- Table View
- List View
Linear Systems Theory (Systems Engineering Ser.)
by Ferenc SzidarovszkyThis second edition comprehensively presents important tools of linear systems theory, including differential and difference equations, Laplace and Z transforms, and more.Linear Systems Theory discusses:Nonlinear and linear systems in the state space form and through the transfer function methodStability, including marginal stability, asymptotical stability, global asymptotical stability, uniform stability, uniform exponential stability, and BIBO stabilityControllabilityObservabilityCanonical formsSystem realizations and minimal realizations, including state space approach and transfer function realizationsSystem designKalman filtersNonnegative systemsAdaptive controlNeural networksThe book focuses mainly on applications in electrical engineering, but it provides examples for most branches of engineering, economics, and social sciences.What's New in the Second Edition?Case studies drawn mainly from electrical and mechanical engineering applications, replacing many of the longer case studiesExpanded explanations of both linear and nonlinear systems as well as new problem sets at the end of each chapterIllustrative examples in all the chaptersAn introduction and analysis of new stability conceptsAn expanded chapter on neural networks, analyzing advances that have occurred in that field since the first editionAlthough more mainstream than its predecessor, this revision maintains the rigorous mathematical approach of the first edition, providing fast, efficient development of the material.Linear Systems Theory enables its reader to develop his or her capabilities for modeling dynamic phenomena, examining their properties, and applying them to real-life situations.
Linear Systems and Operators in Hilbert Space (Dover Books on Mathematics)
by Paul A. FuhrmannA treatment of system theory within the context of finite dimensional spaces, this text is appropriate for students with no previous experience of operator theory. The three-part approach, with notes and references for each section, covers linear algebra and finite dimensional systems, operators in Hilbert space, and linear systems in Hilbert space. 1981 edition.
Linear Time Series with MATLAB and OCTAVE (Statistics and Computing)
by Víctor GómezThis book presents an introduction to linear univariate and multivariate time series analysis, providing brief theoretical insights into each topic, and from the beginning illustrating the theory with software examples. As such, it quickly introduces readers to the peculiarities of each subject from both theoretical and the practical points of view. It also includes numerous examples and real-world applications that demonstrate how to handle different types of time series data. The associated software package, SSMMATLAB, is written in MATLAB and also runs on the free OCTAVE platform. The book focuses on linear time series models using a state space approach, with the Kalman filter and smoother as the main tools for model estimation, prediction and signal extraction. A chapter on state space models describes these tools and provides examples of their use with general state space models. Other topics discussed in the book include ARIMA; and transfer function and structural models; as well as signal extraction using the canonical decomposition in the univariate case, and VAR, VARMA, cointegrated VARMA, VARX, VARMAX, and multivariate structural models in the multivariate case. It also addresses spectral analysis, the use of fixed filters in a model-based approach, and automatic model identification procedures for ARIMA and transfer function models in the presence of outliers, interventions, complex seasonal patterns and other effects like Easter, trading day, etc. This book is intended for both students and researchers in various fields dealing with time series. The software provides numerous automatic procedures to handle common practical situations, but at the same time, readers with programming skills can write their own programs to deal with specific problems. Although the theoretical introduction to each topic is kept to a minimum, readers can consult the companion book ‘Multivariate Time Series With Linear State Space Structure’, by the same author, if they require more details.
Linear Time-Invariant Systems, Behaviors and Modules (Differential-Algebraic Equations Forum)
by Ulrich Oberst Martin Scheicher Ingrid ScheicherThis book comprehensively examines various significant aspects of linear time-invariant systems theory, both for continuous-time and discrete-time. Using a number of new mathematical methods it provides complete and exact proofs of all the systems theoretic and electrical engineering results, as well as important results and algorithms demonstrated with nontrivial computer examples. The book is intended for readers who have completed the first two years of a university mathematics course. All further mathematical results required are proven in the book.
