Vector quantization and signal compression
Vector quantization and signal compression
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In the first section of this paper. we investigate three algorithms that orthogonalize codebooks in a multi-stage CELP coder. They carry out the same processing. a locally optimal modeling of the perceptual signal. but the computational costs differ. We show that the "Recursive Modified Gram-Schmidt" algorithm yields less computational extra-cost than the other two. In the second section. an orthogonal codebook is defined a priori and we observe an equivalence to orthogonal transform coding. Three methods based on the Karhunen-Loeve transform for designing this codebook are compared. A partitioned shape gain VQ is applied in the transform domain.