Admin مدير المنتدى
![مدير المنتدى مدير المنتدى](https://2img.net/i/itest/ranks/stars/stars13.gif)
![Admin](https://2img.net/u/1711/56/32/51/avatars/1-20.jpg)
عدد المساهمات : 18928 التقييم : 35294 تاريخ التسجيل : 01/07/2009 الدولة : مصر العمل : مدير منتدى هندسة الإنتاج والتصميم الميكانيكى
![كتاب MATLAB - Curve Fitting Toolbox - User's Guide Empty](https://2img.net/i/fa/empty.gif) | موضوع: كتاب MATLAB - Curve Fitting Toolbox - User's Guide الخميس 23 يونيو 2022, 8:21 pm | |
| ![](https://i.servimg.com/u/f61/15/36/74/14/subscr10.gif)
أخواني في الله أحضرت لكم كتاب MATLAB - Curve Fitting Toolbox - User's Guide Getting Started
![كتاب MATLAB - Curve Fitting Toolbox - User's Guide M_c_f_12](https://i.servimg.com/u/f61/15/36/74/14/m_c_f_12.jpg) و المحتوى كما يلي :
Curve Fitting Toolbox Product Description . 1-2 Key Features 1-2 Curve Fitting Tools 1-3 Curve Fitting . 1-4 Interactive Curve Fitting . 1-4 Programmatic Curve Fitting . 1-4 Surface Fitting 1-6 Interactive Surface Fitting 1-6 Programmatic Surface Fitting 1-6 Spline Fitting . 1-8 About Splines in Curve Fitting Toolbox . 1-8 Interactive Spline Fitting . 1-8 Programmatic Spline Fitting . 1-8 Interactive Fitting Interactive Curve and Surface Fitting . 2-2 Introducing the Curve Fitting App 2-2 Fit a Curve 2-2 Fit a Surface . 2-3 Model Types for Curves and Surfaces 2-4 Selecting Data to Fit in Curve Fitting App . 2-5 Save and Reload Sessions . 2-6 Data Selection 2-8 Selecting Data to Fit in Curve Fitting App . 2-8 Selecting Compatible Size Surface Data 2-9 Troubleshooting Data Problems . 2-10 Create Multiple Fits in Curve Fitting App . 2-11 Refining Your Fit 2-11 Creating Multiple Fits 2-11 Duplicating a Fit . 2-11 Deleting a Fit . 2-12 Displaying Multiple Fits Simultaneously . 2-12 Using the Statistics in the Table of Fits 2-13 v ContentsGenerating MATLAB Code and Exporting Fits . 2-15 Interactive Code Generation and Programmatic Fitting . 2-15 Compare Fits in Curve Fitting App . 2-16 Interactive Curve Fitting Workflow . 2-16 Loading Data and Creating Fits . 2-16 Determining the Best Fit 2-18 Analyzing Your Best Fit in the Workspace 2-22 Saving Your Work 2-24 Surface Fitting to Franke Data 2-26 Programmatic Curve and Surface Fitting 3 Curve and Surface Fitting . 3-2 Fitting a Curve . 3-2 Fitting a Surface 3-2 Model Types and Fit Analysis 3-2 Workflow for Command Line Fitting . 3-3 Curve and Surface Fitting Objects and Methods 3-6 Curve Fitting Objects 3-6 Curve Fitting Methods . 3-7 Surface Fitting Objects and Methods 3-9 Linear and Nonlinear Regression 4 Parametric Fitting . 4-2 Parametric Fitting with Library Models . 4-2 Selecting a Model Type Interactively 4-3 Selecting Model Type Programmatically 4-4 Using Normalize or Center and Scale 4-4 Specifying Fit Options and Optimized Starting Points 4-5 List of Library Models for Curve and Surface Fitting 4-10 Use Library Models to Fit Data 4-10 Library Model Types 4-10 Model Names and Equations . 4-11 Polynomial Models . 4-14 About Polynomial Models 4-14 Fit Polynomial Models Interactively 4-15 Fit Polynomials Using the Fit Function 4-16 Polynomial Model Fit Options . 4-25 Defining Polynomial Terms for Polynomial Surface Fits 4-26 vi ContentsExponential Models . 4-28 About Exponential Models . 4-28 Fit Exponential Models Interactively 4-28 Fit Exponential Models Using the fit Function . 4-30 Fourier Series . 4-34 About Fourier Series Models 4-34 Fit Fourier Models Interactively . 4-34 Fit Fourier Models Using the fit Function 4-35 Gaussian Models . 4-42 About Gaussian Models . 4-42 Fit Gaussian Models Interactively 4-42 Fit Gaussian Models Using the fit Function . 4-43 Power Series . 4-45 About Power Series Models 4-45 Fit Power Series Models Interactively . 4-45 Fit Power Series Models Using the fit Function 4-46 Rational Polynomials 4-48 About Rational Models 4-48 Fit Rational Models Interactively 4-48 Selecting a Rational Fit at the Command Line . 4-49 Example: Rational Fit . 