Linear Transformation: Examples and Solutions (Mathematical Engineering, Manufacturing, and Management Sciences)
by Nita H. Shah Urmila B. ChaudhariThis book introduces linear transformation and its key results, which have applications in engineering, physics, and various branches of mathematics. Linear transformation is a difficult subject for students. This concise text provides an in-depth overview of linear trans-formation. It provides multiple-choice questions, covers enough examples for the reader to gain a clear understanding, and includes exact methods with specific shortcuts to reach solutions for particular problems. Research scholars and students working in the fields of engineering, physics, and different branches of mathematics need to learn the concepts of linear transformation to solve their problems. This book will serve their need instead of having to use the more complex texts that contain more concepts then needed. The chapters mainly discuss the definition of linear transformation, properties of linear transformation, linear operators, composition of two or more linear transformations, kernels and range of linear transformation, inverse transformation, one-to-one and onto transformation, isomorphism, matrix linear transformation, and similarity of two matrices.
Linear and Complex Analysis for Applications (Advances in Applied Mathematics)
by John P. D'Angelo<p>Linear and Complex Analysis for Applications aims to unify various parts of mathematical analysis in an engaging manner and to provide a diverse and unusual collection of applications, both to other fields of mathematics and to physics and engineering. The book evolved from several of the author’s teaching experiences, his research in complex analysis in several variables, and many conversations with friends and colleagues. <p>It has three primary goals: <p> <li>to develop enough linear analysis and complex variable theory to prepare students in engineering or applied mathematics for advanced work, <li>to unify many distinct and seemingly isolated topics, <li>to show mathematics as both interesting and useful, especially via the juxtaposition of examples and theorems.</li> <p> <p>The book realizes these goals by beginning with reviews of Linear Algebra, Complex Numbers, and topics from Calculus III. As the topics are being reviewed, new material is inserted to help the student develop skill in both computation and theory. The material on linear algebra includes infinite-dimensional examples arising from elementary calculus and differential equations. Line and surface integrals are computed both in the language of classical vector analysis and by using differential forms. Connections among the topics and applications appear throughout the book. <p>The text weaves abstract mathematics, routine computational problems, and applications into a coherent whole, whose unifying theme is linear systems. It includes many unusual examples and contains more than 450 exercises.</p>
Linear and Convex Optimization: A Mathematical Approach
by Michael H. VeatchDiscover the practical impacts of current methods of optimization with this approachable, one-stop resource Linear and Convex Optimization: A Mathematical Approach delivers a concise and unified treatment of optimization with a focus on developing insights in problem structure, modeling, and algorithms. Convex optimization problems are covered in detail because of their many applications and the fast algorithms that have been developed to solve them. Experienced researcher and undergraduate teacher Mike Veatch presents the main algorithms used in linear, integer, and convex optimization in a mathematical style with an emphasis on what makes a class of problems practically solvable and developing insight into algorithms geometrically. Principles of algorithm design and the speed of algorithms are discussed in detail, requiring no background in algorithms. The book offers a breadth of recent applications to demonstrate the many areas in which optimization is successfully and frequently used, while the process of formulating optimization problems is addressed throughout. Linear and Convex Optimization contains a wide variety of features, including: Coverage of current methods in optimization in a style and level that remains appealing and accessible for mathematically trained undergraduates Enhanced insights into a few algorithms, instead of presenting many algorithms in cursory fashion An emphasis on the formulation of large, data-driven optimization problems Inclusion of linear, integer, and convex optimization, covering many practically solvable problems using algorithms that share many of the same concepts Presentation of a broad range of applications to fields like online marketing, disaster response, humanitarian development, public sector planning, health delivery, manufacturing, and supply chain management Ideal for upper level undergraduate mathematics majors with an interest in practical applications of mathematics, this book will also appeal to business, economics, computer science, and operations research majors with at least two years of mathematics training.
Linear and Generalized Linear Mixed Models and Their Applications (Springer Series in Statistics)
by Jiming Jiang Thuan NguyenThis book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models. It presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it includes recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method in the context of mixed models. The book is aimed at students, researchers and other practitioners who are interested in using mixed models for statistical data analysis.
