Graphical Representations of Probability Density Functions Generated Using MATLAB Code for Reference
Visualizations of Various Probability Density Functions Created with MATLAB Code for Informational Use
Estimating Maximum Likelihood Using Probability Density Functions in MATLAB
Calculating maximum likelihood estimates for given data and corresponding probability density functions using MATLAB's numerical optimization tools
2D Dataset Parzen Window Non-Parametric PDF Estimation with 3D Visualization
Implementation of Parzen window non-parametric probability density function estimation for 2D datasets, featuring 3D visualization results. Includes complete documentation, program execution instructions, MATLAB source code, and graphical outputs. Developed as a pattern recognition assignment focusing on kernel density estimation techniques.
Implementation of Parzen Window Density Estimation
This code implements Parzen window estimation for probability density functions, a fundamental technique in pattern recognition applications including clustering, classification, and anomaly detection.
Simulation of Nakagami Probability Density Function Using Monte Carlo Method
Implementation of Monte Carlo simulation for Nakagami probability density function with code-based parameter estimation and statistical analysis
Waveform Functions with Laplace Distribution and Probability Density Functions
Comprehensive collection of waveform generation algorithms including Laplace distribution implementations, along with various probability density function (PDF) methods for signal processing and statistical analysis
Gaussian Models in Pattern Recognition
Gaussian Models in Pattern Recognition with MATLAB Implementation
Maximum Likelihood Estimation for Probability Density Functions using MATLAB
Implementing Maximum Likelihood Estimation (MLE) for probability density functions in MATLAB with optimization algorithms and statistical toolbox functions