Explore MATLAB source code curated for "参数估计" with clean implementations, documentation, and examples.
This radon-based image motion blur parameter estimation program calculates blur angle and blur scale parameters, though oversized images require preprocessing before use - implementing Radon transform analysis and peak detection algorithms to extract motion blur characteristics from image spectra.
Implementation of Fractional Fourier Transform (FrFT) for parameter estimation (chirp rate and initial frequency) of Linear Frequency Modulation (LFM) signals using coarse-to-fine order search algorithm, requiring external frft.m utility function download.
Estimation of 2D Signal Angle of Arrival and Parameters with Matrix Pencil Algorithm Implementation
Implementation of spread spectrum signal detection and parameter estimation using MATLAB, demonstrating superior detection capability under low signal-to-noise ratio conditions through cross-correlation analysis and peak detection algorithms
In statistical computing, the Expectation-Maximization (EM) algorithm is an iterative method for finding maximum likelihood (MLE) or maximum a posteriori (MAP) estimates of parameters in probabilistic models that depend on unobserved latent variables. The EM algorithm is widely used in machine learning and computer vision for data clustering applications. The algorithm alternates between an expectation step (E-step), which computes the expected value of the latent variables given current parameters, and a maximization step (M-step), which updates parameters to maximize the expected log-likelihood.
Parameter estimation procedure for multi-component Linear Frequency Modulated (LFM) signals through Fractional Fourier Transform with code implementation insights
Parameter estimation and peak detection techniques for Fractional Fourier Transform implementation, including peak search algorithms and optimization methods
MATLAB implementation of Expectation-Maximization (EM) algorithm - an iterative method for finding maximum likelihood or maximum a posteriori estimates of parameters in statistical models with unobserved latent variables, featuring probability model handling and parameter optimization.
High-precision lithium battery model for accurate parameter estimation utilizing MATLAB Simulink and Simscape toolboxes
MATLAB implementation for parameter estimation of defocus blurred images with Lucy-Richardson deconvolution method for effective image restoration