Download or read book Curve and Surface Fitting Functions With Matlab written by J. Braselton and published by CreateSpace. This book was released on 2014-09-10 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: Curve Fitting Toolbox provides graphical tools and command-line functions for fitting curves and surfaces to data. The toolbox lets you perform exploratory data analysis, preprocess and post-process data, compare candidate models, and remove outliers. You can conduct regression analysis using the library of linear and nonlinear models provided or specify your own custom equations. The library provides optimized solver parameters and starting conditions to improve the quality of your fits. The toolbox also supports nonparametric modeling techniques, such as splines, interpolation, and smoothing. After creating a fit, you can apply a variety of post-processing methods for plotting, interpolation, and extrapolation; estimating confidence intervals; and calculating integrals and derivatives. This book explains through examples all Curve Fitting Toolbox functions

Download or read book Curve and Surface Fitting Functions with MATLAB written by J. Braselton and published by Createspace Independent Publishing Platform. This book was released on 2016-06-22 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops the syntax of functions of Curve Fitting Toolbox(tm). This package provides an app and functions for fitting curves and surfaces to data. The toolbox lets you perform exploratory data analysis, preprocess and post-process data, compare candidate models, and remove outliers. You can conduct regression analysis using the library of linear and nonlinear models provided or specify your own custom equations. The library provides optimized solver parameters and starting conditions to improve the quality of your fits. The toolbox also supports nonparametric modeling techniques, such as splines, interpolation, and smoothing.After creating a fit, you can apply a variety of post-processing methods for plotting, interpolation, and extrapolation; estimating confidence intervals; and calculating integrals and derivatives.

Download or read book Curve and Surface Fitting With Matlab written by J. Braselton and published by CreateSpace. This book was released on 2014-09-11 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt: MATLAB Curve Fitting Toolbox provides graphical tools and command-line functions for fitting curves and surfaces to data. The toolbox lets you perform exploratory data analysis, preprocess and post-process data, compare candidate models, and remove outliers. You can conduct regression analysis using the library of linear and nonlinear models provided or specify your own custom equations. The library provides optimized solver parameters and starting conditions to improve the quality of your fits. The toolbox also supports nonparametric modeling techniques, such as splines, interpolation, and smoothing. After creating a fit, you can apply a variety of post-processing methods for plotting, interpolation, and extrapolation; estimating confidence intervals; and calculating integrals and derivatives. The most important topics in this book are: Interactive Curve and Surface Fitting Introducing the Curve Fitting Tool Fitting a Curve Fitting a Surface Model Types for Curves and Surfaces Interactive Fit Comparison Refining Your Fit Creating Multiple Fits Duplicating a Fit Deleting a Fit Displaying Multiple Fits Simultaneously Using the Statistics in the Table of Fits Generating MATLAB Code and Exporting Fits Interactive Code Generation and Programmatic Fitting Curve Fitting to Census Data Interactive Curve Fitting Workflow Loading Data and Creating Fits Determining the Best Fit Analyzing Your Best Fit in the Workspace Saving Your Work Surface Fitting to Franke Data Programmatic Curve and Surface Fitting Curve and Surface Fitting Objects and Methods Curve Fitting Objects Curve Fitting Methods Surface Fitting Objects and Methods

Download or read book Curve and Surface Fitting with MATLAB written by J. Braselton and published by Createspace Independent Publishing Platform. This book was released on 2016-06-22 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Curve Fitting Toolbox(tm) provides an app and functions for fitting curves and surfaces to data. The toolbox lets you perform exploratory data analysis, preprocess and post-process data, compare candidate models, and remove outliers. You can conduct regression analysis using the library of linear and nonlinear models provided or specify your own custom equations. The library provides optimized solver parameters and starting conditions to improve the quality of your fits. The toolbox also supports nonparametric modeling techniques, such as splines, interpolation, and smoothing.After creating a fit, you can apply a variety of post-processing methods for plotting, interpolation, and extrapolation; estimating confidence intervals; and calculating integrals and derivatives.Curve Fitting Toolbox(tm) software allows you to work in two different environments:An interactive environment, with the Curve Fitting app and the Spline ToolA programmatic environment that allows you to write object-oriented MATLAB(r) code using curve and surface fitting methods

Download or read book Modeling of Curves and Surfaces with MATLAB written by Vladimir Rovenski and published by Springer Science & Business Media. This book was released on 2010-07-03 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text on geometry is devoted to various central geometrical topics including: graphs of functions, transformations, (non-)Euclidean geometries, curves and surfaces as well as their applications in a variety of disciplines. This book presents elementary methods for analytical modeling and demonstrates the potential for symbolic computational tools to support the development of analytical solutions. The author systematically examines several powerful tools of MATLAB® including 2D and 3D animation of geometric images with shadows and colors and transformations using matrices. With over 150 stimulating exercises and problems, this text integrates traditional differential and non-Euclidean geometries with more current computer systems in a practical and user-friendly format. This text is an excellent classroom resource or self-study reference for undergraduate students in a variety of disciplines.

