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docs(matrices): update matrices doc
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src/matrices/binomial.jl

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@@ -3,12 +3,10 @@ Binomial Matrix
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===============
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The matrix is a multiple of an involutory matrix.
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*Input options:*
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+ dim: the dimension of the matrix.
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*References:*
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# Input Options
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- dim: the dimension of the matrix.
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# References
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**G. Boyd, C.A. Micchelli, G. Strang and D.X. Zhou**,
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Binomial matrices, Adv. in Comput. Math., 14 (2001), pp 379-391.
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"""

src/matrices/cauchy.jl

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@@ -4,18 +4,13 @@ Cauchy Matrix
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Given two vectors `x` and `y`, the `(i,j)` entry of the Cauchy matrix is
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`1/(x[i]+y[j])`.
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*Input options*:
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+ x: an integer, as vectors 1:x and 1:x.
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+ x, y: two integers, as vectors 1:x and 1:y.
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+ x: a vector. `y` defaults to `x`.
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+ x, y: two vectors.
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*References:*
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# Input Options
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- x: an integer, as vectors 1:x and 1:x.
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- x, y: two integers, as vectors 1:x and 1:y.
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- x: a vector. `y` defaults to `x`.
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- x, y: two vectors.
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# References
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**N. J. Higham**, Accuracy and Stability of Numerical Algorithms,
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second edition, Society for Industrial and Applied Mathematics, Philadelphia, PA, USA,
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2002; sec. 28.1

src/matrices/chebspec.jl

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@@ -6,15 +6,12 @@ If `k = 0`,the generated matrix is nilpotent and a vector with
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matrix is nonsingular and well-conditioned. Its eigenvalues
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have negative real parts.
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*Input options:*
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+ dim, k: `dim` is the dimension of the matrix and
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# Input Options
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- dim, k: `dim` is the dimension of the matrix and
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`k = 0 or 1`.
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- dim: `k=0`.
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+ dim: `k=0`.
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*References:*
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# References
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**L. N. Trefethen and M. R. Trummer**, An instability
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phenomenon in spectral methods, SIAM J. Numer. Anal., 24 (1987), pp. 1008-1023.
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"""

src/matrices/chow.jl

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@@ -3,16 +3,13 @@ Chow Matrix
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===========
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The Chow matrix is a singular Toeplitz lower Hessenberg matrix.
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*Input options:*
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+ dim, alpha, delta: `dim` is dimension of the matrix.
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# Input Options
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- dim, alpha, delta: `dim` is dimension of the matrix.
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`alpha`, `delta` are scalars such that `A[i,i] = alpha + delta` and
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`A[i,j] = alpha^(i + 1 -j)` for `j + 1 <= i`.
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- dim: `alpha = 1`, `delta = 0`.
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+ dim: `alpha = 1`, `delta = 0`.
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*References:*
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# References
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**T. S. Chow**, A class of Hessenberg matrices with known
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eigenvalues and inverses, SIAM Review, 11 (1969), pp. 391-395.
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"""

src/matrices/circulant.jl

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@@ -5,14 +5,11 @@ A circulant matrix has the property that each row is obtained
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by cyclically permuting the entries of the previous row one
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step forward.
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*Input options:*
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+ vec: a vector.
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+ dim: an integer, as vector 1:dim.
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*References:*
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# Input Options
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- vec: a vector.
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- dim: an integer, as vector 1:dim.
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# References
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**P. J. Davis**, Circulant Matrices, John Wiley, 1977.
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"""
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struct Circulant{T<:Number} <: AbstractMatrix{T}

src/matrices/clement.jl

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@@ -4,16 +4,13 @@ Clement Matrix
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The Clement matrix is a tridiagonal matrix with zero
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diagonal entries. If k = 1, the matrix is symmetric.
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*Input options:*
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+ dim, k: `dim` is the dimension of the matrix.
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# Input Options
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- dim, k: `dim` is the dimension of the matrix.
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If `k = 0`, the matrix is of type `Tridiagonal`.
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If `k = 1`, the matrix is of type `SymTridiagonal`.
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- dim: `k = 0`.
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+ dim: `k = 0`.
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*References:*
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# References
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**P. A. Clement**, A class of triple-diagonal
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matrices for test purposes, SIAM Review, 1 (1959), pp. 50-52.
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"""

src/matrices/companion.jl

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@@ -8,13 +8,10 @@ The companion matrix to a monic polynomial
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is the n-by-n matrix with ones on the subdiagonal and
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the last column given by the coefficients of `a(x)`.
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*Input options:*
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+ vec: `vec` is a vector of coefficients.
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+ dim: `vec = [1:dim;]`. `dim` is the dimension of the matrix.
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+ polynomial: `polynomial` is a polynomial. vector will be appropriate values from coefficients.
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# Input Options
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- vec: `vec` is a vector of coefficients.
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- dim: `vec = [1:dim;]`. `dim` is the dimension of the matrix.
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- polynomial: `polynomial` is a polynomial. vector will be appropriate values from coefficients.
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"""
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struct Companion{T<:Number} <: AbstractMatrix{T}
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n::Integer

src/matrices/dingdong.jl

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@@ -5,12 +5,10 @@ The Dingdong matrix is a symmetric Hankel matrix invented
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by DR. F. N. Ris of IBM, Thomas J Watson Research Centre.
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The eigenvalues cluster around `π/2` and `-π/2`.
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*Input options:*
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+ dim: the dimension of the matrix.
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*References:*
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# Input Options
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- dim: the dimension of the matrix.
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# References
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**J. C. Nash**, Compact Numerical Methods for
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Computers: Linear Algebra and Function Minimisation,
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second edition, Adam Hilger, Bristol, 1990 (Appendix 1).

src/matrices/fiedler.jl

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The Fiedler matrix is symmetric matrix with a dominant
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positive eigenvalue and all the other eigenvalues are negative.
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*Input options:*
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+ vec: a vector.
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+ dim: `dim` is the dimension of the matrix. `vec=[1:dim;]`.
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*References:*
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# Input Options
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- vec: a vector.
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- dim: `dim` is the dimension of the matrix. `vec=[1:dim;]`.
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# References
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**G. Szego**, Solution to problem 3705, Amer. Math.
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Monthly, 43 (1936), pp. 246-259.
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src/matrices/forsythe.jl

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@@ -4,12 +4,10 @@ Forsythe Matrix
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The Forsythe matrix is a n-by-n perturbed Jordan block.
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This generator is adapted from N. J. Higham's Test Matrix Toolbox.
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*Input options:*
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+ dim, alpha, lambda: `dim` is the dimension of the matrix.
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# Input Options
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- dim, alpha, lambda: `dim` is the dimension of the matrix.
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`alpha` and `lambda` are scalars.
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+ dim: `alpha = sqrt(eps(type))` and `lambda = 0`.
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- dim: `alpha = sqrt(eps(type))` and `lambda = 0`.
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"""
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struct Forsythe{T<:Number} <: AbstractMatrix{T}
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n::Integer

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