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  2. Degree of a polynomial - Wikipedia

    en.wikipedia.org/wiki/Degree_of_a_polynomial

    Then, f(x)g(x) = 4x 2 + 4x + 1 = 1. Thus deg(f⋅g) = 0 which is not greater than the degrees of f and g (which each had degree 1). Since the norm function is not defined for the zero element of the ring, we consider the degree of the polynomial f(x) = 0 to also be undefined so that it follows the rules of a norm in a Euclidean domain.

  3. Difference quotient - Wikipedia

    en.wikipedia.org/wiki/Difference_quotient

    The difference between two points, themselves, is known as their Delta (ΔP), as is the difference in their function result, the particular notation being determined by the direction of formation: Forward difference: ΔF(P) = F(P + ΔP) − F(P); Central difference: δF(P) = F(P + ⁠ 1 / 2 ⁠ ΔP) − F(P − ⁠ 1 / 2 ⁠ ΔP);

  4. Multiple integral - Wikipedia

    en.wikipedia.org/wiki/Multiple_integral

    Just as the definite integral of a positive function of one variable represents the area of the region between the graph of the function and the x-axis, the double integral of a positive function of two variables represents the volume of the region between the surface defined by the function (on the three-dimensional Cartesian plane where z = f(x, y)) and the plane which contains its domain. [1]

  5. Boolean function - Wikipedia

    en.wikipedia.org/wiki/Boolean_function

    The concept can be generalized as a k-ary derivative in the direction dx, obtained as the difference (XOR) of the function at x and x + dx. [8] The Möbius transform (or Boole-Möbius transform) of a Boolean function is the set of coefficients of its polynomial (algebraic normal form), as a function of the monomial exponent vectors.

  6. Covariance - Wikipedia

    en.wikipedia.org/wiki/Covariance

    The covariance is sometimes called a measure of "linear dependence" between the two random variables. That does not mean the same thing as in the context of linear algebra (see linear dependence ). When the covariance is normalized, one obtains the Pearson correlation coefficient , which gives the goodness of the fit for the best possible ...

  7. Separation of variables - Wikipedia

    en.wikipedia.org/wiki/Separation_of_variables

    where the two variables x and y have been separated. Note dx (and dy) can be viewed, at a simple level, as just a convenient notation, which provides a handy mnemonic aid for assisting with manipulations. A formal definition of dx as a differential (infinitesimal) is somewhat advanced.

  8. Mutual information - Wikipedia

    en.wikipedia.org/wiki/Mutual_information

    In probability theory and information theory, the mutual information (MI) of two random variables is a measure of the mutual dependence between the two variables. More specifically, it quantifies the " amount of information " (in units such as shannons ( bits ), nats or hartleys ) obtained about one random variable by observing the other random ...

  9. Boolean algebra - Wikipedia

    en.wikipedia.org/wiki/Boolean_algebra

    A law of Boolean algebra is an identity such as x ∨ (y ∨ z) = (x ∨ y) ∨ z between two Boolean terms, where a Boolean term is defined as an expression built up from variables and the constants 0 and 1 using the operations ∧, ∨, and ¬. The concept can be extended to terms involving other Boolean operations such as ⊕, →, and ≡ ...