Titlebook: Vector Quantization and Signal Compression; Allen Gersho,Robert M. Gray Textbook 1992 Springer Science+Business Media New York 1992 Jitter

字謎游戲

SEEK

Muscularis

Bit Allocation and Transform Codingracterize the signal. Each such parameter may have a different physical meaning and may require a different relative accuracy of reproduction to achieve a desired overall quality of the reconstructed signal. The number of bits available to collectively describe this set of parameters is inevitably l

暖昧關(guān)系

Entropy Codingder and processed by the decoder. In some communication and storage systems, fixed rate operation is not desirable because the data source may display wide variations in activity. For example, sampled speech may change very little during long periods of silence and then exhibit very complex behavior

疏遠(yuǎn)天際

Vector Quantization I:Structure and Performance dimension to multiple dimensions is a major step and allows a wealth of new ideas, concepts, techniques, and applications to arise that often have no counterpart in the simple case of scalar quantization. While scalar quantization is used primarily for analog-to-digital conversion, VQ is used with

cutlery

subacute

Perceive

松軟無(wú)力

Organization

Textbook 1992 order to "eliminate duplication and redundancy. " This quote both states a goal of data compression and illustrates its common need: the removal of duplication (or redundancy) can provide a more efficient representation of data and the quoted phrase is itself a candidate for such surgery. Not only