4-49 Sum of Sines Models 4-54 About Sum of Sines Models 4-54 Fit Sum of Sine Models Interactively . 4-54 Selecting a Sum of Sine Fit at the Command Line 4-55 Weibull Distributions . 4-56 About Weibull Distribution Models . 4-56 Fit Weibull Models Interactively . 4-56 Selecting a Weibull Fit at the Command Line . 4-57 Least-Squares Fitting . 4-59 Introduction 4-59 Error Distributions . 4-59 Linear Least Squares . 4-60 Weighted Least Squares . 4-62 Robust Least Squares . 4-63 Nonlinear Least Squares 4-65 Robust Fitting 4-66 Custom Linear and Nonlinear Regression 5 Custom Models . 5-2 Custom Models vs. Library Models 5-2 Selecting a Custom Equation Fit Interactively 5-2 Selecting a Custom Equation Fit at the Command Line . 5-4 viiCustom Linear Fitting 5-6 About Custom Linear Models 5-6 Selecting a Linear Fitting Custom Fit Interactively 5-6 Selecting Linear Fitting at the Command Line . 5-7 Fit Custom Linear Legendre Polynomials . 5-8 Custom Nonlinear Census Fitting . 5-16 Custom Nonlinear ENSO Data Analysis . 5-19 Load Data and Fit Library and Custom Fourier Models 5-19 Use Fit Options to Constrain a Coefficient . 5-21 Create Second Custom Fit with Additional Terms and Constraints . 5-23 Create a Third Custom Fit with Additional Terms and Constraints 5-24 Gaussian Fitting with an Exponential Background . 5-27 Surface Fitting to Biopharmaceutical Data 5-30 Interpolation and Smoothing 6 Nonparametric Fitting . 6-2 Interpolation Methods . 6-3 About Interpolation Methods 6-3 Selecting an Interpolant Fit . 6-6 Selecting an Interpolant Fit Interactively . 6-6 Fit Linear Interpolant Models Using the fit Function . 6-6 Smoothing Splines . 6-9 About Smoothing Splines . 6-9 Selecting a Smoothing Spline Fit Interactively 6-10 Fit Smoothing Spline Models Using the fit Function 6-11 Example: Nonparametric Fitting with Cubic and Smoothing Splines 6-12 Lowess Smoothing 6-16 About Lowess Smoothing 6-16 Selecting a Lowess Fit Interactively 6-16 Fit Lowess Models Using the fit Function 6-17 Fit Smooth Surfaces To Investigate Fuel Efficiency . 6-19 Filtering and Smoothing Data 6-27 About Data Smoothing and Filtering 6-27 Moving Average Filtering 6-27 Savitzky-Golay Filtering . 6-28 Local Regression Smoothing 6-29 Example: Smoothing Data 6-33 Example: Smoothing Data Using Loess and Robust Loess 6-34 viii ContentsFit Postprocessing 7 Explore and Customize Plots 7-2 Displaying Fit and Residual Plots . 7-2 Viewing Surface Plots and Contour Plots 7-3 Using Zoom, Pan, Data Cursor, and Outlier Exclusion 7-4 Customizing the Fit Display . 7-5 Print to MATLAB Figures . 7-6 Remove Outliers 7-8 Remove Outliers Interactively 7-8 Exclude Data Ranges 7-8 Remove Outliers Programmatically 7-9 Select Validation Data . 7-12 Generate Code and Export Fits to the Workspace 7-13 Generating Code from the Curve Fitting App . 7-13 Exporting a Fit to the Workspace 7-14 Evaluate a Curve Fit 7-16 Evaluate a Surface Fit . 7-25 Compare Fits Programmatically . 7-32 Evaluating Goodness of Fit . 7-44 How to Evaluate Goodness of Fit 7-44 Goodness-of-Fit Statistics 7-45 Residual Analysis . 7-48 Plotting and Analysing Residuals 7-48 Example: Residual Analysis 7-49 Confidence and Prediction Bounds 7-52 About Confidence and Prediction Bounds 7-52 Confidence Bounds on Coefficients . 7-52 Prediction Bounds on Fits 7-53 Compute Prediction Intervals . 7-55 Differentiating and Integrating a Fit . 7-57 ixSpline Fitting About Splines 8 Introducing Spline Fitting 8-2 About Splines in Curve Fitting Toolbox . 8-2 Spline Overview 8-2 Interactive Spline Fitting . 8-3 Programmatic Spline Fitting . 8-3 Curve Fitting Toolbox Splines and MATLAB Splines . 8-4 Curve Fitting Toolbox Splines 8-4 Splines . 8-5 MATLAB Splines 8-5 Expected Background 8-6 Vector Data Type Support . 8-6 Spline Function Naming Conventions 8-6 Arguments for Curve Fitting Toolbox Spline Functions . 8-7 Acknowledgments . 8-7 Simple Spline Examples 9 Cubic Spline Interpolation 9-2 Cubic Spline Interpolant of Smooth Data . 