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In probability theory, a nonlinear expectation is a nonlinear generalization of the expectation. Nonlinear expectations are useful in utility theory as...

the expected value (also called expectation, expectancy, expectation operator, mathematical expectation, mean, expectation value, or first moment) is a generalization...

relatively strong nonlinear optical properties due to delocalized electrons at π − π {\displaystyle \pi -\pi } * orbitals. This expectation explains extensive...

In probability theory, the g-expectation is a nonlinear expectation based on a backwards stochastic differential equation (BSDE) originally developed by...

related methods in their formulation of cumulative prospect theory. Nonlinear expectation Superadditivity Subadditivity Choquet, G. (1953). "Theory of capacities"...

tiny nonlinearity can be interpreted in terms of virtual pair production A characteristic electric field strength for which the nonlinearities become...

that there are very many different types of nonlinear systems. Historically, system identification for nonlinear systems has developed by focusing on specific...

approximation of the expectation-maximization algorithm gives an alternative approach for doing maximum-likelihood estimation. Nonlinear mixed-effects models...

finance. A type of nonlinear expectation, called the g-expectation, was also derived from the theory of BSDEs. General theories of nonlinear expectations were...

Nonlinear narrative is a storytelling technique in which the events are depicted, for example, out of chronological order, or in other ways where the...

Van der Waerden notation for the notation. In quantum field theory, the nonlinear Dirac equation is a model of self-interacting Dirac fermions. This model...

be linear or nonlinear functionals of the density matrix. If linear, then they can also be viewed as observables for which the expectation value of the...

data. IFT extends such known filter formula to situations with nonlinear physics, nonlinear devices, non-Gaussian field or noise statistics, dependence of...

and in particular to the DCT-II which is simply known as the "DCT". Nonlinear dimensionality reduction techniques tend to be more computationally demanding...

Reynolds decomposition is a mathematical technique used to separate the expectation value of a quantity from its fluctuations. For example, for a quantity...

work is negative, and those contribute enormously to the expectation, giving us an expectation that is exactly one. A question has been raised about who...

regression), this allows the researcher to estimate the conditional expectation (or population average value) of the dependent variable when the independent...

implemented in a computer with finite memory. A finite dimensional approximated nonlinear filter may be more based on heuristics, such as the extended Kalman filter...

artificial neural network, consisting of fully connected neurons with a nonlinear activation function, organized in at least three layers, notable for being...

smooth map and the noise are all learned from the training data using the expectation–maximization (EM) algorithm. GTM was introduced in 1996 in a paper by...