  Equiangular Algorithm generates a set of equiangular normalized vectors with
given angle {\theta} using a set of linearly independence vectors in a real
inner product space, which span the same subspaces. The outcome of EA on column
vectors of a matrix A provides a matrix decomposition A = SR, where S is called
Equiangular Matrix which has equiangular column vectors. In this paper we
discuss some properties of equiangular matrices. The inverse and eigenvalue
problems of these matrices are studied. Also we derive some canonical forms of
some matrices based on equiangular ones.
