A finite-state vector quantizer called dynamic finite-state vector quantization (DFSVQ) is investigated with regard to its subcodebook construction. In DFSVQ each input vector is encoded by a small codebook called the subcodebook which is created from a much larger codebook called the supercodebook by selecting (reordering procedure) a set of appropriate codevectors. The performance of the DFSVQ depends on this reordering procedure. In the paper, several reordering procedures including the conditional histogram, address prediction, vector prediction, nearest neighbor design and the frequency usage of codevectors are introduced and their performance are evaluated by comparing their hit ratios (the number of blocks encoded by the subcodebook) and their computational complexity.
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