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Adaptive Algorithm
An adaptive algorithm is an algorithm that changes its behavior at the time it is run, based on information available and on ''a priori'' defined reward mechanism (or criterion). Such information could be the story of recently received data, information on the available computational resources, or other run-time acquired (or ''a priori'' known) information related to the environment in which it operates. Among the most used adaptive algorithms is the Widrow-Hoff’s least mean squares (LMS), which represents a class of stochastic gradient-descent algorithms used in adaptive filtering and machine learning. In adaptive filtering the LMS is used to mimic a desired filter by finding the filter coefficients that relate to producing the least mean square of the error signal (difference between the desired and the actual signal). For example, stable partition, using no additional memory is ''O''(''n'' lg ''n'') but given ''O''(''n'') memory, it can be ''O''(''n'') in time. As implemente ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Algorithm
In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing calculations and data processing. More advanced algorithms can perform automated deductions (referred to as automated reasoning) and use mathematical and logical tests to divert the code execution through various routes (referred to as automated decision-making). Using human characteristics as descriptors of machines in metaphorical ways was already practiced by Alan Turing with terms such as "memory", "search" and "stimulus". In contrast, a heuristic is an approach to problem solving that may not be fully specified or may not guarantee correct or optimal results, especially in problem domains where there is no well-defined correct or optimal result. As an effective method, an algorithm can be expressed within a finite amount of space ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
AdaBoost
AdaBoost, short for ''Adaptive Boosting'', is a statistical classification meta-algorithm formulated by Yoav Freund and Robert Schapire in 1995, who won the 2003 Gödel Prize for their work. It can be used in conjunction with many other types of learning algorithms to improve performance. The output of the other learning algorithms ('weak learners') is combined into a weighted sum that represents the final output of the boosted classifier. Usually, AdaBoost is presented for binary classification, although it can be generalized to multiple classes or bounded intervals on the real line. AdaBoost is adaptive in the sense that subsequent weak learners are tweaked in favor of those instances misclassified by previous classifiers. In some problems it can be less susceptible to the overfitting problem than other learning algorithms. The individual learners can be weak, but as long as the performance of each one is slightly better than random guessing, the final model can be proven to c ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Adaptive Grammar
An adaptive grammar is a formal grammar that explicitly provides mechanisms within the formalism to allow its own production rules to be manipulated. Overview John N. Shutt defines adaptive grammar as a grammatical formalism that allows rule sets (aka sets of production rules) to be explicitly manipulated within a grammar. Types of manipulation include rule addition, deletion, and modification. Early history The first description of grammar adaptivity (though not under that name) in the literature is generallyChristiansen, Henning, "Survey of Adaptable Grammars" ''ACM SIGPLAN Notices'', Vol. 25 No. 11, pp. 35-44, Nov. 1990.Shutt, John N., Recursive Adaptable Grammars', Master’s Thesis, Worcester Polytechnic Institute, 1993. (16 December 2003 emended revision.)Jackson, Quinn Tyler, Adapting to Babel: Adaptivity and Context-Sensitivity in Parsing', Ibis Publications, Plymouth, Massachusetts, March 2006. taken to be in a paper by Alfonso Caracciolo di Forino published in 1963.Cara ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Adaptive Filter
An adaptive filter is a system with a linear filter that has a transfer function controlled by variable parameters and a means to adjust those parameters according to an optimization algorithm. Because of the complexity of the optimization algorithms, almost all adaptive filters are digital filters. Adaptive filters are required for some applications because some parameters of the desired processing operation (for instance, the locations of reflective surfaces in a reverberant space) are not known in advance or are changing. The closed loop adaptive filter uses feedback in the form of an error signal to refine its transfer function. Generally speaking, the closed loop adaptive process involves the use of a cost function, which is a criterion for optimum performance of the filter, to feed an algorithm, which determines how to modify filter transfer function to minimize the cost on the next iteration. The most common cost function is the mean square of the error signal. As the po ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Adaptation (computer Science)
The term “adaptation” in computer science refers to a process where an interactive system (adaptive system) adapts its behaviour to individual users based on information acquired about its user(s) and its environment. Adaptation is one of the three pillars of empiricism in Scrum. The need for adaptation A software system passes through a potentially long software engineering cycle and before delivery, requirement engineers, designers and software developers realize the components of the system. However, it is impossible to anticipate the requirements of all users, and a single best or optimal system configuration is impossible. The active involvement of users and clear understanding of user and task requirements is a challenge in the development of computer-based interactive systems for two reasons: * The potential user groups may not be known at the start of the project, and would need to be identified according to future scenarios of how the software system will be use ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