Download or read book Curve and Surface Fitting written by Peter Lancaster and published by . This book was released on 1986 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to reveal the foundations and major features of several basic methods for curve and surface fitting that are currently in use.

Download or read book Curve Fitting with MATLAB Linear and Non Linear Regression Interpolation written by Braselton J. and published by Createspace Independent Publishing Platform. This book was released on 2016-06-21 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Curve Fitting Toolbox(tm) provides an app and functions for fitting curves and surfaces to data. The toolbox lets you perform exploratory data analysis, preprocess and post-process data, compare candidate models, and remove outliers. You can conduct regression analysis using the library of linear and nonlinear models provided or specify your own custom equations. The library provides optimized solver parameters and starting conditions to improve the quality of your fits. The toolbox also supports nonparametric modeling techniques, such as splines, interpolation, and smoothing.

Download or read book Spline Fitting with MATLAB written by J. Braselton and published by Createspace Independent Publishing Platform. This book was released on 2016-06-22 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: You can work with splines in Curve Fitting Toolbox(tm) in several ways.Using the Curve Fitting app or the fit function you can:Fit cubic spline interpolants to curves or surfacesFit smoothing splines and shape-preserving cubic spline interpolants to curves (but not surfaces)Fit thin-plate splines to surfaces (but not curves)The toolbox also contains specific splines functions to allow greater control over what you can create. For example, you can use the csapi function for cubic spline interpolation. Why would you use csapi instead of the fit function 'cubicinterp' option? You might require greater flexibility to work with splines for the following reasons:You want to combine the results with other splines, You want vector-valued splines. You can use csapi with scalars, vectors, matrices, and ND-arrays. The fit function only allows scalar-valued splines.You want other types of splines such as ppform, B-form, tensor-product, rational, and stform thin-plate splines.You want to create splines without data.You want to specify breaks, optimize knot placement, and use specialized functions for spline manipulation such as differentiation and integration.If you require specialized spline functions, see the following sections for interactive and programmatic spline fitting.

Download or read book Econometrics With Matlab written by A. Smith and published by Createspace Independent Publishing Platform. This book was released on 2017-11-08 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Curve Fitting Toolbox provides an app and functions for fitting curves and surfaces to data. The toolbox lets you perform exploratory data analysis, preprocess and post-process data, compare candidate models, and remove outliers. You can conduct regression analysis using the library of linear and nonlinear models provided or specify your own custom equations. The library provides optimized solver parameters and starting conditions to improve the quality of your fits. The toolbox also supports nonparametric modeling techniques, such as splines, interpolation, and smoothing. After creating a fit, you can apply a variety of post-processing methods for plotting, interpolation, and extrapolation; estimating confidence intervals; and calculating integrals and derivatives. The most important content is the following: - Curve Fitting app for curve and surface fitting - Linear and nonlinear regression with custom equations - Library of regression models with optimized starting points and solver parameters - Interpolation methods, including B-splines, thin plate splines, and tensor-productsplines - Smoothing techniques, including smoothing splines, localized regression, Savitzky-Golay filters, and moving averages - Preprocessing routines, including outlier removal and sectioning, scaling, andweighting data - Post-processing routines, including interpolation, extrapolation, confidence intervals, integrals and derivatives

Download or read book Curve and Surface Fitting with Splines written by Paul Dierckx and published by Oxford University Press. This book was released on 1995 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fitting of a curve or surface through a set of observational data is a very frequent problem in different disciplines (mathematics, engineering, medicine, ...) with many interesting applications. This book describes the algorithms and mathematical fundamentals of a widely used software package for data fitting with (tensor product) splines. As such it gives a survey of possibilities and benefits but also of the problems to cope with when approximating with this popular type of function. In particular it is demonstrated in detail how the properties of B-splines can be fully exploited for improving the computational efficiency and for incorporating different boundary or shape preserving constraints. Special attention is also paid to strategies for an automatic and adaptive knot selection with intent to obtain serious data reductions. The practical use of the smoothing software is illustrated with many examples, academic as well as taken from real life.

