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Erscheinungsdatum: 05/2010, Medium: Taschenbuch, Einband: Kartoniert / Broschiert, Titel: Dual Reciprocity Boundary Element Methods For Solving Inverse Problems, Titelzusatz: Applications to inverse source and boundary value problems for the Poisson equation, Autor: Farcas, Adrian, Verlag: LAP Lambert Acad. Publ., Sprache: Englisch, Rubrik: Mathematik // Sonstiges, Seiten: 228, Informationen: Paperback, Gewicht: 356 gr, Verkäufer: averdo

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SOLVING POISSON DIFFERENTIAL EQUATION USING VECTORSPACE PROJECTIONS ab 48.99 € als Taschenbuch: . Aus dem Bereich: Bücher, Wissenschaft, Technik,

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Dual Reciprocity Boundary Element Methods For Solving Inverse Problems ab 78.99 € als Taschenbuch: Applications to inverse source and boundary value problems for the Poisson equation. Aus dem Bereich: Bücher, Wissenschaft, Mathematik,

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Were you looking for the book with access to MyStatLab? This product is the book alone, and does NOT come with access to MyStatLab. Buy the book and access card package to save money on this resource. In Statistics for Business: Decision Making and Analysis, authors Robert Stine and Dean Foster of the University of Pennsylvania’s Wharton School, take a sophisticated approach to teaching statistics in the context of making good business decisions. The authors show students how to recognize and understand each business question, use statistical tools to do the analysis, and how to communicate their results clearly and concisely. In addition to providing cases and real data to demonstrate real business situations, this text provides resources to support understanding and engagement. A successful problem-solving framework in the 4-M Examples (Motivation, Method, Mechanics, Message) model a clear outline for solving problems, new What Do You Think questions give students an opportunity to stop and check their understanding as they read, and new learning objectives guide students through each chapter and help them to review major goals. Software Hints provide instructions for using the most up-to-date technology packages. The Second Edition also includes expanded coverage and instruction of Excel® 2010 and the XLSTAT ™ add-in. The MyStatLab™ course management system includes increased exercise coverage with the Second Edition, along with 100% of the You Do It exercises and a library of 1,000 Conceptual Questions that require students to apply their statistical understanding to conceptual business scenarios. Business Insight Videos show students how statistical methods are used by real businesses, and new StatTalk Videos present statistical concepts through a series of fun, brief, real-world examples. Technology tutorial videos at the exercise level support software use. Features + Benefits Statistics in Practice: Preparing Students for Real Business 4-M Examples (Motivation, Method, Mechanics, Message) provide a consistent methodology used for worked-out examples. This approach gives students a consistent structure for solving problems and presenting their findings in the appropriate context. Running Business Examples start each chapter by framing a business question to motivate the contents of the chapter. The example is referenced throughout the chapter when new statistical methods are presented. Statistics in Action case studies follow each of the four parts of the book. These longer applications expand on the statistical methods presented within the preceding part and use them to delve into substantive aspects of real-world business cases. Video resources available in MyStatLab offer students insight into how statistical concepts are applied in the business world and the world around us. Business Insight Videos show how statistical methods are used by real businesses. NEW! StatTalk Videos present statistical concepts through a series of fun, brief, real-world vignettes. Practice & Support: Challenging Students to Assess, Analyze and Report NEW! More than 150 exercises are new or have been updated to provide readers with the most up-to-date and relevant data available. Exercises are divided into five types. Each type focuses on a particular skill to build a deeper understanding of business statistics. Mix and Match and True/False problems test whether students recognize symbols and important steps of calculations. Think About It questions encourage students to pull together concepts and ideas from the chapter; no technology is required. You Do It problems provide practice working through the mechanics of solving a problem (statistical software usage is recommended). These exercises apply the statistical concepts students have learned in the chapter to data related to a business application. Data are available on the included CD-ROM. 4-M Questions are richer, more substantive problems that mimic real applications of statistics in business. Data are available on the included CD-ROM. Support NEW! 30 new What Do You Think? questions check students’ comprehension of the important ideas in the preceding section, ensuring that they understand the concepts before moving on in the chapter. Caution icons indicate a concept that can be troublesome and helps students avoid making common mistakes. Tip icons highlight important ideas or hints within the exposition so that readers don’t overlook them. Best Practices and Pitfalls listed at the end of every chapter offer reminders to help students avoid mistakes such as using the wrong method for a situation, or misinterpreting results. Technology Integration: Giving Students More Tools for Their Future Careers Software Hints at the end of each chapter provide relevant commands for popular statistics packages: Excel®, Minitab®, and JMP®. Extensive graphics, including Excel screenshots throughout the chapters and exercise sets, give students the opportunity to get familiar with seeing and interpreting statistical software output. Technology Tutorial Videos and Study Cards within MyStatLab provide targeted guidance to using statistical software. (Study Cards are available for bundling.) Preface Index of Application PART ONE: VARIATION 1. Introduction 1.1 What Is Statistics? 