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What does it mean to produce resemblance in the performance of written music? Starting from how this question is commonly answered by the practice of interpretation in Western notated art music, this book proposes a move beyond commonly accepted codes, conventions and territories of music performance. Appropriating reflections from post-structural philosophy, visual arts and semiotics, and crucially based upon an artistic research project with a strong creative and practical component, it proposes a new approach to music performance. The approach is based on divergence, on the difference produced by intensifying the chasm between the symbolic aspect of music notation and the irreducible materiality of performance. Instead of regarding performance as reiteration, reconstruction and reproduction of past musical works, 'Powers of Divergence' emphasises its potential for the emergence of the new and for the problematisation of the limits of musical semiotics.
What does it mean to produce resemblance in the performance of written music? Starting from how this question is commonly answered by the practice of interpretation in Western notated art music, this book proposes a move beyond commonly accepted codes, conventions and territories of music performance. Appropriating reflections from post-structural philosophy, visual arts and semiotics, and crucially based upon an artistic research project with a strong creative and practical component, it proposes a new approach to music performance. The approach is based on divergence, on the difference produced by intensifying the chasm between the symbolic aspect of music notation and the irreducible materiality of performance. Instead of regarding performance as reiteration, reconstruction and reproduction of past musical works, Powers of Divergence emphasises its potential for the emergence of the new and for the problematisation of the limits of musical semiotics.
Statistical Inference Based on Divergence Measures by Leandro Pardo Pdf
The idea of using functionals of Information Theory, such as entropies or divergences, in statistical inference is not new. However, in spite of the fact that divergence statistics have become a very good alternative to the classical likelihood ratio test and the Pearson-type statistic in discrete models, many statisticians remain unaware of this p
New Developments in Statistical Information Theory Based on Entropy and Divergence Measures by Leandro Pardo Pdf
This book presents new and original research in Statistical Information Theory, based on minimum divergence estimators and test statistics, from a theoretical and applied point of view, for different statistical problems with special emphasis on efficiency and robustness. Divergence statistics, based on maximum likelihood estimators, as well as Wald’s statistics, likelihood ratio statistics and Rao’s score statistics, share several optimum asymptotic properties, but are highly non-robust in cases of model misspecification under the presence of outlying observations. It is well-known that a small deviation from the underlying assumptions on the model can have drastic effect on the performance of these classical tests. Specifically, this book presents a robust version of the classical Wald statistical test, for testing simple and composite null hypotheses for general parametric models, based on minimum divergence estimators.
Trading with the Trendlines - The Power of Divergence by David Carli Pdf
"The Power of Divergence" is the second volume of the series "Trading with the Trendlines." The book explains a strategy applicable in every market (forex, equities, commodity...), and it is a combination of divergence, trendline, and a little of Fibonacci; a simple strategy that seeks to exploit the reversal of a market. What you will read in the book, is a correct way to use the divergences, in particular, the one between the price and Commodity Channel Index (CCI). Every aspect is well explained, including the proper position sizing, with many examples. Easy and clear is the identification of the target profit and stop-loss of the strategy. Not only. Depending on your account, I will also explain to you the correct position sizing, for proper money management. If you are a beginner, do not worry; the first two chapters will provide you with adequate knowledge for understanding the strategy and using it correctly. Do not be tricked by the fact that the book is free. The strategy, if you use it correctly and with money management appropriate to your account, will give you a high percentage of profitable trades. However, it is recommended to combine the strategy with the fundamental analysis and open a position only if both give the same signal.
Minimum Divergence Methods in Statistical Machine Learning by Shinto Eguchi,Osamu Komori Pdf
This book explores minimum divergence methods of statistical machine learning for estimation, regression, prediction, and so forth, in which we engage in information geometry to elucidate their intrinsic properties of the corresponding loss functions, learning algorithms, and statistical models. One of the most elementary examples is Gauss's least squares estimator in a linear regression model, in which the estimator is given by minimization of the sum of squares between a response vector and a vector of the linear subspace hulled by explanatory vectors. This is extended to Fisher's maximum likelihood estimator (MLE) for an exponential model, in which the estimator is provided by minimization of the Kullback-Leibler (KL) divergence between a data distribution and a parametric distribution of the exponential model in an empirical analogue. Thus, we envisage a geometric interpretation of such minimization procedures such that a right triangle is kept with Pythagorean identity in the sense of the KL divergence. This understanding sublimates a dualistic interplay between a statistical estimation and model, which requires dual geodesic paths, called m-geodesic and e-geodesic paths, in a framework of information geometry. We extend such a dualistic structure of the MLE and exponential model to that of the minimum divergence estimator and the maximum entropy model, which is applied to robust statistics, maximum entropy, density estimation, principal component analysis, independent component analysis, regression analysis, manifold learning, boosting algorithm, clustering, dynamic treatment regimes, and so forth. We consider a variety of information divergence measures typically including KL divergence to express departure from one probability distribution to another. An information divergence is decomposed into the cross-entropy and the (diagonal) entropy in which the entropy associates with a generative model as a family of maximum entropy distributions; the cross entropy associates with a statistical estimation method via minimization of the empirical analogue based on given data. Thus any statistical divergence includes an intrinsic object between the generative model and the estimation method. Typically, KL divergence leads to the exponential model and the maximum likelihood estimation. It is shown that any information divergence leads to a Riemannian metric and a pair of the linear connections in the framework of information geometry. We focus on a class of information divergence generated by an increasing and convex function U, called U-divergence. It is shown that any generator function U generates the U-entropy and U-divergence, in which there is a dualistic structure between the U-divergence method and the maximum U-entropy model. We observe that a specific choice of U leads to a robust statistical procedure via the minimum U-divergence method. If U is selected as an exponential function, then the corresponding U-entropy and U-divergence are reduced to the Boltzmann-Shanon entropy and the KL divergence; the minimum U-divergence estimator is equivalent to the MLE. For robust supervised learning to predict a class label we observe that the U-boosting algorithm performs well for contamination of mislabel examples if U is appropriately selected. We present such maximal U-entropy and minimum U-divergence methods, in particular, selecting a power function as U to provide flexible performance in statistical machine learning.
