Fitting Curves And Sourfaces Using Matlab
DOWNLOAD
Download Fitting Curves And Sourfaces Using Matlab PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Fitting Curves And Sourfaces Using Matlab book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Curve And Surface Fitting With Splines
DOWNLOAD
Author : Paul Dierckx
language : en
Publisher: Oxford University Press
Release Date : 1995
Curve And Surface Fitting With Splines written by Paul Dierckx and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Computers categories.
Describes the algorithms and mathematical fundamentals of a widely-used FORTRAN package for curve and surface fitting with splines.
Curve And Surface Fitting With Matlab Linear And Nonlinear Regression
DOWNLOAD
Author : A Ramirez
language : en
Publisher:
Release Date : 2019-07-22
Curve And Surface Fitting With Matlab Linear And Nonlinear Regression written by A Ramirez and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-22 with categories.
You can fit curves and surfaces to data and view plots with the Curve Fitting app in MATLAB. Is possible: .Create, plot, and compare multiple fits.Use linear or nonlinear regression, interpolation, smoothing, and custom equations..View goodness-of-fit statistics, display confidence intervals and residuals, remove outliers and assess fit with validation data..Automatically generate code to fit and plot curves and surfaces, or export fits to the workspace for further analysis.Curve Fitting app makes it easy to plot and analyze fit at the command line. You can export individual fit to the workspace for further analysis, or you can generate MATLAB code to recreate all fit and plots in your session. By generating code, you can use your interactive curve fitting session to quickly assemble code for curve and surface fit and plots into useful programs.The Curve Fitting app allows convenient, interactive use of Curve Fitting Toolbox functions, without programming. You can, however, access Curve Fitting Toolbox functions directly, and write programs that combine curve fitting functions with MATLAB functions and functions from other toolboxes. This allows you to create a curve fitting environment that is precisely suited to your needs. Models and fit in the Curve Fitting app are managed internally as curve fitting objects. Objects are manipulated through a variety of functions called methods. You can create curve fitting objects, and apply curve fitting methods, outside of the Curve Fitting app
Chemical Engineering Analysis And Optimization Using Matlab
DOWNLOAD
Author : Weiguo Xie
language : en
Publisher: John Wiley & Sons
Release Date : 2025-01-15
Chemical Engineering Analysis And Optimization Using Matlab written by Weiguo Xie and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-15 with Technology & Engineering categories.
Tackle challenging optimization problems with MATLAB software Optimization techniques are used to measure the minimum or maximum value of a given function depending on circumstances and key factors. Engineering processes pertaining to design or manufacture involve optimization techniques at every stage, designed to minimize resource expenditure and maximize outcomes. Optimization problems are difficult and computationally intensive, but the increasingly widely-used MATLAB platform offers numerous tools by which engineers can tackle these essential elements of process and industrial design. Chemical Engineering Analysis and Optimization Using MATLAB offers an introduction to the cutting-edge, highly in-demand skills of computer-aided design and optimization. With a focus on chemical engineering analysis, the book uses the MATLAB platform to develop reader skills in programming, modeling, and more. It provides an overview of some of the most essential tools in modern engineering design. Chemical Engineering Analysis and Optimization Using MATLAB readers will also find: Case studies for developing specific skills in MATLAB and beyond Examples of code both within the text and on companion website End of chapter problems with accompanying solutions manual for instructors This textbook is ideal for advanced undergraduate and graduate students in chemical engineering and related disciplines, as well as professionals with backgrounds in engineering design.
Numerical Symbolic And Statistical Computing For Chemical Engineers Using Matlab
DOWNLOAD
Author : Ghosh, Pallab
language : en
Publisher: PHI Learning Pvt. Ltd.
Release Date : 2018-09-01
Numerical Symbolic And Statistical Computing For Chemical Engineers Using Matlab written by Ghosh, Pallab and has been published by PHI Learning Pvt. Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-01 with Mathematics categories.
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)
Applied Numerical Methods Using Matlab
DOWNLOAD
Author : Won Y. Yang
language : en
Publisher: John Wiley & Sons
Release Date : 2020-03-31
Applied Numerical Methods Using Matlab written by Won Y. Yang and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-31 with Mathematics categories.
