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Furthermore, a global maximum (or minimum) either must be a local maximum (or minimum) in the interior of the domain, or 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 ...
A snippet of C code which prints "Hello, World!". The syntax of the C programming language is the set of rules governing writing of software in C. It is designed to allow for programs that are extremely terse, have a close relationship with the resulting object code, and yet provide relatively high-level data abstraction.
FLT_MAX_EXP, DBL_MAX_EXP, LDBL_MAX_EXP – maximum positive integer such that FLT_RADIX raised to a power one less than that number is a normalized float, double, long double, respectively FLT_MAX_10_EXP , DBL_MAX_10_EXP , LDBL_MAX_10_EXP – maximum positive integer such that 10 raised to that power is a normalized float, double, long double ...
There are four possibilities, the first two cases where c is an extremum, the second two where c is a (local) saddle point: If n is odd and (+) <, then c is a local maximum. If n is odd and (+) >, then c is a local minimum.
Is there an efficient way to find the global maximum/minimum? Take for example the sine integral. It has an infinite number of local maxima and minima. So how can one decide which one is the global maximum/minimum? --Abdull 17:04, 17 May 2007 (UTC) Not in the absolutely general case.
The maximum of a subset of a preordered set is an element of which is greater than or equal to any other element of , and the minimum of is again defined dually. In the particular case of a partially ordered set , while there can be at most one maximum and at most one minimum there may be multiple maximal or minimal elements.
Given a function f with domain D and a preordered set (K, ≤) as codomain, an element y of K is an upper bound of f if y ≥ f (x) for each x in D. The upper bound is called sharp if equality holds for at least one value of x. It indicates that the constraint is optimal, and thus cannot be further reduced without invalidating the inequality.
If D(a, b) = 0 then the point (a, b) could be any of a minimum, maximum, or saddle point (that is, the test is inconclusive). Sometimes other equivalent versions of the test are used. In cases 1 and 2, the requirement that f xx f yy − f xy 2 is positive at ( x , y ) implies that f xx and f yy have the same sign there.