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1-1 a fundamental question of data compression is "what are we going to compress" and how do you understand that?

A: We want to compress the signal space, that is, the physical space, time interval, electromagnetic frequency band. That is, the airspace, time domain and frequency domain space occupied by a signal.

1-2 Another basic problem with data compression is "Why compress", and how do you understand it?

A: The reason why data compression is needed is because of the number of people who generate and use my information more and more, the number of bytes required to represent multimedia data can be very large. If the data compression is not done, it will make the transmission or storage is difficult to practical, the use of data compression can be faster transmission of a variety of sources, on the existing communication trunk to open more parallel services, reduce emissivity, compressed data storage capacity. With data compression, you can reduce storage space and reduce storage space to increase transmission efficiency and conserve bandwidth. You can also reduce the redundancy of your data.

1-6 How is data compression categorized?

A: Data compression is divided into reversible compression (redundancy compression, entropy coding) and non-inverting compression (entropy compression). Reversible compression includes statistical coding and other encodings. Non-reversible compression also includes two kinds of feature extraction and quantization.

First time job