MiniDisc
MiniDisc (MD) is an erasable magneto-optical disc-based data storage format offering a capacity of 60, 74, and later, 80 minutes of digitized audio. Sony announced the MiniDisc in September 1992 and released it in November of that year for sale in Japan and in December in Europe, North America, and other countries. The music format was based on ATRAC audio data compression, Sony's own proprietary compression code. Its successor, Hi-MD, would later introduce the option of linear PCM digital recording to meet audio quality comparable to that of a compact disc. MiniDiscs were very popular in Japan and found moderate success in Europe; although it was designed to be the successor of the cassette tape, it did not manage to mass replace it globally. By March 2011 Sony had sold 22 million MD players. Sony has ceased development of MD devices, with the last of the players sold by March 2013. Market history In 1983, just a year after the introduction of the Compact Disc, Kees ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Adaptive Transform Acoustic Coding
Adaptive Transform Acoustic Coding (ATRAC) is a family of proprietary audio compression algorithms developed by Sony. MiniDisc was the first commercial product to incorporate ATRAC in 1992. ATRAC allowed a relatively small disc like MiniDisc to have the same running time as CD while storing audio information with minimal loss in perceptible quality. Improvements to the codec in the form of ATRAC3, ATRAC3plus, and ATRAC Advanced Lossless followed in 1999, 2002, and 2006 respectively. Files in ATRAC3 format originally have the extension, however in most cases the files would be stored in an OpenMG Audio container using the extension . Initially files that were encrypted with OpenMG had the extension, before it was replaced by starting in SonicStage v2.1. Encryption is no longer compulsory as of v3.2. Other MiniDisc manufacturers such as Sharp and Panasonic also implemented their own versions of the ATRAC codec. History ATRAC was developed for Sony's MiniDisc format. ATRAC ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Signal Processing
Signal processing is an electrical engineering subfield that focuses on analyzing, modifying and synthesizing ''signals'', such as sound, images, and scientific measurements. Signal processing techniques are used to optimize transmissions, digital storage efficiency, correcting distorted signals, subjective video quality and to also detect or pinpoint components of interest in a measured signal. History According to Alan V. Oppenheim and Ronald W. Schafer, the principles of signal processing can be found in the classical numerical analysis techniques of the 17th century. They further state that the digital refinement of these techniques can be found in the digital control systems of the 1940s and 1950s. In 1948, Claude Shannon wrote the influential paper "A Mathematical Theory of Communication" which was published in the Bell System Technical Journal. The paper laid the groundwork for later development of information communication systems and the processing of signals ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Prediction By Partial Matching
Prediction by partial matching (PPM) is an adaptive statistical data compression technique based on context modeling and prediction. PPM models use a set of previous symbols in the uncompressed symbol stream to predict the next symbol in the stream. PPM algorithms can also be used to cluster data into predicted groupings in cluster analysis. Theory Predictions are usually reduced to symbol rankings. Each symbol (a letter, bit or any other amount of data) is ranked before it is compressed, and the ranking system determines the corresponding codeword (and therefore the compression rate). In many compression algorithms, the ranking is equivalent to probability mass function estimation. Given the previous letters (or given a context), each symbol is assigned with a probability. For instance, in arithmetic coding the symbols are ranked by their probabilities to appear after previous symbols, and the whole sequence is compressed into a single fraction that is computed accordin ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Adaptive Huffman Coding
Adaptive Huffman coding (also called Dynamic Huffman coding) is an adaptive coding technique based on Huffman coding In computer science and information theory, a Huffman code is a particular type of optimal prefix code that is commonly used for lossless data compression. The process of finding or using such a code proceeds by means of Huffman coding, an algo .... It permits building the code as the symbols are being transmitted, having no initial knowledge of source distribution, that allows one-pass encoding and adaptation to changing conditions in data. The benefit of one-pass procedure is that the source can be encoded in real time, though it becomes more sensitive to transmission errors, since just a single loss ruins the whole code. Algorithms There are a number of implementations of this method, the most notable are FGK ( Faller- Gallager- Knuth) and Vitter algorithm. FGK Algorithm It is an online coding technique based on Huffman coding. Having no initial knowledge ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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 ''ada ... [...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 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 signal. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
