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Two cases arise: The first case is theoretical: when you know all the coefficients then you take certain limits and find the precise radius of convergence.; The second case is practical: when you construct a power series solution of a difficult problem you typically will only know a finite number of terms in a power series, anywhere from a couple of terms to a hundred terms.
The convergence criteria of the power series then apply, requiring ‖ ‖ to be sufficiently small under the appropriate matrix norm. For more general problems, which cannot be rewritten in such a way that the two matrices commute, the ordering of matrix products produced by repeated application of the Leibniz rule must be tracked.
Consider the formal power series in one complex variable z of the form = = where ,.. Then the radius of convergence of f at the point a is given by = (| | /) where lim sup denotes the limit superior, the limit as n approaches infinity of the supremum of the sequence values after the nth position.
For instance it is not true that if two power series = and = have the same radius of convergence, then = (+) also has this radius of convergence: if = and = + (), for instance, then both series have the same radius of convergence of 1, but the series = (+) = = has a radius of convergence of 3.
Note that sometimes a series like this is called a power series "around p", because the radius of convergence is the radius R of the largest interval or disc centred at p such that the series will converge for all points z strictly in the interior (convergence on the boundary of the interval or disc generally has to be checked separately).
The utility of Abel's theorem is that it allows us to find the limit of a power series as its argument (that is, ) approaches from below, even in cases where the radius of convergence, , of the power series is equal to and we cannot be sure whether the limit should be finite or not.
is a formal power series with rational coefficients a n, which has a non-zero radius of convergence in the complex plane, and within it represents an analytic function that is in fact an algebraic function. Then Eisenstein's theorem states that there exists a non-zero integer A, such that A n a n are all integers.
In mathematics, power iteration (also known as the power method) is an eigenvalue algorithm: given a diagonalizable matrix, the algorithm will produce a number , which is the greatest (in absolute value) eigenvalue of , and a nonzero vector , which is a corresponding eigenvector of , that is, =.