Noise Theory And Application To Physics

This is a unique approach to noise theory and its application to physical measurements that will find its place among the graduate course books. In a very systematic way, the foundations are laid and applied in a way that the book will also be useful to those not focusing on optics. Exercises and solutions help students to deepen their knowledge.

The study of phase transitions is among the most fascinating fields in physics. Originally limited to transition phenomena in equilibrium systems, this field has outgrown its classical confines during the last two decades. The behavior of far from equilibrium systems has received more and more attention and has been an extremely active and productive subject of research for physicists, chemists and biologists. Their studies have brought about a more unified vision of the laws which govern self-organization processes of physico-chemical and biological sys tems. A major achievement has been the extension of the notion of phase transi tion to instabilities which occur only in open nonlinear systems. The notion of phase transition has been proven fruitful in apphcation to nonequilibrium ins- bihties known for about eight decades, like certain hydrodynamic instabilities, as well as in the case of the more recently discovered instabilities in quantum optical systems such as the laser, in chemical systems such as the Belousov-Zhabotinskii reaction and in biological systems. Even outside the realm of natural sciences, this notion is now used in economics and sociology. In this monograph we show that the notion of phase transition can be extend ed even further. It apphes also to a new class of transition phenomena which occur only in nonequilibrium systems subjected to a randomly fluctuating en vironment.

Based on the author’s own research, this book rigorously and systematically develops the theory of Gaussian white noise measures on Hilbert spaces to provide a comprehensive account of nonlinear filtering theory. Covers Markov processes, cylinder and quasi-cylinder probabilities and conditional expectation as well as predictio0n and smoothing and the varied processes used in filtering. Especially useful for electronic engineers and mathematical statisticians for explaining the systematic use of finely additive white noise theory leading to a more simplified and direct presentation.

For a physicist noise is not just about sounds. It refers to any random physical process that blurs measurements and, in so doing, stands in the way of scientific knowledge. This short book deals with the most common types of noise, their properties, and some of their unexpected virtues. The text assumes that the reader knows the basics of probability theory and explains the most useful mathematical concepts related to noise. Finally, it aims at making this subject more widely known, and stimulating interest in its study in young physicists.

Stochastic Resonance: Theory and Applications deals with the theory of noise-added systems and in particular with Stochastic Resonance, a quite novel theory that was introduced in the 1980s to provide better understanding of some natural phenomena (e.g. ice age recurrence). Following the very first works, a number of different applications to both natural and human-produced phenomena were proposed. The book aims to improve the understanding of noise-based techniques and to focus on practical applications of this class of phenomena (an aspect that has been very poorly investigated up to now). Based on this objective, the book is roughly divided into two parts. The first part deals with the essential theory of noise-added systems and in particular a new approach to noise-added techniques that allows a number of strategies proposed in previous years to be unified. The proposed approach also allows real-time control of the noise characteristics, assuring optimal system performance. In the second part a large number of applications are described in detail in the field of electric and electronic devices, with the aim of allowing readers to build their own experimental set. The book comes with a diskette of educational software that the authors developed. Stochastic Resonance: Theory and Applications is an invaluable reference for students, researchers and engineering professionals working in the fields of electric and electronic measurements, electronics and signal theory.

​​Since the parameters in dynamical systems of biological interest are inherently positive and bounded, bounded noises are a natural way to model the realistic stochastic fluctuations of a biological system that are caused by its interaction with the external world. Bounded Noises in Physics, Biology, and Engineering is the first contributed volume devoted to the modeling of bounded noises in theoretical and applied statistical mechanics, quantitative biology, and mathematical physics. It gives an overview of the current state-of-the-art and is intended to stimulate further research. The volume is organized in four parts. The first part presents the main kinds of bounded noises and their applications in theoretical physics. The theory of bounded stochastic processes is intimately linked to its applications to mathematical and statistical physics, and it would be difficult and unnatural to separate the theory from its physical applications. The second is devoted to framing bounded noises in the theory of random dynamical systems and random bifurcations, while the third is devoted to applications of bounded stochastic processes in biology, one of the major areas of potential applications of this subject. The final part concerns the application of bounded stochastic processes in mechanical and structural engineering, the area where the renewed interest for non-Gaussian bounded noises started. Pure mathematicians working on stochastic calculus will find here a rich source of problems that are challenging from the point of view of contemporary nonlinear analysis. Bounded Noises in Physics, Biology, and Engineering is intended for scientists working on stochastic processes with an interest in both fundamental issues and applications. It will appeal to a broad range of applied mathematicians, mathematical biologists, physicists, engineers, and researchers in other fields interested in complexity theory. It is accessible to anyone with a working knowledge of stochastic modeling, from advanced undergraduates to senior researchers.

Turbulence takes place in most flow situations whethertheyoccur naturally or in technological systems. Therefore, considerable effort is being expended in an attempt to understand the phenomenon of turbulence. The recent discovery ofcoherent structure in turbulent shear flows and the modem developments in computer capabilities have revolutionized research work in turbulence. There is a strong evidence that the coherent structure in turbulent shear flows is reminiscent of nonlinear stability waves. As such, the interest in nonlinear stability waves has increased not only for the understandingofthe latterstages of the laminar-turbulent transition process, but also for understanding the coherent structures in turbulent flows. Also. the advances in computers have made direct numerical simulation possible at Low-Reynolds numbers and large-eddy simulation possible at high Reynolds numbers. This made first-principles prediction of turbulence-generated noise feasible. Therefore, this book aims at presenting a graduate-level introductory study of turbulence while accounting for such recent views of concern to researchers. This book is an outgrowth oflecture notes on the subject offered to graduate students in engineering. The book should be of interest to research engineers and graduatestudents in science and engineering. The theoretical basis presented is sufficient not only for studying the specialized literature on turbulence but also for theoretical investigations on the subject.

This book investigates the impact of noise upon the emergence and sustenance of patterns. ?Patterns? loosely refers to coherent spatial structures, including fronts, as well as temporal patterns. The crucial role of nonlinearities is highlighted and expanded upon in the context of dynamical system frameworks. The author's familiarity with chaos theory, statistical physics and nonlinear science is reflected in the highly interdisciplinary character of the text. Model equations and experiments taken from fluid dynamics, semiconductor devices, biophysics and statistical mechanics complement theoretical concepts.It should be of great value to researchers and graduate students who desire a quick introduction to the subject. Excursions into emerging fields such as traffic flow simulations and game theory serve to broaden the scope and to encourage the exploration of sundry topics.