This new edition provides an updated approach for students, engineers, and researchers to apply numerical methods for solving problems using MATLAB® This accessible book makes use of MATLAB® software to teach the fundamental concepts for applying numerical methods to solve practical engineering and/or science problems. It presents programs in a complete form so that readers can run them instantly with no programming skill, allowing them to focus on understanding the mathematical manipulation process and making interpretations of the results. Applied Numerical Methods Using MATLAB®, Second Edition begins with an introduction to MATLAB usage and computational errors, covering everything from input/output of data, to various kinds of computing errors, and on to parameter sharing and passing, and more. The system of linear equations is covered next, followed by a chapter on the interpolation by Lagrange polynomial. The next sections look at interpolation and curve fitting, nonlinear equations, numerical differentiation/integration, ordinary differential equations, and optimization. Numerous methods such as the Simpson, Euler, Heun, Runge-kutta, Golden Search, Nelder-Mead, and more are all covered in those chapters. The eighth chapter provides readers with matrices and Eigenvalues and Eigenvectors. The book finishes with a complete overview of differential equations. Provides examples and problems of solving electronic circuits and neural networks Includes new sections on adaptive filters, recursive least-squares estimation, Bairstow's method for a polynomial equation, and more Explains Mixed Integer Linear Programing (MILP) and DOA (Direction of Arrival) estimation with eigenvectors Aimed at students who do not like and/or do not have time to derive and prove mathematical results Applied Numerical Methods Using MATLAB®, Second Edition is an excellent text for students who wish to develop their problem-solving capability without being involved in details about the MATLAB codes. It will also be useful to those who want to delve deeper into understanding underlying algorithms and equations.
Basics Of Matlab Programming
DOWNLOAD
Author : R. Balaji
language : en
Publisher: Notion Press
Release Date : 2020-09-03
Basics Of Matlab Programming written by R. Balaji and has been published by Notion Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-03 with Technology & Engineering categories.
The first edition of ‘Basics of MATLAB Programming’ offers a brief glimpse of the power and flexibility of MATLAB. This book is intended to assist undergraduates with learning in programming, specifically in MATLAB. The MATLAB codes are given in Courier New font [MATLAB font] to get the feel of MATLAB environment. It combines engineering mathematics with MATLAB. This book has around ten chapters comprising Arrays, Functions, Control statements, Plotting, Simulink and other miscellaneous concepts. It consists of many real-life examples which help in better understanding of MATLAB.
Curve And Surface Fitting With Matlab Interpolation Smoothing And Spline Fitting
DOWNLOAD
Author : A Ramirez
language : en
Publisher:
Release Date : 2019-07-24
Curve And Surface Fitting With Matlab Interpolation Smoothing And Spline Fitting written by A Ramirez and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-24 with categories.
The Curve Fitting Toolbox software supports these nonparametric fitting methods: -"Interpolation Methods" - Estimate values that lie between known data points.-"Smoothing Splines" - Create a smooth curve through the data. You adjust the level of smoothness by varying a parameter that changes the curve from a least-squares straight-line approximation to a cubic spline interpolant.-"Lowess Smoothing" - Create a smooth surface through the data using locally weighted linear regression to smooth data.Interpolation is a process for estimating values that lie between known data points. There are several interpolation methods: - Linear: Linear interpolation. This method fit a different linear polynomial between each pair of data points for curves, or between sets of three points for surfaces.- Nearest neighbor: Nearest neighbor interpolation. This method sets the value of an interpolated point to the value of the nearest data point. Therefore, this method does not generate any new data points.