|
Adaptive Coding
Adaptive coding refers to variants of entropy encoding methods of lossless data compression. They are particularly suited to streaming data, as they adapt to localized changes in the characteristics of the data, and don't require a first pass over the data to calculate a probability model. The cost paid for these advantages is that the encoder and decoder must be more complex to keep their states synchronized, and more computational power is needed to keep adapting the encoder/decoder state. Almost all data compression methods involve the use of a ''model'', a prediction of the composition of the data. When the data matches the prediction made by the model, the encoder can usually transmit the content of the data at a lower information cost, by making reference to the model. This general statement is a bit misleading as general data compression algorithms would include the popular LZW and LZ77 algorithms, which are hardly comparable to compression techniques typically called ''a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Entropy Encoding
In information theory, an entropy coding (or entropy encoding) is any lossless data compression method that attempts to approach the lower bound declared by Shannon's source coding theorem, which states that any lossless data compression method must have an expected code length greater than or equal to the entropy of the source. More precisely, the source coding theorem states that for any source distribution, the expected code length satisfies \operatorname E_ ell(d(x))\geq \operatorname E_ \log_b(P(x))/math>, where \ell is the function specifying the number of symbols in a code word, d is the coding function, b is the number of symbols used to make output codes and P is the probability of the source symbol. An entropy coding attempts to approach this lower bound. Two of the most common entropy coding techniques are Huffman coding and arithmetic coding. If the approximate entropy characteristics of a data stream are known in advance (especially for signal compression), a simple ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lossless Data Compression
Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information. Lossless compression is possible because most real-world data exhibits Redundancy (information theory), statistical redundancy. By contrast, lossy compression permits reconstruction only of an approximation of the original data, though usually with greatly improved Bit rate#Bitrates in multimedia, compression rates (and therefore reduced media sizes). 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 (information theory), redundancy. Different algorithms exist that are designed either with a specific type of input data in mind or with speci ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Streaming Data
Streaming data is data that is continuously generated by different sources. Such data should be processed incrementally using stream processing techniques without having access to all of the data. In addition, it should be considered that concept drift may happen in the data which means that the properties of the stream may change over time. It is usually used in the context of big data in which it is generated by many different sources at high speed. Data streaming can also be explained as a technology used to deliver content to devices over the internet, and it allows users to access the content immediately, rather than having to wait for it to be downloaded. Big data is forcing many organizations to focus on storage costs, which brings interest to data lakes and data streams. A data lake refers to the storage of a large amount of unstructured and semi data, and is useful due to the increase of big data as it can be stored in such a way that firms can dive into the data lake a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Compression
In information theory, data compression, source coding, or bit-rate reduction is the process of encoding information using fewer bits than the original representation. Any particular compression is either lossy or lossless. Lossless compression reduces bits by identifying and eliminating statistical redundancy. No information is lost in lossless compression. Lossy compression reduces bits by removing unnecessary or less important information. Typically, a device that performs data compression is referred to as an encoder, and one that performs the reversal of the process (decompression) as a decoder. The process of reducing the size of a data file is often referred to as data compression. In the context of data transmission, it is called source coding: encoding is done at the source of the data before it is stored or transmitted. Source coding should not be confused with channel coding, for error detection and correction or line coding, the means for mapping data onto a sig ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
LZ77
LZ77 and LZ78 are the two lossless data compression algorithms published in papers by Abraham Lempel and Jacob Ziv in 1977 and 1978. They are also known as Lempel-Ziv 1 (LZ1) and Lempel-Ziv 2 (LZ2) respectively. These two algorithms form the basis for many variations including Lempel–Ziv–Welch, LZW, Lempel–Ziv–Storer–Szymanski, LZSS, Lempel–Ziv–Markov chain algorithm, LZMA and others. Besides their academic influence, these algorithms formed the basis of several ubiquitous compression schemes, including GIF and the DEFLATE algorithm used in Portable Network Graphics, PNG and Zip (file format), ZIP. They are both theoretically dictionary coders. LZ77 maintains a sliding window during compression. This was later shown to be equivalent to the ''explicit dictionary'' constructed by LZ78—however, they are only equivalent when the entire data is intended to be decompressed. Since LZ77 encodes and decodes from a sliding window over previously seen characters, decompressio ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Run-length Encoding