1.2 Previews 2. Data 2.1 Data Tables 2.2 Categorical and Numerical Data 2.3 Recoding and Aggregation 2.4 Time Series 2.5 Further Attributes of Data Chapter Summary 3. Describing Categorical Data 3.1 Looking at Data 3.2 Charts of Categorical Data 3.3 The Area Principle 3.4 Mode and Median Chapter Summary 4. Describing Numerical Data 4.1 Summaries of Numerical Variables 4.2 Histograms 4.3 Boxplot 4.4 Shape of a Distribution 4.5 Epilog Chapter Summary 5. Association between Categorical Variables 5.1 Contingency Tables 5.2 Lurking Variables and Simpson's Paradox 5.3 Strength of Association Chapter Summary 6. Association between Quantitative Variables 6.1 Scatterplots 6.2 Association in Scatterplots 6.3 Measuring Association 6.4 Summarizing Association with a Line 6.5 Spurious Correlation Chapter Summary Statistics in Action: Financial Time Series Statistics in Action: Executive Compensation PART TWO: PROBABILITY 7. Probability 7.1 From Data to Probability 7.2 Rules for Probability 7.3 Independent Events Chapter Summary 8. Conditional Probability 8.1 From Tables to Probabilities 8.2 Dependent Events 8.3 O rganizing Probabilities 8.4 O rder in Conditional Probabilities Chapter Summary 9. Random Variables 9.1 Random Variables 9.2 Properties of Random Variables 9.3 Properties of Expected Values 9.4 Comparing Random Variables Chapter Summary 10. Association between Random Variables 10.1 Portfolios and Random Variables 10.2 Joint Probability Distribution 10.3 Sums of Random Variables 10.4 Dependence between Random Variables 10.5 IID Random Variables 10.6 Weighted Sums Chapter Summary 11. Probability Models for Counts 11.1 Random Variables for Counts 11.2 Binomial Model 11.3 Properties of Binomial Random Variables 11.4 Poisson Model Chapter Summary 12. The Normal Probability Model 12.1 Normal Random Variable 12.2 The Normal Model 12.3 Percentiles 12.4 Departures from Normality Chapter Summary Statistics in Action: Managing Financial Risk Statistics in Action: Modeling Sampling Variation PART THREE: INFERENCE 13. Samples and Surveys 13.1 Two Surprising Properties of Samples 13.2 Variation 13.3 Alternative Sampling Methods 13.4 Questions to Ask Chapter Summary 14. Sampling Variation and Quality 14.1 Sampling Distribution of the Mean 14.2 Control Limits 14.3 Using a Control Chart 14.4 Control Charts for Variation Chapter Summary 15. Confidence Intervals 15.1 Ranges for Parameters 15.2 Confidence Interval for the Mean 15.3 Interpreting Confidence Intervals 15.4 Manipulating Confidence Intervals 15.5 Margin of Error Chapter Summary 16. Statistical Tests 16.1 Concepts of Statistical Tests 16.2 Testing the Proportion 16.3 Testing the Mean 16.4 Significance versus Importance 16.5 Confidence Interval or Test? Chapter Summary 17. Comparison 17.1 Data for Comparisons 17.2 Two-Sample z-test for Proportions 17.3 Two-Sample Confidence Interval for Proportions 17.4 Two-Sample T-test 17.5 Confidence Interval for the Difference between Means 17.6 Paired Comparisons Chapter Summary 18. Inference for Counts 18.1 Chi-Squared Tests 18.2 Test of Independence 18.3 General versus Specific Hypotheses 18.4 Tests of Goodness of Fit Chapter Summary Statistics in Action: Rare Events Statistics in Action: Data Mining Using Chi-Squared PART FOUR: REGRESSION MODELS 19. Linear Patterns 19.1 Fitting a Line to Data 19.2 Interpreting the Fitted Line 19.3 Properties of Residuals 19.4 Explaining Variation 19.5 Conditions for Simple Regression Chapter Summary 20. Curved Patterns 20.1 Detecting Nonlinear Patterns 20.2 Transformations 20.3 Reciprocal Transformation 20.4 Logarithm Transformation Chapter Summary 21. The Simple Regression Model 21.1 The Simple Regression Model 21.2 Conditions for the SRM 21.3 Inference in Regression 21.4 Prediction Intervals Chapter Summary 22. Regression Diagnostics 22.1 Changing Variation 22.2 Outliers 22.3 Dependent Errors and Time Series Chapter Summary 23. Multiple Regression 23.1 The Multiple Regression Model 23.2 Interpreting Multiple Regression 23.3 Checking Conditions 23.4 Inference in Multiple Regression 23.5 Steps in Fitting a Multiple Regression Chapter Summary 24. Building Regression Models 24.1 Identifying Explanatory Variables 24.2 Collinearity 24.3 Removing Explanatory Variables Chapter Summary 25. Categorical Explanatory Variables 25.1 Two-Sample Comparisons 25.2 Analysis of Covariance 25.3 Checking Conditions 25.4 Interactions and Inference 25.5 Regression with Several Groups Chapter Summary 26. Analysis of Variance 26.1 Comparing Several Groups 26.2 Inference in ANOVA Regression Models 26.3 Multiple Comparisons 26.4 Groups of Different Size Chapter Summary 27. Time Series 27.1 Decomposing a Time Series 27.2 Regression Models 27.3 Checking the Model Chapter Summary Statistics in Action: Analyzing Experiments Statistics in Action: Automated Modeling Appendix: Tables Answers Photo Acknowledgments Index Supplementary Material (online-only) Alternative Approaches to Inference More Regression 2-Way ANOVAWere you looking for the book with access to MyStatLab? This product is the book alone, and does NOT come with access to MyStatLab. Buy the book and access card package to save money on this resource.In Statistics for Business: Decision Making and Analysis, authors Robert Stine and Dean Foster of the University of Pennsylvania s Wharton School, take a sophisticated approach to teaching statistics in the context of making good business decisions. The authors show students how to recognize and understand each business question, use statistical tools to do the analysis, and how to communicate their results clearly and concisely.In addition to providing cases and real data to demonstrate real business situations, this text provides resources to support understanding and engagement. A successful problem-solving framework in the 4-M Examples (Motivation, Method, Mechanics, Message) model a clear outline for solving problems, new What Do You Think questions give students an opportunity to stop and check their understanding as they read, and new learning objectives guide students through each chapter and help them to review major goals. Software Hints provide instructions for using the most up-to-date technology packages. The Second Edition also includes expanded coverage and instruction of Excel® 2010 and the XLSTAT add-in.The MyStatLab course management system includes increased exercise coverage with the Second Edition, along with 100% of the You Do It exercises and a library of 1,000 Conceptual Questions that require students to apply their statistical understanding to conceptual business scenarios. Business Insight Videos show students how statistical methods are used by real businesses, and new StatTalk Videos present statistical concepts through a series of fun, brief, real-world examples. Technology tutorial videos at the exercise level support software use.

