In numerical analysis, inverse iteration (also known as the inverse power method) is an iterative eigenvalue algorithm. It allows one to find an approximate...

understood as variations of the power iteration. For instance, the inverse iteration method applies power iteration to the matrix A − 1 {\displaystyle A^{-1}}...

approximation of the inverse square root of the input. Treating the bits again as a floating-point number, it runs one iteration of Newton's method, yielding...

iteration, μ = λ. Power iteration finds the largest eigenvalue in absolute value, so even when λ is only an approximate eigenvalue, power iteration is...

zy + cy; zx = xtemp + cx; iteration = iteration + 1; } if (iteration == max_iteration) return black; else return iteration; } f ( z ) = z n + c {\displaystyle...

The algorithm is very similar to inverse iteration, but replaces the estimated eigenvalue at the end of each iteration with the Rayleigh quotient. Begin...

sequences of inverse matrices used in obtaining matrix square roots by Denman–Beavers iteration. That may need more than one pass of the iteration at each...

inverse function. The inverse function is also differentiable, and the inverse function rule expresses its derivative as the multiplicative inverse of...

or several times. The process of repeatedly applying the same function is called iteration. In this process, starting from some initial object, the result of applying...

{\displaystyle b} iterated logarithm (although differing in minor details of rounding) and forms an inverse to the operation of tetration. The iterated logarithm...

the iteration can be determined directly from the difference between the location of the iteration from the left and the location of the iteration from...

Each iteration of the Lanczos algorithm produces another column of the final transformation matrix V {\displaystyle V} , whereas an iteration of Householder...

reconstruction artifacts in the image. Iterative algorithms approach the correct solution using multiple iteration steps, which allows to obtain a better...

become arbitrarily small. This iteration can also be generalized to a wider sort of inverses; for example, matrix inverses. Every real or complex number...

In mathematics, and in particular linear algebra, the Moore–Penrose inverse ⁠ A + {\displaystyle A^{+}} ⁠ of a matrix ⁠ A {\displaystyle A} ⁠, often called...

In computer animation and robotics, inverse kinematics is the mathematical process of calculating the variable joint parameters needed to place the end...

An inverse problem in science is the process of calculating from a set of observations the causal factors that produced them: for example, calculating...

matrices are unavailable or are impractical to compute at every iteration. Some iterative methods that reduce to Newton's method, such as sequential quadratic...

The Landweber iteration or Landweber algorithm is an algorithm to solve ill-posed linear inverse problems, and it has been extended to solve non-linear...

the shift-and-invert problem by an iterative solver, e.g., the power iteration. This gives the Inverse iteration, which normally converges to the eigenvector...

mathematics, the inverse function of a function f (also called the inverse of f) is a function that undoes the operation of f. The inverse of f exists if...

iteration, produces another image visually similar to the original. In 1989, Arnaud Jacquin presented a solution to a restricted form of the inverse problem...

values, then each iteration of the algorithm produces a successively more accurate approximation to the root. Since the iteration must be stopped at...

contrapoint (a5 = −3.35724) and the iterate remains the same (b5 = b4). In the sixth iteration, we cannot use inverse quadratic interpolation because b5...

VLSI hardware implements inverse square root using a second degree polynomial estimation followed by a Goldschmidt iteration. If S < 0, then its principal...

Knyazev, Neymeyr (2003). "A geometric theory for preconditioned inverse iteration III: A short and sharp convergence estimate for generalized eigenvalue...

algorithms Arnoldi iteration Inverse iteration Jacobi method Lanczos iteration Power iteration QR algorithm Rayleigh quotient iteration Gram–Schmidt process:...

the Jacobian determinant, and the multiplicative inverse of the derivative is replaced by the inverse of the Jacobian matrix. The Jacobian determinant...

locating the eigenvalues of a matrix Power iteration Inverse iteration Rayleigh quotient iteration Arnoldi iteration — based on Krylov subspaces Lanczos algorithm...

Inverse probability weighting is a statistical technique for estimating quantities related to a population other than the one from which the data was...