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nonlinear estimation

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  • Estimation theory — is a branch of statistics and signal processing that deals with estimating the values of parameters based on measured/empirical data. The parameters describe an underlying physical setting in such a way that the value of the parameters affects… …   Wikipedia

  • Nonlinear filter — A nonlinear filter is a signal processing device whose output is not a linear function of its input. Terminology concerning the filtering problem may refer to the time domain (state space) showing of the signal or to the frequency domain… …   Wikipedia

  • Nonlinear regression — See Michaelis Menten kinetics for details In statistics, nonlinear regression is a form of regression analysis in which observational data are modeled by a function which is a nonlinear combination of the model parameters and depends on one or… …   Wikipedia

  • Nonlinear programming — In mathematics, nonlinear programming (NLP) is the process of solving a system of equalities and inequalities, collectively termed constraints, over a set of unknown real variables, along with an objective function to be maximized or minimized,… …   Wikipedia

  • Maximum likelihood sequence estimation — (MLSE) is a mathematical algorithm to extract useful data out of a noisy data stream. Contents 1 Theory 2 Background 3 References 4 Further reading …   Wikipedia

  • Minimum distance estimation — (MDE) is a statistical method for fitting a mathematical model to data, usually the empirical distribution. Contents 1 Definition 2 Statistics used in estimation 2.1 Chi square criterion …   Wikipedia

  • Maximum spacing estimation — The maximum spacing method tries to find a distribution function such that the spacings, D(i), are all approximately of the same length. This is done by maximizing their geometric mean. In statistics, maximum spacing estimation (MSE or MSP), or… …   Wikipedia

  • List of digital estimation techniques — *Linear models **Parameter Estimation ***Deterministic parameters ****Least squares (batch and recursive processing) ****Best linear unbiased estimation (BLUE) ****Maximum likelihood ***Random parameters ****Mean squared ****Maximum a posteriori… …   Wikipedia

  • Maximum a posteriori estimation — In Bayesian statistics, a maximum a posteriori probability (MAP) estimate is a mode of the posterior distribution. The MAP can be used to obtain a point estimate of an unobserved quantity on the basis of empirical data. It is closely related to… …   Wikipedia

  • Unbiased estimation of standard deviation — In statistics, the standard deviation is often estimated from a random sample drawn from the population. The most common measure used is the sample standard deviation , which is defined by:s = sqrt{frac{1}{n 1} sum {i=1}^n (x i… …   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

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