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In mathematics, the direct method in the calculus of variations is a general method for constructing a proof of the existence of a minimizer for a given functional, [1] introduced by Stanisław Zaremba and David Hilbert around 1900. The method relies on methods of functional analysis and topology. As well as being used to prove the existence of ...
Calculus of variations is concerned with variations of functionals, which are small changes in the functional's value due to small changes in the function that is its argument. The first variation [l] is defined as the linear part of the change in the functional, and the second variation [m] is defined as the quadratic part. [22]
This is also the case for non-linear plots, such as that of against , often wrongly called a "Michaelis-Menten plot", and that of against used by Michaelis and Menten. [6] In contrast to all of these, the direct linear plot is a plot in parameter space , with observations represented by lines rather than as points.
It is also called the constant of variation or constant of proportionality. Given such a constant k , the proportionality relation ∝ with proportionality constant k between two sets A and B is the equivalence relation defined by { ( a , b ) ∈ A × B : a = k b } . {\displaystyle \{(a,b)\in A\times B:a=kb\}.}
Direct linear transformation (DLT) is an algorithm which solves a set of variables from a set of similarity relations: for =, …,. where and are known vectors, denotes equality up to an unknown scalar multiplication, and is a matrix (or linear transformation) which contains the unknowns to be solved.
For example, the problem of determining the shape of a hanging chain suspended at both ends—a catenary—can be solved using variational calculus, and in this case, the variational principle is the following: The solution is a function that minimizes the gravitational potential energy of the chain.
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In multivariable calculus, the directional derivative measures the rate at which a function changes in a particular direction at a given point. [citation needed]The directional derivative of a multivariable differentiable (scalar) function along a given vector v at a given point x intuitively represents the instantaneous rate of change of the function, moving through x with a direction ...