Matlab built-in function condest: c = condest(A) computes a lower bound c for the 1-norm condition number of a square matrix A. c = condest(A,t) changes t, a positive integer parameter equal to the number of columns in an underlying iteration matrix. Increasing the number of columns usually gives a better condition estimate but increases the cost. The default is t = 2, which almost always gives an estimate correct to within a factor 2. [c,v] = condest(A) also computes a vector v which is an approximate null vector if c is large. v satisfies norm(A*v,1) = norm(A,1)*norm(v,1)/c.
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Singler, John; Kramer, Boris: A POD projection method for large-scale algebraic Riccati equations (2016)
- Brás, Carmo P.; Hager, William W.; Júdice, Joaquim J.: An investigation of feasible descent algorithms for estimating the condition number of a matrix (2012)
- Higham, Nicholas J.; Tisseur, Françoise: A block algorithm for matrix 1-norm estimation, with an application to 1-norm pseudospectra (2000)
- Hager, William W.: Condition estimates (1984)