Iterative Parameter Fitting for Nonlinear Functions (Ionospheric Delay Model)
Iterative implementation of parameter fitting for nonlinear ionospheric delay models in GNSS measurement error modeling
Explore MATLAB source code curated for "迭代" with clean implementations, documentation, and examples.
Iterative implementation of parameter fitting for nonlinear ionospheric delay models in GNSS measurement error modeling
An adaptive iterative reweighted penalized least squares algorithm suitable for background removal in Raman spectroscopy or chromatographic data analysis, with robust noise filtering capabilities and customizable parameter optimization.
This program presents advanced control algorithms using adaptive dynamic programming, featuring iterative controller design methodologies with practical implementation examples.
Implementation of LMS algorithm with 200 iterations to plot adaptive antenna patterns under 30 dB interference-to-noise ratio conditions, including performance analysis in high-noise environments
Implementation of Iterative Optimal Threshold Segmentation Algorithm using Bayesian Classification for Image Thresholding - Successfully running in MATLAB 7.0 environment with error-free execution
Comparative analysis of simplified MAX-LOG-MAP vs LOG-MAP algorithms using standard 1024-length interleaving with 1-3 iterations under grid conditions, and simplified MAX-LOG-MAP vs threshold-based MAX-LOG-MAP with 640-length interleaving over 10 iterations, including implementation insights for turbo decoding systems.
MATLAB implementation of iterative blind deconvolution algorithm for image deblurring in digital image processing, featuring complete source code for restoring blurred images to sharp, recognizable quality
Iterative Closest Point Algorithm: Computing Optimal Alignment Between Two Point Clouds with Code Implementation Insights
This kernel-based partial least squares algorithm first applies a kernel function for nonlinear transformation of the original matrix, then solves the problem through nonlinear iterative optimization.
This MATLAB program implements iterative image processing algorithms to identify regions of interest (ROIs) in images. The included M-files perform comprehensive ROI analysis, outputting region properties including area size, mean intensity, standard deviation, minimum/maximum values, median intensity, and centroid coordinates. The implementation utilizes morphological operations and statistical analysis for robust ROI detection.