Abstract
A novel variable‐rate vector quantizer (VQ) design algorithm using both genetic and fuzzy clustering techniques is presented. The algorithm, termed genetic fuzzy entropy‐constrained VQ (GFECVQ) design algorithm, has a superior rate‐distortion performance than that of the existing variable‐rate VQ design algorithms. The algorithm utilizes fuzzy clustering technique to enhance the rate‐distortion performance for the VQ design. In addition, a novel genetic algorithm is employed to ensure the robustness of the performance against the selection of initial parameters. Simulation results demonstrate that the FECVQ can be an effective alternative for the design of variable‐rate VQs.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
