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In mathematics, maxima and minima, also known as extrema, are points in the domain of a function at which the function takes the largest (maximum), or smallest (minimum) value either within a given neighbourhood (local extrema), or on the function domain in its entirety (global extrema).
Definitions A point x A local minimum is a point x A global (or absolute) maximum is a point x The concepts of maxima and minima are not restricted to functions whose domain is the real numbers. One can talk about global maxima and global minima for real-valued functions whose domain is any set. In order to be able to define local maxima and local minima, the function needs to take real values, and the concept of neighborhood must be defined on the domain of the function. A neighborhood then plays the role of the set of x such that |x - x One refers to a local maximum/minimum as to a local extremum (or local optimum), and to a global maximum/minimum as to a global extremum (or global optimum). Finding maxima and minima Finding global maxima and minima is the goal of optimization. If the function is defined over a closed domain, then by the extreme value theorem global maxima and minima exist. Furthermore, a global maximum (or minimum) must be either a local maximum (or minimum) in the interior of the domain, or it must lie on the boundary of the domain. So a method of finding a global maximum (or minimum) is to look at all the local maxima (or minima) in the interior, and also look at the maxima (or minima) of the points on the boundary; and take the biggest (or smallest) one. For twice-differentiable functions in one variable, a simple technique for finding local maxima and minima is to look for stationary points, which are points where the first derivative is zero. If the second derivative at a stationary point is positive, the point is a local minimum; if it is negative, the point is a local maximum; if it is zero, further investigation is required. Examples Functions of more variables For functions of more variables similar concepts apply, but there is also the saddle point. See also | ||||||||
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