1996
DOI: 10.1109/97.475819
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Nonsquare transform vector quantization

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Cited by 11 publications
(3 citation statements)
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“…We therefore selected the optimum numbers for the spectrum magnitude and phase as 15 and 8 in the first enhancement layer 1 and 30 and 16 in the second enhancement layer, respectively. By measuring the spectral distortion (SD) (Lupini and Cuperman 1996), it is possible to compare two structures, namely multi-stage VQ both with and without DCT. The results are described in Table 4.…”
Section: Figmentioning
confidence: 99%
“…We therefore selected the optimum numbers for the spectrum magnitude and phase as 15 and 8 in the first enhancement layer 1 and 30 and 16 in the second enhancement layer, respectively. By measuring the spectral distortion (SD) (Lupini and Cuperman 1996), it is possible to compare two structures, namely multi-stage VQ both with and without DCT. The results are described in Table 4.…”
Section: Figmentioning
confidence: 99%
“…with A N an N × M matrix. The described approach is known as nonsquare transform [14,15], and optimality criterion can be found for the matrices A N and B N . Similar to the case of partial quantization, the method is more suitable for low dimension, since the transformation process introduces losses that are not reversible.…”
Section: Variable-to-fixed-dimension Conversion Via Interpolation or mentioning
confidence: 99%
“…The discipline of variable dimension quantization, it appears, has not gained much attention. Though, in [6], a method for variable dimension quantization was proposed and then in [7], this method was applied to the problem of quantization of sinusoidal parameters for speech coding. Specifically, this was done by a variable-tofixed dimension transform followed by quantization.…”
Section: Introductionmentioning
confidence: 99%