Linear and Integer Optimization: Theory and Practice, Third Edition (Advances in Applied Mathematics)
by Gerard Sierksma Yori ZwolsPresenting a strong and clear relationship between theory and practice, Linear and Integer Optimization: Theory and Practice is divided into two main parts. The first covers the theory of linear and integer optimization, including both basic and advanced topics. Dantzig's simplex algorithm, duality, sensitivity analysis, integer optimization models
Linear and Integer Programming Made Easy
by T. C. Hu Andrew B. KahngThis textbook provides concise coverage of the basics of linear and integer programming which, with megatrends toward optimization, machine learning, big data, etc. , are becoming fundamental toolkits for data and information science and technology. The authors' approach is accessible to students from almost all fields of engineering, including operations research, statistics, machine learning, control system design, scheduling, formal verification and computer vision. The presentations enables the basis for numerous approaches to solving hard combinatorial optimization problems through randomization and approximation. Readers will learn to cast various problems that may arise in their research as optimization problems, understand the cases where the optimization problem will be linear, choose appropriate solution methods and interpret results appropriately.
Linear and Mixed Integer Programming for Portfolio Optimization
by Renata Mansini Włodzimierz Ogryczak M. Grazia SperanzaThis book presents solutions to the general problem of single period portfolio optimization. It introduces different linear models, arising from different performance measures, and the mixed integer linear models resulting from the introduction of real features. Other linear models, such as models for portfolio rebalancing and index tracking, are also covered. The book discusses computational issues and provides a theoretical framework, including the concepts of risk-averse preferences, stochastic dominance and coherent risk measures. The material is presented in a style that requires no background in finance or in portfolio optimization; some experience in linear and mixed integer models, however, is required. The book is thoroughly didactic, supplementing the concepts with comments and illustrative examples.
Linear and Multiobjective Programming with Fuzzy Stochastic Extensions
by Masatoshi Sakawa Hitoshi Yano Ichiro NishizakiAlthough several books or monographs on multiobjective optimization under uncertainty have been published, there seems to be no book which starts with an introductory chapter of linear programming and is designed to incorporate both fuzziness and randomness into multiobjective programming in a unified way. In this book, five major topics, linear programming, multiobjective programming, fuzzy programming, stochastic programming, and fuzzy stochastic programming, are presented in a comprehensive manner. Especially, the last four topics together comprise the main characteristics of this book, and special stress is placed on interactive decision making aspects of multiobjective programming for human-centered systems in most realistic situations under fuzziness and/or randomness. Organization of each chapter is briefly summarized as follows: Chapter 2 is a concise and condensed description of the theory of linear programming and its algorithms. Chapter 3 discusses fundamental notions and methods of multiobjective linear programming and concludes with interactive multiobjective linear programming. In Chapter 4, starting with clear explanations of fuzzy linear programming and fuzzy multiobjective linear programming, interactive fuzzy multiobjective linear programming is presented. Chapter 5 gives detailed explanations of fundamental notions and methods of stochastic programming including two-stage programming and chance constrained programming. Chapter 6 develops several interactive fuzzy programming approaches to multiobjective stochastic programming problems. Applications to purchase and transportation planning for food retailing are considered in Chapter 7. The book is self-contained because of the three appendices and answers to problems. Appendix A contains a brief summary of the topics from linear algebra. Pertinent results from nonlinear programming are summarized in Appendix B. Appendix C is a clear explanation of the Excel Solver, one of the easiest ways to solve optimization problems, through the use of simple examples of linear and nonlinear programming.
