Implementation of Vector Quantization Using the LBG Algorithm
- Login to Download
- 1 Credits
Resource Overview
This graduation project demonstrates the implementation of vector quantization through the LBG algorithm using MATLAB, focusing on code structure, algorithm workflow, and vector dimension reduction techniques.
Detailed Documentation
In my graduation project, I researched and implemented vector quantization using the Linde-Buzo-Gray (LBG) algorithm. This iterative clustering algorithm efficiently compresses high-dimensional datasets into lower-dimensional codebook vectors by minimizing distortion metrics like Mean Squared Error. The MATLAB implementation involves key steps: initial codebook generation using splitting methods, nearest-neighbor classification with Euclidean distance calculations, and centroid updates through iterative optimization. The project deepened my understanding of vector quantization principles (including codebook design and convergence criteria) while enhancing my skills in algorithm design and MATLAB programming for signal processing applications.
- Login to Download
- 1 Credits