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Author: Michael Oberguggenberger Publisher: Springer Science & Business Media ISBN: 0857294466 Category : Computers Languages : en Pages : 342
Book Description
This textbook presents an algorithmic approach to mathematical analysis, with a focus on modelling and on the applications of analysis. Fully integrating mathematical software into the text as an important component of analysis, the book makes thorough use of examples and explanations using MATLAB, Maple, and Java applets. Mathematical theory is described alongside the basic concepts and methods of numerical analysis, supported by computer experiments and programming exercises, and an extensive use of figure illustrations. Features: thoroughly describes the essential concepts of analysis; provides summaries and exercises in each chapter, as well as computer experiments; discusses important applications and advanced topics; presents tools from vector and matrix algebra in the appendices, together with further information on continuity; includes definitions, propositions and examples throughout the text; supplementary software can be downloaded from the book’s webpage.
Author: Michael Oberguggenberger Publisher: Springer Science & Business Media ISBN: 0857294466 Category : Computers Languages : en Pages : 342
Book Description
This textbook presents an algorithmic approach to mathematical analysis, with a focus on modelling and on the applications of analysis. Fully integrating mathematical software into the text as an important component of analysis, the book makes thorough use of examples and explanations using MATLAB, Maple, and Java applets. Mathematical theory is described alongside the basic concepts and methods of numerical analysis, supported by computer experiments and programming exercises, and an extensive use of figure illustrations. Features: thoroughly describes the essential concepts of analysis; provides summaries and exercises in each chapter, as well as computer experiments; discusses important applications and advanced topics; presents tools from vector and matrix algebra in the appendices, together with further information on continuity; includes definitions, propositions and examples throughout the text; supplementary software can be downloaded from the book’s webpage.
Author: Dana Vrajitoru Publisher: Springer ISBN: 3319098888 Category : Computers Languages : en Pages : 466
Book Description
This book introduces the essential concepts of algorithm analysis required by core undergraduate and graduate computer science courses, in addition to providing a review of the fundamental mathematical notions necessary to understand these concepts. Features: includes numerous fully-worked examples and step-by-step proofs, assuming no strong mathematical background; describes the foundation of the analysis of algorithms theory in terms of the big-Oh, Omega, and Theta notations; examines recurrence relations; discusses the concepts of basic operation, traditional loop counting, and best case and worst case complexities; reviews various algorithms of a probabilistic nature, and uses elements of probability theory to compute the average complexity of algorithms such as Quicksort; introduces a variety of classical finite graph algorithms, together with an analysis of their complexity; provides an appendix on probability theory, reviewing the major definitions and theorems used in the book.
Author: Dexter C. Kozen Publisher: Springer Science & Business Media ISBN: 1461244005 Category : Computers Languages : en Pages : 327
Book Description
These are my lecture notes from CS681: Design and Analysis of Algo rithms, a one-semester graduate course I taught at Cornell for three consec utive fall semesters from '88 to '90. The course serves a dual purpose: to cover core material in algorithms for graduate students in computer science preparing for their PhD qualifying exams, and to introduce theory students to some advanced topics in the design and analysis of algorithms. The material is thus a mixture of core and advanced topics. At first I meant these notes to supplement and not supplant a textbook, but over the three years they gradually took on a life of their own. In addition to the notes, I depended heavily on the texts • A. V. Aho, J. E. Hopcroft, and J. D. Ullman, The Design and Analysis of Computer Algorithms. Addison-Wesley, 1975. • M. R. Garey and D. S. Johnson, Computers and Intractibility: A Guide to the Theory of NP-Completeness. w. H. Freeman, 1979. • R. E. Tarjan, Data Structures and Network Algorithms. SIAM Regional Conference Series in Applied Mathematics 44, 1983. and still recommend them as excellent references.
Author: Michael Oberguggenberger Publisher: ISBN: 9783319911564 Category : Computer science Languages : en Pages :
Book Description
This textbook/reference presents a concise introduction to mathematical analysis from an algorithmic point of view, with a particular focus on applications of analysis and aspects of mathematical modelling. The text describes the mathematical theory alongside the basic concepts and methods of numerical analysis, enriched by computer experiments using MATLAB, Python, Maple, and Java applets. This fully updated and expanded new edition also features an even greater number of programming exercises. Topics and features : Describes the fundamental concepts in analysis, covering real and complex numbers, trigonometry, sequences and series, functions, derivatives, integrals, and curves; Discusses important applications and advanced topics, such as fractals and L-systems, numerical integration, linear regression, and differential equations; Presents tools from vector and matrix algebra in the appendices, together with further information on continuity; Includes added material on hyperbolic functions, curves and surfaces in space, second-order differential equations, and the pendulum equation (NEW); Contains experiments, exercises, definitions, and propositions throughout the text; Supplies programming examples in Python, in addition to MATLAB (NEW); Provides supplementary resources at an associated website, including Java applets, code source files, and links to interactive online learning material.
Author: Martin Theus Publisher: CRC Press ISBN: 1420011065 Category : Computers Languages : en Pages : 293
Book Description
Interactive Graphics for Data Analysis: Principles and Examples discusses exploratory data analysis (EDA) and how interactive graphical methods can help gain insights as well as generate new questions and hypotheses from datasets.Fundamentals of Interactive Statistical GraphicsThe first part of the book summarizes principles and methodology, demons
Author: J. Wesley Barnes Publisher: McGraw-Hill Companies ISBN: Category : Engineering Languages : en Pages : 440
Book Description
This text covers topics such as nonparametric statistics, statistical quality control, multivariate regression analysis and operating characteristic curves. The accompanying MAC software gives a complete treatment of statistically valid sample sizes in all tests of hypotheses addressed.
Author: Kai-Tai Fang Publisher: CRC Press ISBN: 1420034898 Category : Mathematics Languages : en Pages : 304
Book Description
Computer simulations based on mathematical models have become ubiquitous across the engineering disciplines and throughout the physical sciences. Successful use of a simulation model, however, requires careful interrogation of the model through systematic computer experiments. While specific theoretical/mathematical examinations of computer experim
Author: Clifford A. Shaffer Publisher: Courier Corporation ISBN: 048648582X Category : Computers Languages : en Pages : 626
Book Description
A comprehensive treatment focusing on the creation of efficient data structures and algorithms, this text explains how to select or design the data structure best suited to specific problems. It uses C++ as the programming language and is suitable for second-year data structure courses and computer science courses in algorithmic analysis.
Author: National Research Council Publisher: National Academies Press ISBN: 0309165636 Category : Computers Languages : en Pages : 216
Book Description
Computer Science: Reflections on the Field, Reflections from the Field provides a concise characterization of key ideas that lie at the core of computer science (CS) research. The book offers a description of CS research recognizing the richness and diversity of the field. It brings together two dozen essays on diverse aspects of CS research, their motivation and results. By describing in accessible form computer science's intellectual character, and by conveying a sense of its vibrancy through a set of examples, the book aims to prepare readers for what the future might hold and help to inspire CS researchers in its creation.
Author: Michael Oberguggenberger
Author: Michael Oberguggenberger
Author: Dana Vrajitoru
Author: Dexter C. Kozen
Author: Michael Oberguggenberger
Author: Martin Theus
Author: Arnold O. Allen
Author: J. Wesley Barnes
Author: Kai-Tai Fang
Author: Clifford A. Shaffer
Author: National Research Council