Bücher veröffentlicht von Springer New York

This introduction to random variables and signals is intended to provide engineering students with the analytical and computational tools for processing random signals using linear systems. It presents the underlying theory as well as examples and applications using computational aids throughout, in particular, computer-based symbolic computation programs are used for performing the analytical manipulations and the numerical calculations. Intended for a one-semester course for advanced undergraduates or beginning graduate students, the book covers such topics as: set theory and an introduction to probability; random variables, distributions, and processes; deterministic signals, spectral properties, and transformations; and filtering, and detection theory. The large number of worked examples together with the programming aids provided on the CD make the book eminently suited for self study as well as classroom use.

In the last decades the subject of nonsmooth analysis has grown rapidly due to the recognition that nondifferentiable phenomena are more widespread, and play a more important role, than had been thought. In recent years, it has come to play a role in functional analysis, optimization, optimal design, mechanics and plasticity, differential equations, control theory, and, increasingly, in analysis. This volume presents the essentials of the subject clearly and succinctly, together with some of its applications and a generous supply of interesting exercises. The book begins with an introductory chapter which gives the reader a sampling of what is to come while indicating at an early stage why the subject is of interest. The next three chapters constitute a course in nonsmooth analysis and identify a coherent and comprehensive approach to the subject leading to an efficient, natural, yet powerful body of theory. The last chapter, as its name implies, is a self-contained introduction to the theory of control of ordinary differential equations. End-of-chapter problems also offer scope for deeper understanding. The authors have incorporated in the text a number of new results which clarify the relationships between the different schools of thought in the subject. Their goal is to make nonsmooth analysis accessible to a wider audience. In this spirit, the book is written so as to be used by anyone who has taken a course in functional analysis.

As the new title indicates, this second edition of Log-Linear Models has been modi?ed to place greater emphasis on logistic regression. In addition to new material, the book has been radically rearranged. The fundamental material is contained in Chapters 1-4. Intermediate topics are presented in Chapters 5 through 8. Generalized linear models are presented in Ch- ter 9. The matrix approach to log-linear models and logistic regression is presented in Chapters 10-12, with Chapters 10 and 11 at the applied Ph.D. level and Chapter 12 doing theory at the Ph.D. level. The largest single addition to the book is Chapter 13 on Bayesian bi- mial regression. This chapter includes not only logistic regression but also probit and complementary log-log regression. With the simplicity of the Bayesian approach and the ability to do (almost) exact small sample s- tistical inference, I personally ?nd it hard to justify doing traditional large sample inferences. (Another possibility is to do exact conditional inference, but that is another story.) Naturally,Ihavecleaneduptheminor?awsinthetextthatIhavefound. All examples, theorems, proofs, lemmas, etc. are numbered consecutively within each section with no distinctions between them, thus Example 2.3.1 willcomebeforeProposition2.3.2.Exercisesthatdonotappearinasection at the end have a separate numbering scheme. Within the section in which it appears, an equation is numbered with a single value, e.g., equation (1).

This book is meant as a text for a first year graduate course in analysis. Any standard course in undergraduate analysis will constitute sufficient preparation for its understanding, for instance, my Undergraduate Anal- ysis. I assume that the reader is acquainted with notions of uniform con- vergence and the like. In this third edition, I have reorganized the book by covering inte- gration before functional analysis. Such a rearrangement fits the way courses are taught in all the places I know of. I have added a number of examples and exercises, as well as some material about integration on the real line (e.g. on Dirac sequence approximation and on Fourier analysis), and some material on functional analysis (e.g. the theory of the Gelfand transform in Chapter XVI). These upgrade previous exercises to sections in the text. In a sense, the subject matter covers the same topics as elementary calculus, viz. linear algebra, differentiation and integration. This time, however, these subjects are treated in a manner suitable for the training of professionals, i.e. people who will use the tools in further investiga- tions, be it in mathematics, or physics, or what have you. In the first part, we begin with point set topology, essential for all analysis, and we cover the most important results.

This book teaches introductory computer programming using Maple, offering more mathematically oriented exercises and problems than those found in traditional programming courses, while reinforcing and applying concepts and techniques of calculus. Includes case studies.

Analysis and Simulation of Chaotic Systems is a text designed to be used at the graduate level in applied mathematics for students from mathematics, engineering, physics, chemistry and biology. The book can be used as a stand-alone text for a full year course or it can be heavily supplemented with material of more mathematical, more engineering or more scientific nature. Computations and computer simulations are used throughout this text to illustrate phenomena discussed and to supply readers with probes to use on new problems.

A key experiment in biomedical research is monitoring the expression of different proteins in order to detect changes that occur in biological systems under different experimental conditions. The method that is most widely used is the Western blot analysis. While Western blot is a workhorse in laboratories studying protein expression and has several advantages, it also has a number of significant limitations. In particular, the method is semi-quantitative with limited dynamic range. Western blot focuses on a single protein per sample with only a small number of representative samples analyzed in an experiment. New quantitative tools have been needed for some time to at least supplement, & possibly replace, the Western blot. Mass spectrometric methods have begun to compete with Western blot for routine quantitative analyses of proteins. One of these methods is based on the tandem mass spectrometry technique of selected reaction monitoring (SRM), which is also called multiple reaction monitoring (MRM). Selected reaction monitoring is actually an older tandem mass spectrometry technique, first described in the late 70s, that is widely utilized in the quantitative analysis of small molecules like drugs & metabolites. The use of selected reaction monitoring for the quantitative analysis of proteins has a number of advantages. Most importantly, it is fundamentally quantitative with a wide dynamic range. The output of the analysis is a numerical result that can range over several orders of magnitude. Other advantages include sufficient specificity & sensitivity to detect low abundance proteins in complex mixtures. Finally, selected reaction monitoring can be multiplexed to allow the quantitative analysis of relatively large numbers of proteins in a single sample in a single experiment. This Brief will explain both the theoretical & experimental details of the selected reaction monitoring experiment as it is applied to proteins.

