表脸
发表于 2025-3-25 04:08:04
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车床
发表于 2025-3-25 08:08:40
0893-3405 anizing in 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.
Chronic
发表于 2025-3-25 14:20:50
Random Processes and Linear Systems process. Where this is not the case, there would be no need to communicate the signal—it would already be known to the potential user. In addition to the original signal, the system itself may have random components such as the addition of random noise or the introduction of digital errors in a random fashion.
conflate
发表于 2025-3-25 16:30:15
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排名真古怪
发表于 2025-3-25 20:51:48
Vector Quantization II:Optimality and Design A few of the ideas are sketched, but the detailed developments are left to the literature. See in particular Chapter 5 of and the original references such as , , , , , .
capillaries
发表于 2025-3-26 03:31:25
Predictive Vector Quantizationders possessing memory may be more efficient in the sense of providing better performance at given bit rates and complexity by taking advantage of the inter-vector or inter-block dependence or correlation.
有机体
发表于 2025-3-26 07:54:57
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propose
发表于 2025-3-26 11:31:21
Random Processes and Linear Systemsools and techniques of linear systems play an important part in their analysis. In a mathematical model of a communication system in general and a signal coding system in particular, it is usually assumed that the data to be communicated (or stored, compressed, processed,...) is produced by a random
财产
发表于 2025-3-26 12:54:54
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鉴赏家
发表于 2025-3-26 17:58:51
Scalar Quantization I: Structure and Performanceating value from a predetermined finite set of allowed numerical values. Ordinarily the input value is . that is, it may take on any value from a continuous range of possible amplitudes; furthermore, the output is ., being uniquely specified by an integer in the set {1, 2, 3, • • •, ., where . is th