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  2. Chebychev–Grübler–Kutzbach criterion - Wikipedia

    en.wikipedia.org/wiki/Chebychev–Grübler...

    The Kutzbach criterion is also called the mobility formula, because it computes the number of parameters that define the configuration of a linkage from the number of links and joints and the degree of freedom at each joint.

  3. Routh–Hurwitz stability criterion - Wikipedia

    en.wikipedia.org/wiki/Routh–Hurwitz_stability...

    In the control system theory, the Routh–Hurwitz stability criterion is a mathematical test that is a necessary and sufficient condition for the stability of a linear time-invariant (LTI) dynamical system or control system. A stable system is one whose output signal is bounded; the position, velocity or energy do not increase to infinity as ...

  4. Characteristic function (probability theory) - Wikipedia

    en.wikipedia.org/wiki/Characteristic_function...

    The formula in the definition of characteristic function allows us to compute φ when we know the distribution function F (or density f). If, on the other hand, we know the characteristic function φ and want to find the corresponding distribution function, then one of the following inversion theorems can be used. Theorem.

  5. Kharitonov's theorem - Wikipedia

    en.wikipedia.org/wiki/Kharitonov's_theorem

    Kharitonov's theorem is a result used in control theory to assess the stability of a dynamical system when the physical parameters of the system are not known precisely. When the coefficients of the characteristic polynomial are known, the Routh–Hurwitz stability criterion can be used to check if the system is stable (i.e. if all roots have negative real parts).

  6. Bayesian information criterion - Wikipedia

    en.wikipedia.org/wiki/Bayesian_information_criterion

    In statistics, the Bayesian information criterion (BIC) or Schwarz information criterion (also SIC, SBC, SBIC) is a criterion for model selection among a finite set of models; models with lower BIC are generally preferred. It is based, in part, on the likelihood function and it is closely related to the Akaike information criterion (AIC).

  7. Kullback–Leibler divergence - Wikipedia

    en.wikipedia.org/wiki/Kullback–Leibler_divergence

    In mathematical statistics, the Kullback–Leibler (KL) divergence (also called relative entropy and I-divergence [1]), denoted (), is a type of statistical distance: a measure of how much a model probability distribution Q is different from a true probability distribution P.

  8. K-stability - Wikipedia

    en.wikipedia.org/wiki/K-stability

    According to the analogy with the Hilbert-Mumford criterion, once one has a notion of deformation (test configuration) and weight on the central fibre (Donaldson-Futaki invariant), one can define a stability condition, called K-stability. Let (,) be a polarised algebraic variety. We say that (,) is:

  9. Kinematics - Wikipedia

    en.wikipedia.org/wiki/Kinematics

    The formula for the acceleration A P can now be obtained as: = ˙ + + (), or = / + / +, where α is the angular acceleration vector obtained from the derivative of the angular velocity vector; / =, is the relative position vector (the position of P relative to the origin O of the moving frame M); and = ¨ is the acceleration of the origin of ...