Steepest — Steep Steep, a. [Compar. {Steeper} ( [ e]r); superl. {Steepest}.] [OE. steep, step, AS. ste[ a]p; akin to Icel. steyp[eth]r steep, and st[=u]pa to stoop, Sw. stupa to fall, to tilt; cf. OFries. stap high. Cf. {Stoop}, v. i., {Steep}, v. t.,… … The Collaborative International Dictionary of English
steepest descent — greičiausiasis nusileidimas statusas T sritis automatika atitikmenys: angl. steepest descent vok. steilster Abfall, m; steilster Anstieg, m rus. наискорейший спуск, m pranc. lieu de plus grande pente, m … Automatikos terminų žodynas
steepest — adjective Being steep to the greatest degree … Wiktionary
steepest — stɪËp v. soak in a liquid, immerse in liquid; saturate, imbue adj. having a sharp slope, precipitous; expensive, exorbitant; extreme … English contemporary dictionary
Method of steepest descent — For the optimization algorithm, see Gradient descent. In mathematics, the method of steepest descent or stationary phase method or saddle point method is an extension of Laplace s method for approximating an integral, where one deforms a contour… … Wikipedia
traction limited grade — Steepest negotiable grade where traction is the limiting factor … Dictionary of automotive terms
Non-linear least squares — is the form of least squares analysis which is used to fit a set of m observations with a model that is non linear in n unknown parameters (m > n). It is used in some forms of non linear regression. The basis of the method is to… … Wikipedia
Takabisha — Données clés Localisation Fuji Q Highland, Japon Ouverture 16 juillet 2011 Constructeur … Wikipédia en Français
Funicular — For the mathematical and architectural curve known as funicular, see catenary. Funicular in Valparaíso, Chile A funicular, also known as an inclined plane or cliff railway, is a cable railway in which a cable attached to a pair of tram like… … Wikipedia
Nonlinear conjugate gradient method — In numerical optimization, the nonlinear conjugate gradient method generalizes the conjugate gradient method to nonlinear optimization. For a quadratic function : The minimum of f is obtained when the gradient is 0: . Whereas linear conjugate… … Wikipedia
Conjugate gradient method — A comparison of the convergence of gradient descent with optimal step size (in green) and conjugate vector (in red) for minimizing a quadratic function associated with a given linear system. Conjugate gradient, assuming exact arithmetic,… … Wikipedia