Analysis of Divergence by William Bray,Caslav Stanojevic Pdf
The 7th International Workshop in Analysis and its Applications (IWAA) was held at the University of Maine, June 1-6, 1997 and featured approxi mately 60 mathematicians. The principal theme of the workshop shares the title of this volume and the latter is a direct outgrowth of the workshop. IWAA was founded in 1984 by Professor Caslav V. Stanojevic. The first meeting was held in the resort complex Kupuri, Yugoslavia, June 1-10, 1986, with two pilot meetings preceding. The Organization Committee to gether with the Advisory Committee (R. P. Boas, R. R. Goldberg, J. P. Kahne) set forward the format and content of future meetings. A certain number of papers were presented that later appeared individually in such journals as the Proceedings of the AMS, Bulletin of the AMS, Mathematis chen Annalen, and the Journal of Mathematical Analysis and its Applica tions. The second meeting took place June 1-10, 1987, at the same location. At the plenary session of this meeting it was decided that future meetings should have a principal theme. The theme for the third meeting (June 1- 10, 1989, Kupuri) was Karamata's Regular Variation. The principal theme for the fourth meeting (June 1-10, 1990, Kupuri) was Inner Product and Convexity Structures in Analysis, Mathematical Physics, and Economics. The fifth meeting was to have had the theme, Analysis and Foundations, organized in cooperation with Professor A. Blass (June 1-10, 1991, Kupuri).
Goodness-of-Fit Statistics for Discrete Multivariate Data by Timothy R.C. Read,Noel A.C. Cressie Pdf
The statistical analysis of discrete multivariate data has received a great deal of attention in the statistics literature over the past two decades. The develop ment ofappropriate models is the common theme of books such as Cox (1970), Haberman (1974, 1978, 1979), Bishop et al. (1975), Gokhale and Kullback (1978), Upton (1978), Fienberg (1980), Plackett (1981), Agresti (1984), Goodman (1984), and Freeman (1987). The objective of our book differs from those listed above. Rather than concentrating on model building, our intention is to describe and assess the goodness-of-fit statistics used in the model verification part of the inference process. Those books that emphasize model development tend to assume that the model can be tested with one of the traditional goodness-of-fit tests 2 2 (e.g., Pearson's X or the loglikelihood ratio G ) using a chi-squared critical value. However, it is well known that this can give a poor approximation in many circumstances. This book provides the reader with a unified analysis of the traditional goodness-of-fit tests, describing their behavior and relative merits as well as introducing some new test statistics. The power-divergence family of statistics (Cressie and Read, 1984) is used to link the traditional test statistics through a single real-valued parameter, and provides a way to consolidate and extend the current fragmented literature. As a by-product of our analysis, a new 2 2 statistic emerges "between" Pearson's X and the loglikelihood ratio G that has some valuable properties.
Hand-books of Natural Philosophy and Astronomy: Mechanics. Hydrostatics, hydraulics, pneumatics, and sound. Optics.- v. 2. Heat. Magnetism, common electricity, and voltaic electricity.- v. 3. Meteorology. Astronomy by Dionysius Lardner Pdf
From the bestselling author of The Ascent of Money and The Square and the Tower “A dazzling history of Western ideas.” —The Economist “Mr. Ferguson tells his story with characteristic verve and an eye for the felicitous phrase.” —Wall Street Journal “[W]ritten with vitality and verve . . . a tour de force.” —Boston Globe Western civilization’s rise to global dominance is the single most important historical phenomenon of the past five centuries. How did the West overtake its Eastern rivals? And has the zenith of Western power now passed? Acclaimed historian Niall Ferguson argues that beginning in the fifteenth century, the West developed six powerful new concepts, or “killer applications”—competition, science, the rule of law, modern medicine, consumerism, and the work ethic—that the Rest lacked, allowing it to surge past all other competitors. Yet now, Ferguson shows how the Rest have downloaded the killer apps the West once monopolized, while the West has literally lost faith in itself. Chronicling the rise and fall of empires alongside clashes (and fusions) of civilizations, Civilization: The West and the Rest recasts world history with force and wit. Boldly argued and teeming with memorable characters, this is Ferguson at his very best.
Laser-Induced Damage of Optical Materials by Roger M. Wood Pdf
The laser power handling capacities of optical systems are determined by the physical properties of their component materials. At low intensity levels these factors are not important, but an understanding of damage mechanisms is fundamental to good design of laser products operating at high power. Laser Induced Damage of Optical Materials presents