Linear and Nonlinear Programming
by David G. Luenberger Yinyu YeThis new edition covers the central concepts of practical optimization techniques, with an emphasis on methods that are both state-of-the-art and popular. One major insight is the connection between the purely analytical character of an optimization problem and the behavior of algorithms used to solve a problem. This was a major theme of the first edition of this book and the fourth edition expands and further illustrates this relationship. As in the earlier editions, the material in this fourth edition is organized into three separate parts. Part I is a self-contained introduction to linear programming. The presentation in this part is fairly conventional, covering the main elements of the underlying theory of linear programming, many of the most effective numerical algorithms, and many of its important special applications. Part II, which is independent of Part I, covers the theory of unconstrained optimization, including both derivations of the appropriate optimality conditions and an introduction to basic algorithms. This part of the book explores the general properties of algorithms and defines various notions of convergence. Part III extends the concepts developed in the second part to constrained optimization problems. Except for a few isolated sections, this part is also independent of Part I. It is possible to go directly into Parts II and III omitting Part I, and, in fact, the book has been used in this way in many universities. New to this edition is a chapter devoted to Conic Linear Programming, a powerful generalization of Linear Programming. Indeed, many conic structures are possible and useful in a variety of applications. It must be recognized, however, that conic linear programming is an advanced topic, requiring special study. Another important topic is an accelerated steepest descent method that exhibits superior convergence properties, and for this reason, has become quite popular. The proof of the convergence property for both standard and accelerated steepest descent methods are presented in Chapter 8. As in previous editions, end-of-chapter exercises appear for all chapters. From the reviews of the Third Edition: ". . . this very well-written book is a classic textbook in Optimization. It should be present in the bookcase of each student, researcher, and specialist from the host of disciplines from which practical optimization applications are drawn. " (Jean-Jacques Strodiot, Zentralblatt MATH, Vol. 1207, 2011)
Linear and Nonlinear Programming with Maple: An Interactive, Applications-Based Approach
by Paul E. FishbackHelps Students Understand Mathematical Programming Principles and Solve Real-World ApplicationsSupplies enough mathematical rigor yet accessible enough for undergraduatesIntegrating a hands-on learning approach, a strong linear algebra focus, Maple software, and real-world applications, Linear and Nonlinear Programming with Maple : An Interactive,
Linear and Quasilinear Complex Equations of Hyperbolic and Mixed Types
by Guo Chun WenThis volume deals with first and second order complex equations of hyperbolic and mixed types. Various general boundary value problems for linear and quasilinear complex equations are investigated in detail. To obtain results for complex equations of mixed types, some discontinuous boundary value problems for elliptic complex equations are discusse
Linear-Scaling Techniques in Computational Chemistry and Physics
by Jerzy Leszczynski Manthos G. Papadopoulos Robert Zaleśny Paul G. Mezey"Linear-Scaling Techniques in Computational Chemistry and Physics" summarizes recent progresses in linear-scaling techniques and their applications in chemistry and physics. In order to meet the needs of a broad community of chemists and physicists, the book focuses on recent advances that extended the scope of possible exploitations of the theory. The first chapter provides an overview of the present state of the linear-scaling methodologies and their applications, outlining hot topics in this field, and pointing to expected developments in the near future. This general introduction is then followed by several review chapters written by experts who substantially contributed to recent developments in this field. The purpose of this book is to review, in a systematic manner, recent developments in linear-scaling methods and their applications in computational chemistry and physics. Great emphasis is put on the theoretical aspects of linear-scaling methods. This book serves as a handbook for theoreticians, who are involved in the development of new efficient computational methods as well as for scientists, who are using the tools of computational chemistry and physics in their research.
Lineare Algebra
by Volker Mehrmann Jörg LiesenEine Einführung, welche die Lineare Algebra aus Anwendungsproblemen motiviert und eine Basis- und Matrizenorientierte Darstellung mit der abstrakten mathematischen Theorie kombiniert. Die Bedeutung der Linearen Algebra für die Entwicklung moderner numerischer Verfahren sowie als grundlegendes Werkzeug im Bereich der reinen Mathematik wird verdeutlicht. Das Buch ist stark modularisiert und für unterschiedliche Typen von Lehrveranstaltungen geeignet.
Lineare Algebra I: Geeignet zum Selbststudium oder für Inverted-Classroom-Vorlesungen
by Marco HienDieses Lehrbuch behandelt die üblichen Inhalte der Vorlesung „Lineare Algebra“. Ein besonderer Schwerpunkt wird auf die schrittweise Entwicklung der Grundbegriffe, Konzepte und Sätze gelegt. Das Buch enthält eine Vielzahl von Motivationen und Querbezügen zwischen konkreten (Rechen-)Beispielen und abstrakten Aussagen und eignet sich daher hervorragend zum Selbststudium und zur Prüfungsvorbereitung.
Lineare Algebra II: Geeignet zum Selbststudium oder für Inverted-Classroom-Vorlesungen
by Marco HienDieses Lehrbuch behandelt übliche Inhalte der Vorlesung "Lineare Algebra 2". Ein besonderer Schwerpunkt wird auf die schrittweise Entwicklung der Grundbegriffe, Konzepte und Sätze gelegt. Das Buch enthält eine Vielzahl von Motivationen und Querbezügen zwischen konkreten (Rechen-)Beispielen und abstrakten Aussagen und eignet sich daher hervorragend zum Selbststudium und zur Prüfungsvorbereitung. Als teilweise schwierig geltende Themen wie die Jordan-Normal-Form oder Tensorprodukte werden ausführlich motiviert und erklärt.
