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The word problem for an algebra is then to determine, given two expressions (words) involving the generators and operations, whether they represent the same element of the algebra modulo the identities. The word problems for groups and semigroups can be phrased as word problems for algebras. [1]
The rule states that if the nonzero terms of a single-variable polynomial with real coefficients are ordered by descending variable exponent, then the number of positive roots of the polynomial is either equal to the number of sign changes between consecutive (nonzero) coefficients, or is less than it by an even number.
That is, every problem in the existential theory of the reals has a polynomial-time many-one reduction to an instance of one of these problems, and in turn these problems are reducible to the existential theory of the reals. [4] [17] A number of problems of this type concern the recognition of intersection graphs of a certain type.
Every polynomial in one variable x with real coefficients can be uniquely written as the product of a constant, polynomials of the form x + a with a real, and polynomials of the form x 2 + ax + b with a and b real and a 2 − 4b < 0 (which is the same thing as saying that the polynomial x 2 + ax + b has no real roots).
Finding the real roots of a polynomial with real coefficients is a problem that has received much attention since the beginning of 19th century, and is still an active domain of research. Most root-finding algorithms can find some real roots, but cannot certify having found all the roots.
This shows that the root α j will be less stable if there are many roots α k close to α j, in the sense that the distance |α j − α k | between them is smaller than |α j |. Example. For the root α 1 = 1, the derivative is equal to 1/19! which is very small; this root is stable even for large changes in t.
If the coefficients are real and the polynomial has odd degree, then it must have at least one real root. To find this, use a real value of p 0 as the initial guess and make q 0 and r 0, etc., complex conjugate pairs. Then the iteration will preserve these properties; that is, p n will always be real, and q n and r n, etc., will always be ...
An illustration of Newton's method. In numerical analysis, the Newton–Raphson method, also known simply as Newton's method, named after Isaac Newton and Joseph Raphson, is a root-finding algorithm which produces successively better approximations to the roots (or zeroes) of a real-valued function.
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