical Independence in a contingency table is represented as a special form of linear dependence, where all the rows or columns are described by one row or column, respectively. This also means that the rank of the matrix is equal to 1.0. When the rank is equal to 1, we also have some interesting properties corresponding to collinearity in project geometry. Then, we consider the cases where the rank of a given matrix is not full. In these cases, partial Statistical Independence is observed, where at least one row (column) can be represented by linear combinations of other rows (columns).
Shoji Hirano - One of the best experts on this subject based on the ideXlab platform.
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Statistical Independence and determinants in a contingency table interpretation of pearson residuals based on linear algebra
Fundamenta Informaticae, 2009Co-Authors: Shusaku Tsumoto, Shoji HiranoAbstract:This paper analyzes pearson residuals, which is an important element of chi-square test statistic, in a contingency table from the viewpoint of matrix theory as follows. First, a given contingency table is viewed as a matrix and the residual of each element in a matrix are obtained as the difference bewteen observed values and expected values calculated by marginal distributions. Then, each residual σ$_{ij}$ is decomposed into the linear sum of the 2 × 2 subderminants of a original matrix, except for i-th column and j-th row. Furthermore, the number of the determinants is equal to the degree of freedom for the chi-square test statistic for a given contingency table. Thus, 2 × 2 subdeterminants in a contingencymatrix determine the degree of Statistical Independence of two attributes as elementary granules.
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Statistical Independence of multivariate contingency tables
NAFIPS 2009 - 2009 Annual Meeting of the North American Fuzzy Information Processing Society, 2009Co-Authors: Shusaku Tsumoto, Shoji Hirano, Hidenao AbeAbstract:This paper focuses on Statistical Independence of multiple variables from the viewpoint of linear algebra. While information granules of Statistical Independence of two variables can be viewed as determinants of 2 × 2- submatrices, those of three variables consist of several combination s of determinants. However, this combination can be viewed as a linear sum over the all combinarial pairs of 2×2 -matrix, where 2×2 matrix form can be viewed as a fundamental granule for Statistical Independence.
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GrC - Multivariate Statistical Independence and contingency tables
2009 IEEE International Conference on Granular Computing, 2009Co-Authors: Shusaku Tsumoto, Shoji Hirano, Hidenao AbeAbstract:This paper focuses on Statistical Independence of multiple variables from the viewpoint of linear algebra. The residual for odds ratio, which can be viewed as an extension of the determinant of two dimensional contingency matrix, plays an important role in decomposition of multivariate data tables.
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Statistical Independence and contingency matrix
International Conference on Data Mining, 2008Co-Authors: Shusaku Tsumoto, Shoji HiranoAbstract:This paper shows the meaning of Pearson residuals as an indicator of Statistical Independence. While information granules of Statistical Independence of two variables can be viewed as determinants of 2times2-submatrices, those of three variables consist of several combinations of linear equations which will become residuals for odds ratio (outer products) when they are equal to 0. Interestingly, the residuals can be an expansion series of the product of marginal distributions and the residuals for odds ratio (outer products).
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partial Statistical Independence in contingency matrix
IEEE International Conference on Fuzzy Systems, 2008Co-Authors: Shusaku Tsumoto, Shoji HiranoAbstract:This paper focuses on how Statistical Independence can be observed in a contingency table when the table is viewed as a matrix. Statistical Independence in a contingency table is represented as a special form of linear dependence, where all the rows or columns are described by one row or column, respectively. This also means that the rank of the matrix is equal to 1.0. When the rank is equal to 1, we also have some interesting properties corresponding to collinearity in project geometry. Then, we consider the cases where the rank of a given matrix is not full. In these cases, partial Statistical Independence is observed, where at least one row (column) can be represented by linear combinations of other rows (columns).
Bogdan Badea - One of the best experts on this subject based on the ideXlab platform.
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Evaluating the performance of a test-method for Statistical Independence decision in the context of chaotic signals
2016 International Conference on Communications (COMM), 2016Co-Authors: Alexandru Vaduva, Adriana Vlad, Bogdan BadeaAbstract:The current paper addresses the larger field of signal processing, communications and cryptography with an orientation on chaotic signals. We reconsider some aspects concerning the Statistical Independence issue in the context of chaotic signals. We developed a test tool in order to make decisions without the human observer involvement concerning the Statistical Independence of two data sets coming out from continuous random variables with a known or unknown probability law.
