nonlinear estimation

  • 1Estimation 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… …

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  • 2Nonlinear 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… …

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  • 3Nonlinear 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… …

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  • 4Nonlinear 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,… …

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  • 5Maximum 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 …

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  • 6Minimum 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 …

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  • 7Maximum 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… …

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  • 8List 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… …

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  • 9Maximum 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… …

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  • 10Unbiased 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… …

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