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recursive estimate

См. также в других словарях:

  • Recursive least squares filter — Recursive least squares (RLS) algorithm is used in adaptive filters to find the filter coefficients that relate to recursively producing the least squares (minimum of the sum of the absolute squared) of the error signal (difference between the… …   Wikipedia

  • Recursive Bayesian estimation — is a general probabilistic approach for estimating an unknown probability density function recursively over time using incoming measurements and a mathematical process model. Model The true state x is assumed to be an unobserved Markov process,… …   Wikipedia

  • Monte Carlo integration — An illustration of Monte Carlo integration. In this example, the domain D is the inner circle and the domain E is the square. Because the square s area can be easily calculated, the area of the circle can be estimated by the ratio (0.8) of the… …   Wikipedia

  • Kalman filter — Roles of the variables in the Kalman filter. (Larger image here) In statistics, the Kalman filter is a mathematical method named after Rudolf E. Kálmán. Its purpose is to use measurements observed over time, containing noise (random variations)… …   Wikipedia

  • Multivariate adaptive regression splines — (MARS) is a form of regression analysis introduced by Jerome Friedman in 1991.[1] It is a non parametric regression technique and can be seen as an extension of linear models that automatically models non linearities and interactions. The term… …   Wikipedia

  • Algorithm — Flow chart of an algorithm (Euclid s algorithm) for calculating the greatest common divisor (g.c.d.) of two numbers a and b in locations named A and B. The algorithm proceeds by successive subtractions in two loops: IF the test B ≤ A yields yes… …   Wikipedia

  • Reverse mathematics — is a program in mathematical logic that seeks to determine which axioms are required to prove theorems of mathematics. The method can briefly be described as going backwards from the theorems to the axioms. This contrasts with the ordinary… …   Wikipedia

  • Particle filter — Particle filters, also known as sequential Monte Carlo methods (SMC), are sophisticated model estimation techniques based on simulation. They are usually used to estimate Bayesian models and are the sequential ( on line ) analogue of Markov chain …   Wikipedia

  • Adaptive Simpson's method — Adaptive Simpson s method, also called adaptive Simpson s rule, is a method of numerical integration proposed by William M. McKeeman in 1962.William M. McKeeman: Algorithm 145: Adaptive numerical integration by Simpson s rule. Commun. ACM 5(12):… …   Wikipedia

  • Importance sampling — In statistics, importance sampling is a general technique for estimating the properties of a particular distribution, while only having samples generated from a different distribution rather than the distribution of interest. Depending on the… …   Wikipedia

  • Constraint algorithm — In mechanics, a constraint algorithm is a method for satisfying constraints for bodies that obey Newton s equations of motion. There are three basic approaches to satisfying such constraints: choosing novel unconstrained coordinates ( internal… …   Wikipedia

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