Download or read book Modeling of Curves and Surfaces with MATLAB written by Vladimir Rovenski and published by Springer Science & Business Media. This book was released on 2010-06-10 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text on geometry is devoted to various central geometrical topics including: graphs of functions, transformations, (non-)Euclidean geometries, curves and surfaces as well as their applications in a variety of disciplines. This book presents elementary methods for analytical modeling and demonstrates the potential for symbolic computational tools to support the development of analytical solutions. The author systematically examines several powerful tools of MATLAB® including 2D and 3D animation of geometric images with shadows and colors and transformations using matrices. With over 150 stimulating exercises and problems, this text integrates traditional differential and non-Euclidean geometries with more current computer systems in a practical and user-friendly format. This text is an excellent classroom resource or self-study reference for undergraduate students in a variety of disciplines.

Download or read book Meshfree Approximation Methods with Matlab written by Gregory E Fasshauer and published by World Scientific Publishing Company. This book was released on 2007-04-17 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meshfree approximation methods are a relatively new area of research, and there are only a few books covering it at present. Whereas other works focus almost entirely on theoretical aspects or applications in the engineering field, this book provides the salient theoretical results needed for a basic understanding of meshfree approximation methods. The emphasis here is on a hands-on approach that includes MATLAB routines for all basic operations. Meshfree approximation methods, such as radial basis function and moving least squares method, are discussed from a scattered data approximation and partial differential equations point of view. A good balance is supplied between the necessary theory and implementation in terms of many MATLAB programs, with examples and applications to illustrate key points. Used as class notes for graduate courses at Northwestern University, Illinois Institute of Technology, and Vanderbilt University, this book will appeal to both mathematics and engineering graduate students.

Download or read book Introduction to Modeling and Simulation written by Mark W. Spong and published by John Wiley & Sons. This book was released on 2023-01-09 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Modeling and Simulation An essential introduction to engineering system modeling and simulation from a well-trusted source in engineering and education This new introductory-level textbook provides thirteen self-contained chapters, each covering an important topic in engineering systems modeling and simulation. The importance of such a topic cannot be overstated; modeling and simulation will only increase in importance in the future as computational resources improve and become more powerful and accessible, and as systems become more complex. This resource is a wonderful mix of practical examples, theoretical concepts, and experimental sessions that ensure a well-rounded education on the topic. The topics covered in Introduction to Modeling and Simulation are timeless fundamentals that provide the necessary background for further and more advanced study of one or more of the topics. The text includes topics such as linear and nonlinear dynamical systems, continuous-time and discrete-time systems, stability theory, numerical methods for solution of ODEs, PDE models, feedback systems, optimization, regression and more. Each chapter provides an introduction to the topic to familiarize students with the core ideas before delving deeper. The numerous tools and examples help ensure students engage in active learning, acquiring a range of tools for analyzing systems and gaining experience in numerical computation and simulation systems, from an author prized for both his writing and his teaching over the course of his over-40-year career. Introduction to Modeling and Simulation readers will also find: Numerous examples, tools, and programming tips to help clarify points made throughout the textbook, with end-of-chapter problems to further emphasize the material As systems become more complex, a chapter devoted to complex networks including small-world and scale-free networks – a unique advancement for textbooks within modeling and simulation A complementary website that hosts a complete set of lecture slides, a solution manual for end-of-chapter problems, MATLAB files, and case-study exercises Introduction to Modeling and Simulation is aimed at undergraduate and first-year graduate engineering students studying systems, in diverse avenues within the field: electrical, mechanical, mathematics, aerospace, bioengineering, physics, and civil and environmental engineering. It may also be of interest to those in mathematical modeling courses, as it provides in-depth material on MATLAB simulation and contains appendices with brief reviews of linear algebra, real analysis, and probability theory.

