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Data compression. In information theory, data compression, source coding, [1] or bit-rate reduction is the process of encoding information using fewer bits than the original representation. [2] Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy.
In information technology, lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data discarding to represent the content. These techniques are used to reduce data size for storing, handling, and transmitting content. Higher degrees of approximation create coarser ...
By operation of the pigeonhole principle, no lossless compression algorithm can shrink the size of all possible data: Some data will get longer by at least one symbol or bit. Compression algorithms are usually effective for human- and machine-readable documents and cannot shrink the size of random data that contain no redundancy. Different ...
File size. File size is a measure of how much data a computer file contains or, alternately, how much storage it consumes. Typically, file size is expressed in units of measurement based on the byte. By convention, file size units use either a metric prefix (as in megabyte and gigabyte) or a binary prefix (as in mebibyte and gibibyte).
Definition. Data compression ratio is defined as the ratio between the uncompressed size and compressed size: [1][2][3][4][5] Thus, a representation that compresses a file's storage size from 10 MB to 2 MB has a compression ratio of 10/2 = 5, often notated as an explicit ratio, 5:1 (read "five" to "one"), or as an implicit ratio, 5/1.
With simple keyboard shortcuts, you can zoom in or out to make text larger or smaller. In an instant, these commands improve the readability of the content you're viewing. • Zoom in - Press Ctrl (CMD on a Mac) + the plus key (+) on your keyboard. • Zoom out - Press Ctrl (CMD on a Mac) + the minus key (-) on your keyboard.
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