bundles / scipy latest / scipy / optimize / _trustregion_exact / estimate_smallest_singular_value
function
scipy.optimize._trustregion_exact:estimate_smallest_singular_value
Signature
def estimate_smallest_singular_value ( U ) Summary
Given upper triangular matrix U estimate the smallest singular value and the correspondent right singular vector in O(n**2) operations.
Parameters
U: ndarraySquare upper triangular matrix.
Returns
s_min: floatEstimated smallest singular value of the provided matrix.
z_min: ndarrayEstimated right singular vector.
Notes
The procedure is based on [1] and is done in two steps. First, it finds a vector e with components selected from {+1, -1} such that the solution w from the system U.T w = e is as large as possible. Next it estimate U v = w. The smallest singular value is close to norm(w)/norm(v) and the right singular vector is close to v/norm(v).
The estimation will be better more ill-conditioned is the matrix.
Aliases
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scipy.optimize._trustregion_exact.estimate_smallest_singular_value