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In mathematics, Fermat's theorem (also known as interior extremum theorem) is a method to find local maxima and minima of differentiable functions on open sets by showing that every local extremum of the function is a stationary point (the function's derivative is zero at that point). Fermat's theorem is a theorem in real analysis, named after ...
Lagrange multiplier. In mathematical optimization, the method of Lagrange multipliers is a strategy for finding the local maxima and minima of a function subject to equation constraints (i.e., subject to the condition that one or more equations have to be satisfied exactly by the chosen values of the variables). [1]
Maximum and minimum. Local and global maxima and minima for cos (3π x)/ x, 0.1≤ x ≤1.1. In mathematical analysis, the maximum and minimum[a] of a function are, respectively, the largest and smallest value taken by the function. Known generically as extremum, [b] they may be defined either within a given range (the local or relative extrema ...
This is analogous to Fermat's theorem in calculus, stating that at any point where a differentiable function attains a local extremum its derivative is zero. In Lagrangian mechanics , according to Hamilton's principle of stationary action, the evolution of a physical system is described by the solutions to the Euler equation for the action of ...
Derivative test. In calculus, a derivative test uses the derivatives of a function to locate the critical points of a function and determine whether each point is a local maximum, a local minimum, or a saddle point. Derivative tests can also give information about the concavity of a function. The usefulness of derivatives to find extrema is ...
In mathematics, particularly in calculus, a stationary point of a differentiable function of one variable is a point on the graph of the function where the function's derivative is zero. [1][2][3] Informally, it is a point where the function "stops" increasing or decreasing (hence the name). For a differentiable function of several real ...
Finding the extrema of functionals is similar to finding the maxima and minima of functions. The maxima and minima of a function may be located by finding the points where its derivative vanishes (i.e., is equal to zero). The extrema of functionals may be obtained by finding functions for which the functional derivative is equal to zero.
Second partial derivative test. The Hessian approximates the function at a critical point with a second-degree polynomial. In mathematics, the second partial derivative test is a method in multivariable calculus used to determine if a critical point of a function is a local minimum, maximum or saddle point.