The eigenvalue problems for quasilinear and nonlinear operators present many differences with the linear case, and a Lyapunov inequality for quasilinear resonant systems showed the existence of eigenvalue asymptotics driven by the coupling of the equations instead of the order of the equations. For p=2, the coupling and the order of the equations are the same, so this cannot happen in linear problems. Another striking difference between linear and quasilinear second order differential operators is the existence of Lyapunov-type inequalities in R^n when p>n. Since the linear case corresponds to p=2, for the usual Laplacian there exists a Lyapunov inequality only for one-dimensional problems. For linear higher order problems, several Lyapunov-type inequalities were found by Egorov and Kondratiev and collected in On spectral theory of elliptic operators, Birkhauser Basel 1996. However, there exists an interesting interplay between the dimension of the underlying space, the order of the differential operator, the Sobolev space where the operator is defined, and the norm of the weight appearing in the inequality which is not fully developed. Also, the Lyapunov inequality for differential equations in Orlicz spaces can be used to develop an oscillation theory, bypassing the classical sturmian theory which is not known yet for those equations. For more general operators, like the p(x) laplacian, the possibility of existence of Lyapunov-type inequalities remains unexplored.

This brief examines resource allocation and interference management for 4G femtocells. It introduces 4G femtocells in the context of 4G mobile networks and discusses related technical challenges in resource allocation and interference management. Topics include ant colony algorithm based downlink resource allocation, intelligent scheduling and power control, uplink and downlink for two-tier networks, quality of service (QoS) constraints and the cross-tier interference constraint. The authors present algorithms to alleviate common femtocell-related problems such as subchannel power allocation. The complexity of the proposed resource allocation algorithms is analyzed, and the effectiveness of the proposed algorithms is verified by simulations. This concise and practical book directly addresses common problems relating to femtocells and resource management. It serves as a useful tool for researchers in the field. Advanced-level students or professionals interested in femtocells and networks will also find the content helpful.

The primary focus of this thesis is to theoretically describe nanokelvin experiments in cold atomic gases, which offer the potential to revolutionize our understanding of strongly correlated many-body systems. The thesis attacks major challenges of the field: it proposes and analyzes experimental protocols to create new and interesting states of matter and introduces theoretical techniques to describe probes of these states. The phenomena considered include the fractional quantum Hall effect, spectroscopy of strongly correlated states, and quantum criticality, among others. The thesis also clarifies experiments on disordered quantum solids, which display a variety of exotic phenomena and are candidates to exhibit so-called "e;supersolidity."e; It collects experimental results and constrains their interpretation through theoretical considerations.This Doctoral Thesis has been accepted by Cornell University, Ithaca, USA.

This book introduces readers to Next Generation Sequencing applications in medical genetics. The authors discuss the direct application of next-generation sequencing to medicine, specifically, laboratory medicine or molecular diagnostics. The first part of the book contains chapters on sanger sequencing, NGS technologies, targeted-amplification and capture, and exome sequencing. The second part of the book focuses on genetic disorders diagnoses by NGS, prenatal diagnosis, muscular dystrophies, mitochondrial disorders diagnosis, and challenges in molecular diagnosis. Recent developments and potential future trends in NGS sequencing applications are highlighted, as well.

A primer on the evolution of particle physics and the search for the fundamental building blocks of matter. The book presents the full current body of understanding of particle physics in way accessible to a reader with some basic principles of physics (energy, momentum, electrical charge). This concise book tells the fascinating story of how 20th century physicists revealed layer upon layer of structure within the atom to reach the basic particles of matter, and then culminates in descriptions of current theories which form the Standard Model and the discovery of the top quark. Includes chapters on cosmology. Book includes many illustrations and photographs, and integrates the stories of the individual scientists throughout. Includes 4 color photographs, and the famous "Particle Chart". The book is a collaboration among eminent physicists (including J.D. Jackson and G. Goldhaber) at LBL, CERN and high school teachers in the Contemporary Physics Education Project to develop a novel book to teach particle physics to students.Book can thus be used as a supplement for courses in advanced high school and physics courses.

The first edition of this book was well received by updated. The two of us have made further collab- orative efforts to present a better understanding of medical students, graduate students, and clinicians interested in furthering their understanding of basic the function of the kidney in conjunction with the principles of renal physiology. Most of the reviews most recent anatomical findings. of the first edition and comments from the various The second edition consists of 13 Chapters and 3 instructors who used the book were very positive Appendices. As in the first edition, the anatomical and complimentary with regard to the presentation description of the kidney is incorporated into the of the physiological information and the use of the various chapters dealing with kidney functions. Most system analysis approach to describe renal function. of the anatomical information was written by Wil- These positive and encouraging comments over the helm Kriz. The physiological information was writ- past nine years, since the publication of the first ten by Esmail Koushanpour, except for Chapter 12 edition, gave us the impetus to consider the prepa- which was jointly written. Chapters 1 through 3 were ration of a second edition.

This textbook provides an in depth course on data structures in the context of object oriented development. Its main themes are abstraction, implementation, encapsulation, and measurement: that is, that the software process begins with abstraction of data types, which then lead to alternate representations and encapsulation, and finally to resource measurement. A clear object oriented approach, making use of Booch components, will provide readers with a useful library of data structure components and experience in software reuse. Students using this book are expected to have a reasonable understanding of the basic logical structures such as stacks and queues. Throughout, Ada 95 is used and the author takes full advantage of Ada's encapsulation features and the ability to present specifications without implementational details. Ada code is supported by two suites available over the World Wide Web.