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The second virial coefficient is a relevant property for determining the effect of the non-ideality of real gases, applicable to the vast majority of existing chemical and industrial processes. An Analysis of the most relevant correlations, based on a new approach. This book can be used by students, researchers and professionals interested in a both the fundamentals and the most advanced aspects of the subjects, as well as in the application to chemical process calculations.

Boyle's Temperature --- Second Virial Coefficient --- Gases --- Molecules --- Virial Coefficients --- Models --- Chemical Technology

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This monograph covers dynamical inverse problems, that is problems whose data are the values of wave fields. It deals with the problem of determination of one or more coefficients of a hyperbolic equation or a system of hyperbolic equations. The desired coefficients are functions of point. Most attention is given to the case where the required functions depend only on one coordinate. The first chapter of the book deals mainly with methods of solution of one-dimensional inverse problems. The second chapter focuses on scalar inverse problems of wave propagation in a layered medium. In the final chapter inverse problems for elasticity equations in stratified media and acoustic equations for moving media are given.

Wave-motion, Theory of. --- Undulatory theory --- Mechanics --- Acoustic Equations. --- Coefficients. --- Determination. --- Dynamical Inverse Problems. --- Elasticity Equations. --- Functions of Point. --- Hyperbolic Equations. --- One-dimensional Inverse Problems. --- Scalar Inverse Problems. --- Wave Fields. --- Wave Propagation.

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"Modular forms are tremendously important in various areas of mathematics, from number theory and algebraic geometry to combinatorics and lattices. Their Fourier coefficients, with Ramanujan's tau-function as a typical example, have deep arithmetic significance. Prior to this book, the fastest known algorithms for computing these Fourier coefficients took exponential time, except in some special cases. The case of elliptic curves (Schoof's algorithm) was at the birth of elliptic curve cryptography around 1985. This book gives an algorithm for computing coefficients of modular forms of level one in polynomial time. For example, Ramanujan's tau of a prime number P can be computed in time bounded by a fixed power of the logarithm of P. Such fast computation of Fourier coefficients is itself based on the main result of the book: the computation, in polynomial time, of Galois representations over finite fields attached to modular forms by the Langlands program. Because these Galois representations typically have a nonsolvable image, this result is a major step forward from explicit class field theory, and it could be described as the start of the explicit Langlands program. The computation of the Galois representations uses their realization, following Shimura and Deligne, in the torsion subgroup of Jacobian varieties of modular curves. The main challenge is then to perform the necessary computations in time polynomial in the dimension of these highly nonlinear algebraic varieties. Exact computations involving systems of polynomial equations in many variables take exponential time. This is avoided by numerical approximations with a precision that suffices to derive exact results from them. Bounds for the required precision--in other words, bounds for the height of the rational numbers that describe the Galois representation to be computed--are obtained from Arakelov theory. Two types of approximations are treated: one using complex uniformization and another one using geometry over finite fields. The book begins with a concise and concrete introduction that makes its accessible to readers without an extensive background in arithmetic geometry. And the book includes a chapter that describes actual computations"-- "This book represents a major step forward from explicit class field theory, and it could be described as the start of the 'explicit Langlands program'"--

Galois modules (Algebra) --- Class field theory. --- Algebraic number theory --- Galois module structure (Algebra) --- Galois's modules (Algebra) --- Modules (Algebra) --- Arakelov invariants. --- Arakelov theory. --- Fourier coefficients. --- Galois representation. --- Galois representations. --- Green functions. --- Hecke operators. --- Jacobians. --- Langlands program. --- Las Vegas algorithm. --- Lehmer. --- Peter Bruin. --- Ramanujan's tau function. --- Ramanujan's tau-function. --- Ramanujan's tau. --- Riemann surfaces. --- Schoof's algorithm. --- Turing machines. --- algorithms. --- arithmetic geometry. --- arithmetic surfaces. --- bounding heights. --- bounds. --- coefficients. --- complex roots. --- computation. --- computing algorithms. --- computing coefficients. --- cusp forms. --- cuspidal divisor. --- eigenforms. --- finite fields. --- height functions. --- inequality. --- lattices. --- minimal polynomial. --- modular curves. --- modular forms. --- modular representation. --- modular representations. --- modular symbols. --- nonvanishing conjecture. --- p-adic methods. --- plane curves. --- polynomial time algorithm. --- polynomial time algoriths. --- polynomial time. --- polynomials. --- power series. --- probabilistic polynomial time. --- random divisors. --- residual representation. --- square root. --- square-free levels. --- tale cohomology. --- torsion divisors. --- torsion.

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This book was published in 2004. The estimation of noisily observed states from a sequence of data has traditionally incorporated ideas from Hilbert spaces and calculus-based probability theory. As conditional expectation is the key concept, the correct setting for filtering theory is that of a probability space. Graduate engineers, mathematicians and those working in quantitative finance wishing to use filtering techniques will find in the first half of this book an accessible introduction to measure theory, stochastic calculus, and stochastic processes, with particular emphasis on martingales and Brownian motion. Exercises are included. The book then provides an excellent users' guide to filtering: basic theory is followed by a thorough treatment of Kalman filtering, including recent results which extend the Kalman filter to provide parameter estimates. These ideas are then applied to problems arising in finance, genetics and population modelling in three separate chapters, making this a comprehensive resource for both practitioners and researchers.

Kalman filtering --- Measure theory --- 305.974 --- AA / International- internationaal --- Lebesgue measure --- Measurable sets --- Measure of a set --- Algebraic topology --- Integrals, Generalized --- Measure algebras --- Rings (Algebra) --- Filtering, Kalman --- Control theory --- Estimation theory --- Prediction theory --- Stochastic processes --- Time varying coefficients. Kalman Filter --- Measure theory. --- Kalman filtering.

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In this book, Andrew Harvey sets out to provide a unified and comprehensive theory of structural time series models. Unlike the traditional ARIMA models, structural time series models consist explicitly of unobserved components, such as trends and seasonals, which have a direct interpretation. As a result the model selection methodology associated with structural models is much closer to econometric methodology. The link with econometrics is made even closer by the natural way in which the models can be extended to include explanatory variables and to cope with multivariate time series. From the technical point of view, state space models and the Kalman filter play a key role in the statistical treatment of structural time series models. The book includes a detailed treatment of the Kalman filter. This technique was originally developed in control engineering, but is becoming increasingly important in fields such as economics and operations research. This book is concerned primarily with modelling economic and social time series, and with addressing the special problems which the treatment of such series poses. The properties of the models and the methodological techniques used to select them are illustrated with various applications. These range from the modellling of trends and cycles in US macroeconomic time series to to an evaluation of the effects of seat belt legislation in the UK.

Time-series analysis --- Mathematical statistics --- Kalman filtering --- Kalman, filtrage de --- Série chronologique --- Time-series analysis. --- Kalman filtering. --- Filtering, Kalman --- Analysis of time series --- Control theory --- Estimation theory --- Prediction theory --- Stochastic processes --- Autocorrelation (Statistics) --- Harmonic analysis --- Probabilities --- 304.5 --- 305.974 --- AA / International- internationaal --- Techniek van de statistische-econometrische voorspellingen. Prognose in de econometrie --- Time varying coefficients. Kalman Filter --- Séries chronologiques --- Economic forecasting --- Prévision économique --- Time series analysis