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  2. Rouché's theorem - Wikipedia

    en.wikipedia.org/wiki/Rouché's_theorem

    Since has zeros inside the disk | | < (because >), it follows from Rouché's theorem that also has the same number of zeros inside the disk. One advantage of this proof over the others is that it shows not only that a polynomial must have a zero but the number of its zeros is equal to its degree (counting, as usual, multiplicity).

  3. Root-finding algorithm - Wikipedia

    en.wikipedia.org/wiki/Root-finding_algorithm

    In numerical analysis, a root-finding algorithm is an algorithm for finding zeros, also called "roots", of continuous functions. A zero of a function f is a number x such that f ( x ) = 0 . As, generally, the zeros of a function cannot be computed exactly nor expressed in closed form , root-finding algorithms provide approximations to zeros.

  4. Geometrical properties of polynomial roots - Wikipedia

    en.wikipedia.org/wiki/Geometrical_properties_of...

    If the coefficients a i of a random polynomial are independently and identically distributed with a mean of zero, most complex roots are on the unit circle or close to it. In particular, the real roots are mostly located near ±1, and, moreover, their expected number is, for a large degree, less than the natural logarithm of the degree.

  5. Bézout's theorem - Wikipedia

    en.wikipedia.org/wiki/Bézout's_theorem

    The concept of multiplicity is fundamental for Bézout's theorem, as it allows having an equality instead of a much weaker inequality. Intuitively, the multiplicity of a common zero of several polynomials is the number of zeros into which the common zero can split when the coefficients are slightly changed.

  6. Zero of a function - Wikipedia

    en.wikipedia.org/wiki/Zero_of_a_function

    The fundamental theorem of algebra shows that any non-zero polynomial has a number of roots at most equal to its degree, and that the number of roots and the degree are equal when one considers the complex roots (or more generally, the roots in an algebraically closed extension) counted with their multiplicities. [3]

  7. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    This is equivalent to finding the zeroes of a single vector-valued function :. In the formulation given above, the scalars x n are replaced by vectors x n and instead of dividing the function f ( x n ) by its derivative f ′ ( x n ) one instead has to left multiply the function F ( x n ) by the inverse of its k × k Jacobian matrix J F ( x n ) .

  8. 24 Discontinued '70s and '80s Foods That We'll Never ... - AOL

    www.aol.com/finance/24-discontinued-70s-80s...

    3. Keebler Fudge Magic Middles. Neither the chocolate fudge cream inside a shortbread cookie nor versions with peanut butter or chocolate chip crusts survived.

  9. Hilbert's Nullstellensatz - Wikipedia

    en.wikipedia.org/wiki/Hilbert's_Nullstellensatz

    In mathematics, Hilbert's Nullstellensatz (German for "theorem of zeros", or more literally, "zero-locus-theorem") is a theorem that establishes a fundamental relationship between geometry and algebra. This relationship is the basis of algebraic geometry. It relates algebraic sets to ideals in polynomial rings over algebraically closed fields.