enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Reciprocal rule - Wikipedia

    en.wikipedia.org/wiki/Reciprocal_rule

    In calculus, the reciprocal rule gives the derivative of the reciprocal of a function f in terms of the derivative of f.The reciprocal rule can be used to show that the power rule holds for negative exponents if it has already been established for positive exponents.

  3. Newton's method - Wikipedia

    en.wikipedia.org/wiki/Newton's_method

    This is the case, for example, if f(x) = x 3 − 2x + 2. For this function, it is even the case that Newton's iteration as initialized sufficiently close to 0 or 1 will asymptotically oscillate between these values. For example, Newton's method as initialized at 0.99 yields iterates 0.99, −0.06317, 1.00628, 0.03651, 1.00196, 0.01162, 1.00020 ...

  4. Quotient rule - Wikipedia

    en.wikipedia.org/wiki/Quotient_rule

    3.1 Proof from derivative definition and limit properties. ... Download QR code; Print/export ... The quotient rule states that the derivative of h(x) is ...

  5. Differentiation rules - Wikipedia

    en.wikipedia.org/wiki/Differentiation_rules

    The derivatives in the table above are for when the range of the inverse secant is [,] and when the range of the inverse cosecant is [,]. It is common to additionally define an inverse tangent function with two arguments , arctan ⁡ ( y , x ) {\textstyle \arctan(y,x)} .

  6. Product rule - Wikipedia

    en.wikipedia.org/wiki/Product_rule

    In calculus, the product rule (or Leibniz rule [1] or Leibniz product rule) is a formula used to find the derivatives of products of two or more functions.For two functions, it may be stated in Lagrange's notation as () ′ = ′ + ′ or in Leibniz's notation as () = +.

  7. Differential calculus - Wikipedia

    en.wikipedia.org/wiki/Differential_calculus

    One way of improving the approximation is to take a quadratic approximation. That is to say, the linearization of a real-valued function f(x) at the point x 0 is a linear polynomial a + b(xx 0), and it may be possible to get a better approximation by considering a quadratic polynomial a + b(xx 0) + c(xx 0) 2.

  8. Danskin's theorem - Wikipedia

    en.wikipedia.org/wiki/Danskin's_theorem

    The following version is proven in "Nonlinear programming" (1991). [2] Suppose (,) is a continuous function of two arguments, : where is a compact set.. Under these conditions, Danskin's theorem provides conclusions regarding the convexity and differentiability of the function = (,).

  9. Differential of a function - Wikipedia

    en.wikipedia.org/wiki/Differential_of_a_function

    A number of properties of the differential follow in a straightforward manner from the corresponding properties of the derivative, partial derivative, and total derivative. These include: [ 11 ] Linearity : For constants a and b and differentiable functions f and g , d ( a f + b g ) = a d f + b d g . {\displaystyle d(af+bg)=a\,df+b\,dg.}