Run-length encoding (RLE) is a form of lossless data compression in which ''runs'' of data (consecutive occurrences of the same data value) are stored as a single occurrence of that data value and a count of its consecutive occurrences, rather than as the original run. As an imaginary example of the concept, when encoding an image built up from colored dots, the sequence "green green green green green green green green green" is shortened to "green x 9". This is most efficient on data that contains many such runs, for example, simple graphic images such as icons, line drawings, games, and animations. For files that do not have many runs, encoding them with RLE could increase the file size. RLE may also refer in particular to an early graphics file format supported by CompuServe for compressing black and white images, that was widely supplanted by their later Graphics Interchange Format (GIF). RLE also refers to a little-used image format in Windows 3.x that is saved with the fil ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
JPEG
JPEG ( , short for Joint Photographic Experts Group and sometimes retroactively referred to as JPEG 1) is a commonly used method of lossy compression for digital images, particularly for those images produced by digital photography. The degree of compression can be adjusted, allowing a selectable trade off between storage size and image quality. JPEG typically achieves 10:1 compression with noticeable, but widely agreed to be acceptable perceptible loss in image quality. Since its introduction in 1992, JPEG has been the most widely used image compression standard in the world, and the most widely used digital image format, with several billion JPEG images produced every day as of 2015. The Joint Photographic Experts Group created the standard in 1992, based on the discrete cosine transform (DCT) algorithm. JPEG was largely responsible for the proliferation of digital images and digital photos across the Internet and later social media. JPEG compression is used in a number of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Saturn
Saturn is the sixth planet from the Sun and the second largest in the Solar System, after Jupiter. It is a gas giant, with an average radius of about 9 times that of Earth. It has an eighth the average density of Earth, but is over 95 times more massive. Even though Saturn is almost as big as Jupiter, Saturn has less than a third its mass. Saturn orbits the Sun at a distance of , with an orbital period of 29.45 years. Saturn's interior is thought to be composed of a rocky core, surrounded by a deep layer of metallic hydrogen, an intermediate layer of liquid hydrogen and liquid helium, and an outer layer of gas. Saturn has a pale yellow hue, due to ammonia crystals in its upper atmosphere. An electrical current in the metallic hydrogen layer is thought to give rise to Saturn's planetary magnetic field, which is weaker than Earth's, but has a magnetic moment 580 times that of Earth because of Saturn's greater size. Saturn's magnetic field strength is about a twen ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Solid-state Drive
A solid-state drive (SSD) is a type of solid-state storage device that uses integrated circuits to store data persistently. It is sometimes called semiconductor storage device, solid-state device, or solid-state disk. SSDs rely on non-volatile memory, typically NAND flash, to store data in memory cells. The performance and endurance of SSDs vary depending on the number of bits stored per cell, ranging from high-performing single-level cells (SLC) to more affordable but slower quad-level cells (QLC). In addition to flash-based SSDs, other technologies such as 3D XPoint offer faster speeds and higher endurance through different data storage mechanisms. Unlike traditional hard disk drives (HDDs), SSDs have no moving parts, allowing them to deliver faster data access speeds, reduced latency, increased resistance to physical shock, lower power consumption, and silent operation. Often interfaced to a system in the same way as HDDs, SSDs are used in a variety of devices, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Damaged N00153918
Damage is any change in a thing, often a physical object, that degrades it away from its initial state. It can broadly be defined as "changes introduced into a system that adversely affect its current or future performance".Farrar, C.R., Sohn, H., Park, G.,Converting Large Sensor Array Data into Structural Health Information, in Andrew Smyth, Raimondo Betti, ''The 4th International Workshop on Structural Control'' (2005), p. 67. Damage "does not necessarily imply total loss of system functionality, but rather that the system is no longer operating in its optimal manner". Damage to physical objects is "the progressive physical process by which they break",Jean Lemaitre, ''A Course on Damage Mechanics'' (2013). and includes mechanical stress that weakens a structure, even if this is not visible. Physical damage All physical damage begins on the atomic level, with the shifting or breaking of atomic bonds, and the rate at which damage to any physical thing occurs is therefore lar ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lossless Compression Algorithms
Lossless compression is a class of data compression that allows the original data to be perfectly reconstructed from the compressed data with no loss of information. Lossless compression is possible because most real-world data exhibits statistical redundancy. By contrast, lossy compression permits reconstruction only of an approximation of the original data, though usually with greatly improved compression rates (and therefore reduced media sizes). 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 algorithms exist that are designed either with a specific type of input data in mind or with specific assumptions about what kinds of redundancy the uncompressed data are likely to contain. Lo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