Lineare Algebra für Dummies (Für Dummies)
by Ernst Georg HaffnerDieses Buch wird Sie sanft in eines der wichtigsten Teilgebiete der Mathematik begleiten. Folgerichtig beginnt es mit den Grundlagen - komplexe Zahlen, Körper, Vektorrechnung -, bevor es sich linearen Gleichungssystemen und Matrizen zuwendet. Auf den nächsten Teil dürfen Sie sich freuen: Schnitte von Ebenen und affine Abbildungen werden mit den Mitteln der linearen Algebra ganz leicht handhabbar. Und zuletzt bekommen Sie noch eine Einführung in die schwierigsten Themen der linearen Algebra: Morphismen, Determinanten, Basiswechsel, Eigenwerte und -vektoren und Diagonalisierung.
Lineare Algebra kompakt für Dummies (Für Dummies)
by Ernst Georg HaffnerDer schnelle Überblick für Schüler, Studenten und jeden, den es sonst noch interessiert Sie ist unbeliebt und gilt als schwer verständlich: die Li‑neare Algebra. Aber keine Sorge, Hilfe naht: E.-G. Haffner hat für Sie das Wichtigste kompakt und dennoch verständlich zusammengefasst. Dank vieler Beispiele und Schritt-für-Schritt-Beschreibungen erlernen Sie den Umgang mit Vektoren, Vektorräumen, Matrizen und linearen Gleichungssystemen fast wie von selbst. Damit ist Lineare Algebra kompakt für Dummies der perfekte Nachhilfelehrer für die Tasche: einfach, kompetent und günstig.
Lineare Algebra: Analysis Und Lineare Algebra Mit Querverbindungen
by Christian Karpfinger Hellmuth StachelDieses vierfarbige Lehrbuch wendet sich an Studierende der Mathematik, der Physik und Informatik in Bachelor- und Lehramts-Studiengängen. Es bietet ein lebendiges Bild der Linearen Algebra, wie sie üblicherweise im ersten Studienjahr behandelt wird. Studierende der Mathematik und der mathematiknahen Studiengänge finden wichtige Begriffe, Sätze und Beweise ausführlich und mit vielen Beispielen erklärt und werden an grundlegende Konzepte und Methoden herangeführt. Im Mittelpunkt stehen das Verständnis der mathematischen Zusammenhänge und des Aufbaus der Theorie sowie die Strukturen und Ideen wichtiger Sätze und Beweise. Es wird nicht nur ein in sich geschlossenes Theoriengebäude dargestellt, sondern auch verdeutlicht, wie es entsteht und wozu die Inhalte später benötigt werden. Herausragende Merkmale sind: durchgängig vierfarbiges Layout mit mehr als 150 Abbildungen prägnant formulierte Kerngedanken bilden die Abschnittsüberschriften ausführliche Übungsbeispiele laden zum „Learning by Doing“ ein Selbsttests in kurzen Abständen ermöglichen Lernkontrollen während des Lesensfarbige Merkkästen heben das Wichtigste hervor„Hintergrund-und-Ausblick“-Boxen stellen Zusammenhänge zu anderen Gebieten und weiterführenden Themen herÜbersichtsboxen fassen wichtige Resultate zusammen.mehr als 250 Verständnisfragen, Rechenaufgaben und Aufgaben zu Beweisen Das Buch wird allen Studierenden der Mathematik und mathematiknaher Studiengänge vom Beginn des Studiums bis in höhere Semester hinein ein verlässlicher Begleiter sein. Die Inhalte dieses Buches basieren größtenteils auf dem Werk „Grundwissen Mathematikstudium – Analysis und Lineare Algebra mit Querverbindungen“, werden aber wegen der curricularen Bedeutung hiermit in vollständig überarbeiteter Form als eigenständiges Werk veröffentlicht.