Download or read book Applied Optimization with MATLAB Programming written by P. Venkataraman and published by John Wiley & Sons. This book was released on 2009-03-23 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technology/Engineering/Mechanical Provides all the tools needed to begin solving optimization problems using MATLAB® The Second Edition of Applied Optimization with MATLAB® Programming enables readers to harness all the features of MATLAB® to solve optimization problems using a variety of linear and nonlinear design optimization techniques. By breaking down complex mathematical concepts into simple ideas and offering plenty of easy-to-follow examples, this text is an ideal introduction to the field. Examples come from all engineering disciplines as well as science, economics, operations research, and mathematics, helping readers understand how to apply optimization techniques to solve actual problems. This Second Edition has been thoroughly revised, incorporating current optimization techniques as well as the improved MATLAB® tools. Two important new features of the text are: Introduction to the scan and zoom method, providing a simple, effective technique that works for unconstrained, constrained, and global optimization problems New chapter, Hybrid Mathematics: An Application, using examples to illustrate how optimization can develop analytical or explicit solutions to differential systems and data-fitting problems Each chapter ends with a set of problems that give readers an opportunity to put their new skills into practice. Almost all of the numerical techniques covered in the text are supported by MATLAB® code, which readers can download on the text's companion Web site www.wiley.com/go/venkat2e and use to begin solving problems on their own. This text is recommended for upper-level undergraduate and graduate students in all areas of engineering as well as other disciplines that use optimization techniques to solve design problems.

Download or read book NUMERICAL SYMBOLIC AND STATISTICAL COMPUTING FOR CHEMICAL ENGINEERS USING MATLAB written by Ghosh, Pallab and published by PHI Learning Pvt. Ltd.. This book was released on 2018-09-01 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical, analytical and statistical computations are routine affairs for chemical engineers. They usually prefer a single software to solve their computational problems, and at present, MATLAB has emerged as a powerful computational language, which is preferably used for this purpose, due to its built-in functions and toolboxes. Considering the needs and convenience of the students, the author has made an attempt to write this book, which explains the various concepts of MATLAB in a systematic way and makes its readers proficient in using MATLAB for computing. It mainly focuses on the applications of MATLAB, rather than its use in programming basic numerical algorithms. Commencing with the introduction to MATLAB, the text covers vector and matrix computations, solution of linear and non-linear equations, differentiation and integration, and solution of ordinary and partial differential equations. Next, analytical computations using the Symbolic Math Toolbox and statistical computations using the Statistics and Machine Learning Toolbox are explained. Finally, the book describes various curve fitting techniques using the Curve Fitting Toolbox. Inclusion of all these advanced-level topics in the book stands it out from the rest. KEY FEATURES  Numerous worked-out examples to enable the readers understand the steps involved in solving the chemical engineering problems  MATLAB codes to explain the computational techniques  Several snapshots to help the readers understand the step-by-step procedures of using the toolboxes  Chapter-end exercises, including short-answer questions and numerical problems  Appendix comprising the definitions of some important and special matrices  Supplemented with Solutions Manual containing complete detailed solutions to the unsolved analytical problems  Accessibility of selected colour figures (including screenshots and results/outputs of the programs) cited in the text at www.phindia.com/Pallab_Ghosh. TARGET AUDIENCE • BE/B.Tech (Chemical Engineering) • ME/M.Tech (Chemical Engineering)

Download or read book Meshfree Approximation Methods with MATLAB written by Gregory E. Fasshauer and published by World Scientific. This book was released on 2007 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meshfree approximation methods are a relatively new area of research. This book provides the salient theoretical results needed for a basic understanding of meshfree approximation methods. It places emphasis on a hands-on approach that includes MATLAB routines for all basic operations.

Download or read book Data Driven Modeling Using MATLAB in Water Resources and Environmental Engineering written by Shahab Araghinejad and published by Springer Science & Business Media. This book was released on 2013-11-26 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering” provides a systematic account of major concepts and methodologies for data-driven models and presents a unified framework that makes the subject more accessible to and applicable for researchers and practitioners. It integrates important theories and applications of data-driven models and uses them to deal with a wide range of problems in the field of water resources and environmental engineering such as hydrological forecasting, flood analysis, water quality monitoring, regionalizing climatic data, and general function approximation. The book presents the statistical-based models including basic statistical analysis, nonparametric and logistic regression methods, time series analysis and modeling, and support vector machines. It also deals with the analysis and modeling based on artificial intelligence techniques including static and dynamic neural networks, statistical neural networks, fuzzy inference systems, and fuzzy regression. The book also discusses hybrid models as well as multi-model data fusion to wrap up the covered models and techniques. The source files of relatively simple and advanced programs demonstrating how to use the models are presented together with practical advice on how to best apply them. The programs, which have been developed using the MATLAB® unified platform, can be found on extras.springer.com. The main audience of this book includes graduate students in water resources engineering, environmental engineering, agricultural engineering, and natural resources engineering. This book may be adapted for use as a senior undergraduate and graduate textbook by focusing on selected topics. Alternatively, it may also be used as a valuable resource book for practicing engineers, consulting engineers, scientists and others involved in water resources and environmental engineering.