Non-Uniform Rational B-Spline Curve Fitting
Develop a program for fitting non-uniform rational B-spline (NURBS) curves with robust data fitting capabilities
Data Fitting and interp1 - Univariate Function Interpolation
This collection includes code implementations for data fitting, interp1 - univariate function interpolation, spline - spline interpolation, polyfit - polynomial interpolation or fitting, curvefit - curve fitting, caspe - spline interpolation with various boundary conditions, casps - spline fitting (not available), interp2 - bivariate function interpolation, griddata - bivariate interpolation for irregular data, interp - non-monotonic point interpolation, and lagrange - Lagrange interpolation method.
Data Curve Fitting for Power Law Distribution Analysis
Performing data curve fitting in MATLAB to examine power law distribution characteristics using log-log coordinates, calculating the power exponent, and visualizing results through comparative plotting.
Data Fitting Techniques
Data Fitting % interp1 - 1D Interpolation % spline - Spline Interpolation % polyfit - Polynomial Interpolation and Fitting % curvefit - Curve Fitting % caspe - Spline Interpolation with Various Boundary Conditions % casps - Spline Fitting (Not Available) % interp2 - 2D Interpolation % griddata - 2D Interpolation for Irregular Data % *interp - Non-monotonic Node Interpolation % *lagrange - Lagrange Interpolation Method
MATLAB Neural Network Toolbox Implementation with Code Examples
Implementing Data Fitting and Predictive Control Using Neural Network Toolbox with Algorithm Explanations
Data Fitting Using Orthogonal Polynomials
Performing curve fitting on GPS sample points using orthogonal polynomials. The program reads GPS sampling data and implements orthogonal polynomial fitting algorithms.
Neural Network Prediction Program
Application Context: Suitable for scenarios with large existing datasets requiring comprehensive fitting and prediction analysis. Key Technology: Utilizes intelligent neural network control methods to perform data analysis and training on existing datasets, generating a composite error function. The trained model is then tested with validation data, producing comparative visualizations between predicted and actual results through appropriate plotting functions.
Data Fitting Implementation Using the RANSAC Algorithm
Data Fitting Implementation Using the RANSAC Algorithm; This powerful algorithm can be applied to various computer vision tasks such as multi-view image matching with robust outlier rejection capabilities.
Creating 3D Data Surface Plots with MATLAB
Implementing 3D data surface visualization using MATLAB with curve fitting techniques and enhanced graphical representations.
Gaussian Fitting Implementation in MATLAB
Gaussian fitting in MATLAB is a powerful data fitting technique that utilizes Gaussian functions to model various datasets. This method is particularly useful for its versatility in scientific computing and engineering applications.