MATLAB Genetic Algorithm Toolbox Implementation
Genetic Algorithm Toolbox with customizable files and embedded functionality, allowing modification of core components and integration of user-defined functions for specific optimization requirements.
Explore MATLAB source code curated for "matlab代码" with clean implementations, documentation, and examples.
Genetic Algorithm Toolbox with customizable files and embedded functionality, allowing modification of core components and integration of user-defined functions for specific optimization requirements.
Discrete signals and their MATLAB implementation, covering unit impulse sequence, unit step sequence, ramp sequence with code examples and algorithmic explanations
MATLAB code implementation of the EM segmentation algorithm with superior results, featuring probabilistic modeling and iterative optimization for image partitioning.
MATLAB implementation of convolutional encoding and Viterbi decoding algorithms, sourced from "Modern Communication Systems Using MATLAB" English edition - proven effective for practical applications with clean, well-structured code
A practical firefly algorithm implementation in MATLAB featuring easy adaptation through test function replacement. Includes guidelines for parameter adjustment such as firefly population size and light absorption coefficient.
MATLAB code implementation of MeanShift algorithm for robust moving human tracking with kernel function optimization and parameter configuration
Comprehensive OFDM simulation including channel modeling, multipath effects, and multi-component waveform analysis with detailed technical explanations and MATLAB implementation insights
MATLAB implementation of simulated annealing algorithm for computing the minimum value of a function, featuring parameter configuration and optimization process explanation
MATLAB implementation of pedestrian detection algorithm using HOG, LBP, and HIKSVM, including the libsvm-mat-3.0-1 package with comprehensive feature extraction and classification code.
This MATLAB M-file implements Wiener filtering primarily for signal and image processing applications, featuring two practical implementation examples with code-level demonstrations of noise reduction and enhancement techniques.