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A study on Statistical Independence in the tent map
2009 International Symposium on Signals Circuits and Systems, 2009Co-Authors: Adrian Luca, Adriana Vlad, Bogdan Badea, Madalin FrunzeteAbstract:The paper evaluates, by means of an original Statistical procedure, the minimum sampling distance that enables to extract Statistically independent random variables from the tent map. The experimental results indicate the relationship among the tent map parameter and the Statistical Independence decision. The study may guide the selection of the suitable tent map parameter for different applications where the Statistical Independence is of interest.
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on Statistical Independence in the logistic map a guide to design new chaotic sequences useful in cryptography
International Conference on Computational Science and Its Applications, 2007Co-Authors: Adriana Vlad, Adrian Luca, Bogdan BadeaAbstract:The paper explores the possibility to generate experimental independent and identically distributed data sets starting from the logistic map and discusses its applicability in cryptography. In order to reveal the Statistical Independence in the context of a chaotic signal, and to come up with firm and accurate results, the paper combines usual Statistical methods with an original test procedure useful in the case of continuous random variables of unknown probability law. The overall theoretical approach may be viewed as a guide to generate independent and identically distributed samples starting from the logistic map, and also to design chaotic sequences useful for cryptographic purposes.
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revealing Statistical Independence of two experimental data sets an improvement on spearman s algorithm
Lecture Notes in Computer Science, 2006Co-Authors: Bogdan Badea, Adriana VladAbstract:A high effective Statistical Independence test procedure derived from Spearman's Rank Correlation Test is presented, applicable to all kind of continuous variables (normal or not, even of unknown probability law). Some relevant practical signal processing test examples as well as a Monte Carlo performance comparison with Spearman's Rank Correlation Test capabilities are explained. Besides describing the test procedure algorithm, the paper reveals, from an engineering point of view, some significant aspects concerning the understanding (perception) of the important and not simple concepts, i.e. testing dependence versus Statistical Independence.
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ICCSA (1) - Revealing Statistical Independence of two experimental data sets: an improvement on spearman’s algorithm
Computational Science and Its Applications - ICCSA 2006, 2006Co-Authors: Bogdan Badea, Adriana VladAbstract:A high effective Statistical Independence test procedure derived from Spearman’s Rank Correlation Test is presented, applicable to all kind of continuous variables (normal or not, even of unknown probability law). Some relevant practical signal processing test examples as well as a Monte Carlo performance comparison with Spearman’s Rank Correlation Test capabilities are explained. Besides describing the test procedure algorithm, the paper reveals, from an engineering point of view, some significant aspects concerning the understanding (perception) of the important and not simple concepts, i.e. testing dependence versus Statistical Independence.
Suhadi Suhadi - One of the best experts on this subject based on the ideXlab platform.
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overcoming the Statistical Independence assumption w r t frequency in speech enhancement
International Conference on Acoustics Speech and Signal Processing, 2005Co-Authors: Tim Fingscheidt, Christophe Beaugeant, Suhadi SuhadiAbstract:In this paper, we give a solution on how to overcome the assumption of Statistical Independence of adjacent frequency bins in noise reduction techniques. We show that under relaxed assumptions the problem results in an a-priori SNR estimation problem, where all available noisy speech spectral amplitudes (observations) are exploited. Any state-of-the-art noise power spectral density (psd) estimation and weighting rule can be used - they do not need to be restated. In order to solve for an estimator well suited for real-time applications, we model the a-priori SNR values as Markov processes w.r.t. frequency. On the basis of the formulation by Ephraim and Malah, this leads to a new a-priori SNR estimator that yields fewer musical tones.
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ICASSP (1) - Overcoming the Statistical Independence assumption w.r.t. frequency in speech enhancement
Proceedings. (ICASSP '05). IEEE International Conference on Acoustics Speech and Signal Processing 2005., 1Co-Authors: Tim Fingscheidt, Christophe Beaugeant, Suhadi SuhadiAbstract:In this paper, we give a solution on how to overcome the assumption of Statistical Independence of adjacent frequency bins in noise reduction techniques. We show that under relaxed assumptions the problem results in an a-priori SNR estimation problem, where all available noisy speech spectral amplitudes (observations) are exploited. Any state-of-the-art noise power spectral density (psd) estimation and weighting rule can be used - they do not need to be restated. In order to solve for an estimator well suited for real-time applications, we model the a-priori SNR values as Markov processes w.r.t. frequency. On the basis of the formulation by Ephraim and Malah, this leads to a new a-priori SNR estimator that yields fewer musical tones.
