A variant of the Gohberg-Semencul formula involving circulant matrices
SIAM Journal on Matrix Analysis and Applications
An improved Newton interaction for the generalized inverse of a Matrix, with applications
SIAM Journal on Scientific and Statistical Computing
Decreasing the displacement rank of a matrix
SIAM Journal on Matrix Analysis and Applications
Parallel solution of Toeplitzlike linear systems
Journal of Complexity
Polynomial and matrix computations (vol. 1): fundamental algorithms
Polynomial and matrix computations (vol. 1): fundamental algorithms
Fast Gaussian elimination with partial pivoting for matrices with displacement structure
Mathematics of Computation
Displacement structure: theory and applications
SIAM Review
Matrix computations (3rd ed.)
Newton's iteration for inversion of Cauchy-like and other structured matrices
Journal of Complexity
Fast reliable algorithms for matrices with structure
Fast reliable algorithms for matrices with structure
Newton's iteration for structured matrices
Fast reliable algorithms for matrices with structure
Structured matrices and polynomials: unified superfast algorithms
Structured matrices and polynomials: unified superfast algorithms
Inversion of Displacement Operators
SIAM Journal on Matrix Analysis and Applications
Concurrent Iterative Algorithm for Toeplitz-like Linear Systems
IEEE Transactions on Parallel and Distributed Systems
FOCS '98 Proceedings of the 39th Annual Symposium on Foundations of Computer Science
Fast algorithms for multivariable systems.
Fast algorithms for multivariable systems.
Computers & Mathematics with Applications
Algebraic and numerical algorithms
Algorithms and theory of computation handbook
Applications of FFT and structured matrices
Algorithms and theory of computation handbook
Root-finding by expansion with independent constraints
Computers & Mathematics with Applications
Multi-dimensional Capon spectral estimation using discrete Zhang neural networks
Multidimensional Systems and Signal Processing
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Iterative processes for the inversion of structured matrices can be further improved by using a technique for compression and refinement via the least-squares computation. We review such processes and elaborate upon incorporation of this technique into the known frameworks.