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Many important algorithms in fields such as image processing or physical simulation necessitate solving systems of partial differential equations. Multigrid methods belong to the fastest and most versatile numerical schemes available for this purpose. With the advent of programmable graphics processing units (GPUs) there have been numerous efforts to use their capabilities - massively parallel floating point computation and high memory bandwidth - in high performance computing. In this work, multigrid methods are evaluated for their suitability towards a GPU implementation. After some introductory material on general purpose GPU programming and a short mathematical overview, a multigrid solver for the 2D Poisson equation built on C++, OpenGL and GLSL is presented in detail. The performance of various implementation techniques is benchmarked and interpreted, a number of optimization strategies are tested and the final results are compared across different hardware platforms and to a traditional CPU-based implementation. This book is aimed at scientists and programmers interested in using the potential of GPUs to speed up their multigrid-based numerical solvers.

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This book contains 13 assignments in applications of statistics in mineral processing engineering. After each assignment readers can check their answers by solutions which are coming after each assignment. In each homework I tried to ask important questions related to statistics in mineral processing. In some assignments there are exel files for solving some questions, in the solutions readers can find and check their answers. In this book all of the essential topics of statistics in mineral processing is mentioned, such as Introduction to Statistics, The Normal Probability Distribution, One and two-Tailed Tests, Small-Sample Statistical Inference, Large-Sample Statistical Inference, Variance Analysis, The Chi-Squared Distribution, Biomial Distribution, Covariance, The Poisson Distribution, Confidence Intervals and ANOVA,SST(Sum of Squares of Treatments), SSE(Sum of Squares of Error)and MST(Mean Square for Treatment).

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The noise contained in images collected by a charge coupled device (CCD) camera is predominantly of Poisson type. This motivates the use of the negative logarithm of the Poisson likelihood in place of the ubiquitous least squares fit-to-data. However, if the underlying mathematical model is assumed to have the form z = Au, where A is a linear, compact operator, the problem of minimizing the negative log-Poisson likelihood function is ill-posed, and hence some form of regularization is required. This work involves solving a variational problem: minimizing the sum of the negative log Poisson likelihood and a regularizing functional. The main result of this book is a theoretical analysis of this variational problem for various regularization functionals. In addition, this work presents an efficient computational method for its solution, and the demonstration of the effectiveness of this approach in practice by applying the algorithm to simulated astronomical imaging data corrupted by the CCD camera noise model mentioned above.

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This work presents a new approach to solving the Poisson partial differential equation in the setting of vector spaces and vector sets. It formulates a very important signal-processing problem of phase unwrapping as a Poisson differential equation problem, and solves it using the vector space projection (VSP) methods. The 2D phase unwrapping problem in radar imaging and magnetic resonance imaging (MRI) is described, and examples in both fields are used to show the effectiveness of the proposed vector space projection method. In the second part of the work, the author approaches the classical problem of solving the Poisson equation in electrodynamics, formulating both the equation itself, and the boundary conditions in the vector space setting. Both the homogeneous and the non-homogenous solutions are presented.The book covers only two of the numerous applications of the Poisson differential equation, but it presents the essentials of the vector space projection methods in solving the partial differential equations. Other applications of VSP methods are hinted, and suggested as the extensions of this work.

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