- Cubic spline: Cubic spline interpolation. This method fit a different cubic polynomial between each pair of data points for curves, or between sets of three points for surfaces.After fitting data with one or more models, you should evaluate the goodness of fit A visual examination of the fitte curve displayed in Curve Fitting app should be your firs step. Beyond that, the toolbox provides these methods to assess goodness of fi for both linear and nonlinear parametric fits-"Goodness-of-Fit Statistics" -"Residual Analysis" -"Confidence and Prediction Bounds" The Curve Fitting Toolbox spline functions are a collection of tools for creating, viewing, and analyzing spline approximations of data. Splines are smooth piecewise polynomials that can be used to represent functions over large intervals, where it would be impractical to use a single approximating polynomial. The spline functionality includes a graphical user interface (GUI) that provides easy access to functions for creating, visualizing, and manipulating splines. The toolbox also contains functions that enable you to evaluate, plot, combine, differentiate and integrate splines. Because all toolbox functions are implemented in the open MATLAB language, you can inspect the algorithms, modify the source code, and create your own custom functions. Key spline features: -GUIs that let you create, view, and manipulate splines and manage and compare spline approximations-Functions for advanced spline operations, including differentiation integration, break/knot manipulation, and optimal knot placement-Support for piecewise polynomial form (ppform) and basis form (B-form) splines-Support for tensor-product splines and rational splines (including NURBS)- Shape-preserving: Piecewise cubic Hermite interpolation (PCHIP). This method preserves monotonicity and the shape of the data. For curves only.- Biharmonic (v4): MATLAB 4 grid data method. For surfaces only.- Thin-plate spline: Thin-plate spline interpolation. This method fit smooth surfaces that also extrapolate well. For surfaces only.If your data is noisy, you might want to fit it using a smoothing spline. Alternatively, you can use one of the smoothing methods. The smoothing spline s is constructed for the specified smoothing parameter p and the specified weights wi.
Curve And Surface Fitting With Matlab Functions And Examples
DOWNLOAD
Author : A Ramirez
language : en
Publisher:
Release Date : 2019-07-24
Curve And Surface Fitting With Matlab Functions And Examples written by A Ramirez and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-24 with categories.
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.This book delves into the curve and surface fitting functions presented its complete syntax and completing them with examples.
Introduction To Modeling And Simulation
DOWNLOAD
Author : Mark W. Spong
language : en
Publisher: John Wiley & Sons
Release Date : 2023-02-13
Introduction To Modeling And Simulation written by Mark W. Spong and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-13 with Technology & Engineering categories.
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.
Applied Numerical Methods For Chemical Engineers
DOWNLOAD
Author : Navid Mostoufi
language : en
Publisher: Academic Press
Release Date : 2022-05-22
Applied Numerical Methods For Chemical Engineers written by Navid Mostoufi and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-22 with Technology & Engineering categories.
Applied Numerical Methods for Chemical Engineers emphasizes the derivation of a variety of numerical methods and their application to the solution of engineering problems, with special attention to problems in the chemical engineering field. These algorithms encompass linear and nonlinear algebraic equations, eigenvalue problems, finite difference methods, interpolation, differentiation and integration, ordinary differential equations, boundary value problems, partial differential equations, and linear and nonlinear regression analysis. MATLAB is adopted as the calculation environment throughout the book because of its ability to perform all the calculations in matrix form, its large library of built-in functions, its strong structural language, and its rich graphical visualization tools. Through this book, students and other users will learn about the basic features, advantages and disadvantages of various numerical methods, learn and practice many useful m-files developed for different numerical methods in addition to the MATLAB built-in solvers, develop and set up mathematical models for problems commonly encountered in chemical engineering, and solve chemical engineering related problems through examples and after-chapter problems with MATLAB by creating application m-files. - Clearly and concisely develops a variety of numerical methods and applies them to the solution of chemical engineering problems. These algorithms encompass linear and nonlinear algebraic equations, eigenvalue problems, finite difference methods, interpolation, linear and nonlinear regression analysis, differentiation and integration, ordinary differential equations, boundary value problems, and partial differential equations - Includes systematic development of the calculus of finite differences and its application to the integration of differential equations, and a detailed discussion of nonlinear regression analysis, with powerful programs for implementing multivariable nonlinear regression and statistical analysis of the results - Makes extensive use of MATLAB and Excel, with most of the methods discussed implemented into general MATLAB functions. All the MATLAB-language scripts developed are listed in the text and included in the book's companion website - Includes numerous real-world examples and homework problems drawn from the field of chemical and biochemical engineering