Lineare Algebra: Ein Lehrbuch über die Theorie mit Blick auf die Praxis (Springer Studium Mathematik (Bachelor))
by Volker Mehrmann Jörg LiesenDieses Lehrbuch über die Lineare Algebra deckt den gesamten Stoff der zweisemestrigen Grundvorlesung ab. Seine anschauliche und konsequent matrizenorientierte Herangehensweise ermöglicht Studierenden ein intuitives Verständnis der abstrakten Objekte. Die im Buch präsentierten vielfältigen Anwendungen und Beispiele motivieren Studierende zur intensiven Auseinandersetzung mit der Linearen Algebra als leistungsfähiges mathematisches Werkzeug. In vielen „MATLAB-Minuten“ können sich Studierende wichtige Sätze und Konzepte am Rechner erarbeiten. Alle notwendigen Vorkenntnisse werden in einer MATLAB-Kurzeinführung erläutert. Das Buch enthält zudem über 350 Übungsaufgaben, die das Erlernen des Stoffes unterstützen. Interessierte Studierende finden darüber hinaus historische Notizen zur Entwicklung des Gebiets. Für diese dritte Auflage wurde die zweite Auflage durchgesehen und ergänzt. Zu den Ergänzungen gehören Abschnitte über die vollständige Induktion und die Existenz von Basen und von Adjungierten in unendlichdimensionalen Vektorräumen. Der übersichtliche Aufbau und das bewährte Konzept des Lehrbuchs wurden beibehalten.
Lineare Algebra: Ein Lehrbuch über die Theorie mit Blick auf die Praxis (Springer Studium Mathematik (Bachelor))
by Volker Mehrmann Jörg LiesenDieses Lehrbuch über die Lineare Algebra deckt den gesamten Stoff der zweisemestrigen Grundvorlesung ab. Seine anschauliche und konsequent matrizenorientierte Herangehensweise ermöglicht Studierenden ein intuitives Verständnis der abstrakten Objekte. Die im Buch präsentierten vielfältigen Anwendungen und Beispiele motivieren Studierende zur intensiven Auseinandersetzung mit der Linearen Algebra als leistungsfähiges mathematisches Werkzeug. In vielen „MATLAB-Minuten“ können sich Studierende wichtige Sätze und Konzepte am Rechner erarbeiten. Alle notwendigen Vorkenntnisse werden in einer MATLAB-Kurzeinführung erläutert. Das Buch enthält zudem über 350 Übungsaufgaben, die das Erlernen des Stoffes unterstützen. Interessierte Studierende finden darüber hinaus historische Notizen zur Entwicklung des Gebiets. Für diese vierte Auflage wurde das Buch durchgesehen und ergänzt. Zu den Ergänzungen gehören insbesondere die genauere Betrachtung von Projektionen, die Herleitung der Frobenius-Normalform von Endomorphismen sowie der Beweis eines wichtigen Satzes über Matrixfunktionen basierend auf der Lösung des Hermite-Interpolationsproblems. Hinzugekommen sind außerdem mehr als 20 neue Aufgaben sowie Begriffe wie der Bidualraum, derogatorische Matrizen, Invariantenteiler und Isometrien. Der übersichtliche Aufbau und das bewährte Konzept des Lehrbuchs wurden beibehalten.
Lineare Algebra: Eine Einführung in die Wissenschaft der Vektoren, Abbildungen und Matrizen
by Albrecht BeutelspacherDieses Lehrbuch ist leicht verständlich, speziell für Anfänger der Mathematik sowohl im Bachelor- als auch im Lehramtsstudium. Unter den vielen Büchern über Lineare Algebra, die Sie in der Bibliothek oder einer Buchhandlung finden, eignet dieses sich besonders dafür, Ihr erstes Mathematikbuch zu sein.Der Stil ist locker, lustig, leicht und unterhaltsam. Vor allem wurde versucht, die üblichen k.o.-Schläge, wie etwa "wie man leicht sieht", "trivialerweise folgt", "man sieht unmittelbar", zu vermeiden.Durch viele Lernhilfen ist das Buch ideal geeignet zum Selbststudium: Zu jedem Kapitel gibt es zunächst eine Reihe von insgesamt über 250 "ganz dummen" Fragen, die zur unmittelbaren Kontrolle dienen; dann gibt es eine reiche Auswahl von leicht lösbaren Übungsaufgaben und schließlich tiefergehende "Projekte". Alles in allem über 300 Übungsaufgaben - mit Tipps zu ihrer Lösung. Das Buch liegt nun in einer verbesserten und neu gesetzten Neuauflage vor.