9-2 Periodic Data 9-3 Other End Conditions 9-4 General Spline Interpolation . 9-4 Knot Choices 9-5 Smoothing 9-6 Least Squares 9-7 Vector-Valued Functions 9-9 Fitting Values at N-D Grid with Tensor-Product Splines . 9-11 Fitting Values at Scattered 2-D Sites with Thin-Plate Smoothing Splines . 9-12 Postprocessing Splines 9-13 x ContentsTypes of Splines 10 Types of Splines: ppform and B-form . 10-2 Polynomials vs. Splines 10-2 ppform 10-2 B-form 10-2 Knot Multiplicity . 10-3 B-Splines and Smoothing Splines . 10-4 B-Spline Properties . 10-4 Variational Approach and Smoothing Splines . 10-5 Multivariate and Rational Splines . 10-6 Multivariate Splines 10-6 Rational Splines . 10-7 The ppform 10-8 Introduction to ppform 10-8 Definition of ppform 10-8 Constructing and Working with ppform Splines . 10-10 Constructing a ppform . 10-10 Working With ppform Splines 10-10 Example ppform 10-11 The B-form . 10-13 Introduction to B-form . 10-13 Definition of B-form . 10-13 B-form and B-Splines 10-13 B-Spline Knot Multiplicity . 10-14 Choice of Knots for B-form 10-15 Constructing and Working with B-form Splines . 10-17 Construction of B-form . 10-17 Working With B-form Splines 10-17 Example: B-form Spline Approximation to a Circle 10-18 Multivariate Tensor Product Splines 10-21 Introduction to Multivariate Tensor Product Splines . 10-21 B-form of Tensor Product Splines . 10-21 Construction With Gridded Data 10-21 ppform of Tensor Product Splines . 10-22 Example: The Mobius Band . 10-22 NURBS and Other Rational Splines . 10-23 Introduction to Rational Splines 10-23 rsform: rpform, rBform . 10-23 Constructing and Working with Rational Splines 10-25 Rational Spline Example: Circle 10-25 Rational Spline Example: Sphere . 10-26 Functions for Working With Rational Splines 10-26 xiConstructing and Working with stform Splines . 10-28 Introduction to the stform 10-28 Construction and Properties of the stform 10-28 Working with the stform 10-29 Advanced Spline Examples 11 Least-Squares Approximation by Natural Cubic Splines . 11-2 Problem . 11-2 General Resolution . 11-2 Need for a Basis Map . 11-2 A Basis Map for “Natural” Cubic Splines . 11-3 The One-line Solution . 11-3 The Need for Proper Extrapolation . 11-3 The Correct One-Line Solution 11-4 Least-Squares Approximation by Cubic Splines 11-5 Solving A Nonlinear ODE 11-6 Problem . 11-6 Approximation Space . 11-6 Discretization . 11-6 Numerical Problem . 11-7 Linearization . 11-7 Linear System to Be Solved 11-7 Iteration . 11-8 Construction of the Chebyshev Spline . 11-10 What Is a Chebyshev Spline? 11-10 Choice of Spline Space . 11-10 Initial Guess . 11-10 Remez Iteration 11-11 Approximation by Tensor Product Splines . 11-14 Choice of Sites and Knots . 11-14 Least Squares Approximation as Function of y . 11-14 Approximation to Coefficients as Functions of x 11-15 The Bivariate Approximation 11-16 Switch in Order 11-17 Approximation to Coefficients as Functions of y 11-18 The Bivariate Approximation 11-19 Comparison and Extension 11-20 Examples 12 Polynomial Curve Fitting 12-2 Surface Fitting With Custom Equations to Biopharmaceutical Data 12-14 xii ContentsHow to Construct Splines . 12-20 Construct and Work with the B-form 12-40 Construct and Work with the PPFORM 12-57 How to Choose Knots 12-66 Cubic Spline Interpolation 12-74 Cubic Smoothing Splines . 12-94 Fitting a Spline to Titanium Test Data . 12-102 Splines in the Plane 12-115 Constructing Spline Curves in 2D and 3D . 12-126 Smoothing a Histogram . 12-130 Bivariate Tensor Product Splines 12-133 Solving a Nonlinear ODE with a Boundary Layer by Collocation 12-145 Construction of a Chebyshev Spline . 12-156 Functions #ماتلاب,#متلاب,#Matlab,
كلمة سر فك الضغط : books-world.net The Unzip Password : books-world.net أتمنى أن تستفيدوا من محتوى الموضوع وأن ينال إعجابكم رابط من موقع عالم الكتب لتنزيل كتاب MATLAB - Curve Fitting Toolbox - User's Guide رابط مباشر لتنزيل كتاب MATLAB - Curve Fitting Toolbox - User's Guide ![](https://i.servimg.com/u/f61/15/36/74/14/sign_110.gif)
|
|