of the SART algorithm was theoretically established in 2004 by Ming Jiang and Ge Wang in their paper " Convergence of the simultaneous algebraic reconstruction technique ( SART )" published in the IEEE Transactions on Image Processing, Vol.

SART and its proposed extensions are used in emission CT in nuclear medicine, for dynamic CT, for holographic tomography, etc.

Systems with 10 to 100 N of thrust have been investigated by SART.

The GMDSS installation on ships include one ( two on vessels over 500 GT ) Search and Rescue Locating device ( s ) called Search and Rescue Radar Transponders ( SART ) which are used to locate survival craft or distressed vessels by creating a series of twelve dots on a rescuing ship's 3 cm radar display.

In addition to equipment listed below, all GMDSS-regulated ships must carry a satellite EPIRB, a NAVTEX receiver ( if they travel in any areas served by NAVTEX ), an Inmarsat-C SafetyNET receiver ( if they travel in any areas not served by NAVTEX ), a DSC-equipped VHF radiotelephone, two ( if between 300 and less than 500 GRT ) or three VHF handhelds ( if 500 GRT or more ), and two 9 GHz search and rescue radar transponders ( SART ).

A standard SART 9 GHz Radar Transponder, produced by Jotron, on board a Norwegian ferry.

Algebraic code-excited linear prediction ( ACELP ) is a patented speech coding algorithm by VoiceAge Corporation in which a limited set of pulses is distributed as excitation to linear prediction filter.

* Reconstruction algorithm

Xiaolin Wu's line algorithm is an algorithm for line antialiasing, which was presented in the article An Efficient Antialiasing Technique in the July 1991 issue of Computer Graphics, as well as in the article Fast Antialiasing in the June 1992 issue of Dr. Dobb's Journal.

PNNI also includes a very powerful summarization mechanism to allow construction of very large networks, as well as a call admission control ( CAC ) algorithm which determines the availability of sufficient bandwidth on a proposed route through a network in order to satisfy the service requirements of a VC or VP.

The basic search procedure was proposed in two seminal papers in the early 60s ( see references below ) and is now commonly referred to as the Davis – Putnam – Logemann – Loveland algorithm (" DPLL " or " DLL ").

Bruun's algorithm ( above ) is another method that was initially proposed to take advantage of real inputs, but it has not proved popular.

The Gauss algorithm for matrix inversion is probably the oldest solution but this approach does not efficiently use the symmetry of R and r. A faster algorithm is the Levinson recursion proposed by Norman Levinson in 1947, which recursively calculates the solution.

proposed an improvement to this algorithm called the split Levinson recursion which requires about half the number of multiplications and divisions.

In the case of computer networking, the metric is computed by a routing algorithm, and can cover such information as bandwidth, network delay, hop count, path cost, load, MTU, reliability, and communication cost ( see e. g. this survey for a list of proposed routing metrics ).

Newell's algorithm, proposed in 1972, provides a method for cutting such polygons.

The algorithm was named after Nicholas Metropolis, who was an author along with Arianna W. Rosenbluth, Marshall N. Rosenbluth, Augusta H. Teller, and Edward Teller of the 1953 paper Equation of State Calculations by Fast Computing Machines which first proposed the algorithm for the specific case of the Boltzmann distribution ; and W. Keith Hastings, who extended it to the more general case in 1970.

The original SVM algorithm was invented by Vladimir N. Vapnik and the current standard incarnation ( soft margin ) was proposed by Vapnik and Corinna Cortes in 1995.

The original optimal hyperplane algorithm proposed by Vapnik in 1963 was a linear classifier.

The original retinex algorithm proposed by Land and McCann uses a localized version of this principle.

The algorithm was initially proposed by Marco Dorigo in 1992, and has since been diversified to solve a wider class of numerical problems.

The Levinson-Durbin algorithm was proposed first by Norman Levinson in 1947, improved by James Durbin in 1960, and subsequently improved to 4n < sup > 2 </ sup > and then 3n < sup > 2 </ sup > multiplications by W. F. Trench and S. Zohar, respectively.

The Viterbi algorithm was proposed by Andrew Viterbi in 1967 as a decoding algorithm for convolutional codes over noisy digital communication links.

* Metropolis – Hastings algorithm: Generates a random walk using a proposal density and a method for rejecting proposed moves.

Bruun's algorithm is a fast Fourier transform ( FFT ) algorithm based on an unusual recursive polynomial-factorization approach, proposed for powers of two by G. Bruun in 1978 and generalized to arbitrary even composite sizes by H. Murakami in 1996.

A recent work proposed a simulator ( SGNSim, Stochastic Gene Networks Simulator ), that can model GRNs where transcription and translation are modeled as multiple time delayed events and its dynamics is driven by a stochastic simulation algorithm ( SSA ) able to deal with multiple time delayed events.

The fastest known algorithm for generating the former model is proposed by Nobari et al.

* 1967-Viterbi algorithm proposed by Andrew Viterbi

* 1978-Bruun's algorithm proposed for powers of two by Georg Bruun

The algorithm proceeds by successive subtractions in two loops: IF the test B ≥ A yields " yes " ( or true ) ( more accurately the number b in location B is greater than or equal to the number a in location A ) THEN the algorithm specifies B ← B − A ( meaning the number b − a replaces the old b ).

A prototypical example of an algorithm is Euclid's algorithm to determine the maximum common divisor of two integers ; an example ( there are others ) is described by the flow chart above and as an example in a later section.

Thus, an algorithm can be considered to be any sequence of operations that can be simulated by a Turing-complete system.

Gurevich: "... Turing's informal argument in favor of his thesis justifies a stronger thesis: every algorithm can be simulated by a Turing machine ... according to Savage, an algorithm is a computational process defined by a Turing machine ".

In computer systems, an algorithm is basically an instance of logic written in software by software developers to be effective for the intended " target " computer ( s ), in order for the target machines to produce output from given input ( perhaps null ).

Algorithm versus function computable by an algorithm: For a given function multiple algorithms may exist.

important to distinguish between the notion of algorithm, i. e. procedure and the notion of function computable by algorithm, i. e. mapping yielded by procedure.

Structured programming, canonical structures: Per the Church-Turing thesis any algorithm can be computed by a model known to be Turing complete, and per Minsky's demonstrations Turing completeness requires only four instruction types — conditional GOTO, unconditional GOTO, assignment, HALT.

Therefore a naive algorithm to calculate the estimated variance is given by the following:

This algorithm can easily be adapted to compute the variance of a finite population: simply divide by n instead of n − 1 on the last line.

However, the algorithm can be improved by adopting the method of the assumed mean.

Again the estimated population variance of 30 is computed correctly by Algorithm II, but the naive algorithm now computes it as − 170. 66666666666666.

The first approach is to compute the statistical moments by separating the data into bins and then computing the moments from the geometry of the resulting histogram, which effectively becomes a one-pass algorithm for higher moments.

Even greater accuracy can be achieved by first computing the means, then using the stable one-pass algorithm on the residuals.

The algorithm described by AES is a symmetric-key algorithm, meaning the same key is used for both encrypting and decrypting the data.

In 2002, a theoretical attack, termed the " XSL attack ", was announced by Nicolas Courtois and Josef Pieprzyk, purporting to show a weakness in the AES algorithm due to its simple description .< ref >