MATLAB Source Code for Object Recognition
MATLAB source code for object recognition, complete with implementation files and accompanying research paper, available for download and study.
Explore MATLAB source code curated for "论文" with clean implementations, documentation, and examples.
MATLAB source code for object recognition, complete with implementation files and accompanying research paper, available for download and study.
This program implements image haze removal based on the paper "Single Image Haze Removal Using Dark Channel Prior" - complete with source code and implementation details
MATLAB simulation of Turbo codes featuring full source code, performance graphs, and supporting research paper. Includes BER analysis, encoding/decoding algorithms implementation, and comprehensive technical documentation.
A comprehensive resource on image smoothing techniques, including both research paper and executable MATLAB code. This package shares practical implementations and theoretical foundations for effective image noise reduction and enhancement.
Classic Image Noise Variance Estimation Methods (Research Papers and Source Code Implementations)
Several papers and programs on LBP face recognition methods, highly valuable for learning LBP with practical implementation insights
This simulation program represents the most comprehensive OFDM source code available in current forums, thoroughly debugged and verified to be error-free. It offers significant research value for graduate students working on simulation projects and OFDM system-related theses who lack complete simulation resources. The suite includes 52 modular simulation components capable of generating 52 distinct simulation diagrams covering various OFDM system aspects.
MATLAB simulation program for Rayleigh channel with implementation of "A Fast and Accurate Rayleigh Fading Simulator" algorithm
This paper applies wavelet transform for image edge extraction following established evaluation criteria. We implement an adaptive threshold-based edge detection method using wavelet transform, validated through computational experiments. Performance comparison with traditional edge detection approaches demonstrates the effectiveness of the proposed methodology through algorithmic implementation and quantitative analysis.
Several academic papers on fuzzy kernel clustering algorithms accompanied by MATLAB implementations, enabling practical learning through hands-on coding exercises to master fuzzy clustering methodologies.