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"Why should we use white noise analysis? Well, one reason of course is that it fills that earlier gap in the tool kit. As Hida would put it, white noise provides us with a useful set of independent coordinates, parametrized by "time". And there is a feature which makes white noise analysis extremely user-friendly. Typically the physicist — and not only he — sits there with some heuristic ansatz, like e.g. the famous Feynman "integral", wondering whether and how this might make sense mathematically. In many cases the characterization theorem of white noise analysis provides the user with a sweet and easy answer. Feynman's "integral" can now be understood, the "It's all in the vacuum" ansatz of Haag and Coester is now making sense via Dirichlet forms, and so on in many fields of application. There is mathematical finance, there have been applications in biology, and engineering, many more than we could collect in the present volume. Finally, there is one extra benefit: when we internalize the structures of Gaussian white noise analysis we will be ready to meet another close relative. We will enjoy the important similarities and differences which we encounter in the Poisson case, championed in particular by Y Kondratiev and his group. Let us look forward to a companion volume on the uses of Poisson white noise. The present volume is more than a collection of autonomous contributions. The introductory chapter on white noise analysis was made available to the other authors early on for reference and to facilitate conceptual and notational coherence in their work."--Publisher's website.
Why should we use white noise analysis? Well, one reason of course is that it fills that earlier gap in the tool kit. As Hida would put it, white noise provides us with a useful set of independent coordinates, parametrized by 'time'. And there is a feature which makes white noise analysis extremely user-friendly. Typically the physicist — and not only he — sits there with some heuristic ansatz, like e.g. the famous Feynman 'integral', wondering whether and how this might make sense mathematically. In many cases the characterization theorem of white noise analysis provides the user with a sweet and easy answer. Feynman's 'integral' can now be understood, the 'It's all in the vacuum' ansatz of Haag and Coester is now making sense via Dirichlet forms, and so on in many fields of application. There is mathematical finance, there have been applications in biology, and engineering, many more than we could collect in the present volume.Finally, there is one extra benefit: when we internalize the structures of Gaussian white noise analysis we will be ready to meet another close relative. We will enjoy the important similarities and differences which we encounter in the Poisson case, championed in particular by Y Kondratiev and his group. Let us look forward to a companion volume on the uses of Poisson white noise.The present volume is more than a collection of autonomous contributions. The introductory chapter on white noise analysis was made available to the other authors early on for reference and to facilitate conceptual and notational coherence in their work.
NATIONAL BOOK AWARD WINNER • An “eerie, brilliant, and touching” (The New York Times) modern classic about mass culture and the numbing effects of technology. “Tremendously funny . . . A stunning performance from one of our most intelligent novelists.”—The New Republic The inspiration for the award-winning major motion picture starring Adam Driver and Greta Gerwig Jack Gladney teaches Hitler Studies at a liberal arts college in Middle America where his colleagues include New York expatriates who want to immerse themselves in “American magic and dread.” Jack and his fourth wife, Babette, bound by their love, fear of death, and four ultramodern offspring, navigate the usual rocky passages of family life to the background babble of brand-name consumerism. Then a lethal black chemical cloud floats over their lives, an “airborne toxic event” unleashed by an industrial accident. The menacing cloud is a more urgent and visible version of the “white noise” engulfing the Gladney family—radio transmissions, sirens, microwaves, ultrasonic appliances, and TV murmurings—pulsing with life, yet suggesting something ominous.
This volume includes papers by leading mathematicians in the fields of stochastic analysis, white noise theory and quantum information, together with their applications. The papers selected were presented at the International Conference on Stochastic Analysis: Classical and Quantum held at Meijo University, Nagoya, Japan from 1 to 5 November 2004. The large range of subjects covers the latest research in probability theory.
The topics discussed in this book can be classified into three parts: . (i) Gaussian processes. The most general and in fact final representation theory of Gaussian processes is included in this book. This theory is still referred to often and its developments are discussed. (ii) White noise analysis. This book includes the notes of the series of lectures delivered in 1975 at Carleton University in Ottawa. They describe the very original idea of introducing the notion of generalized Brownian functionals (nowadays called OC generalized white noise functionalsOCO, and sometimes OC Hida distributionOCO. (iii) Variational calculus for random fields. This topic will certainly represent one of the driving research lines for probability theory in the next century, as can be seen from several papers in this volume. Sample Chapter(s). Chapter 1: Analysis of Brownian Functionals (1,502 KB). Contents: General Theory of White Noise Functionals; Gaussian and Other Processes; Infinite Dimensional Harmonic Analysis and Rotation Group; Quantum Theory; Feynman Integrals and Random Fields; Variational Calculus and Random Fields; Application to Biology. Readership: Graduate students and researchers in the fields of probability theory, functional analysis, statistics and theoretical physics."
Inventive Engineering is an emerging engineering science focused on the conceptual designing processes whereby creative, or inventive, designs are developed. Its core concepts are too often unknown and even surprising, but they are also feasible and can be learned, leading to potentially patentable designs. Inventive engineers have a tremendou
This practical book for use in Reformed worship boasts a collection of highly engaging prayers written by current Presbyterian pastors and theologians. Unique amidst most prayer books, the language of these prayers is conversational in tone, rather than formal, and their concerns represent a diversity of approaches. Divided into sections by seasons of the liturgical year, Let Us Pray includes prayers of confession, petition, intercession, and thanksgiving, as well as assurances of pardon, litanies, and calls to worship.
This Springer brief provides the necessary foundations to understand differential privacy and describes practical algorithms enforcing this concept for the publication of real-time statistics based on sensitive data. Several scenarios of interest are considered, depending on the kind of estimator to be implemented and the potential availability of prior public information about the data, which can be used greatly to improve the estimators' performance. The brief encourages the proper use of large datasets based on private data obtained from individuals in the world of the Internet of Things and participatory sensing. For the benefit of the reader, several examples are discussed to illustrate the concepts and evaluate the performance of the algorithms described. These examples relate to traffic estimation, sensing in smart buildings, and syndromic surveillance to detect epidemic outbreaks.
This is the first book at the graduate textbook level to discuss analyzing financial data with S-PLUS. Its originality lies in the introduction of tools for the estimation and simulation of heavy tail distributions and copulas, the computation of measures of risk, and the principal component analysis of yield curves. The book is aimed at undergraduate students in financial engineering; master students in finance and MBA's, and to practitioners with financial data analysis concerns.
These Proceedings contain invited lectures presented at the third Interna tional Conference on "Irreversible Processes and Dissipative Structures" in Kiihlungsborn (German Democratic Republic) in March, 1985. These con ferences, the first of which was held in Rostock in 1977 and the second in Berlin in 1982, are devoted to the study of irreversible processes far from thermal equilibrium and to the phenomena of selforganization. The meet ing in Kiihlungsborn brought together some 160 mathematicians, physicists, chemists and biologists from 10 countries, who are all interested in the inter disciplinary field of synergetics. The main topics of the conference were basic concepts of selforganization and evolution, such as entropy, instabilities, nucleation, dissipative struc tures, chaos and turbulence. The contributions cover methods from ther modynamics, the theory of dynamic systems, stochastic and statistic theory, the method of Green's functions, the fluctuation-dissipation theorem, etc. Several problems are studied in more detail, e.g., the kinetics of nucleation especially in finite systems, the dynamics of interfaces, reaction-diffusion sys tems, chemical and biochemical pattern formation and information process ing. Further, several contributions are devoted to the development of the concepts of chaos and turbulence. The editors hope that the contributions collected in this volume will pro vide some new information about the field of selforganization, which is in full development now.