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Predictive vector quantizer using constrained optimization

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2 Author(s)
S. A. Rizvi ; Dept. of Electr. & Comput. Eng., State Univ. of New York, Buffalo, NY, USA ; N. M. Nasrabadi

A joint optimization technique is developed for designing the predictor and quantizer of a predictive vector quantizer (PVQ). The proposed technique is based on a constrained optimization technique that makes use of a Lagrangian formulation and iteratively solves the Lagrangian error function to obtain a locally optimal solution for the predictor and quantizer. Simulation results show that the proposed PVQ design outperforms the conventional PVQ schemes, such as the closed-loop design and the jointly-optimized technique.<>

Published in:

IEEE Signal Processing Letters  (Volume:1 ,  Issue: 1 )