Meanwhile, its
inverse matrix can be computed as [K.sup.-1] [member of] M ([Z.sub.N]).
MORRISON, Adjustment of an
inverse matrix corresponding to a change in one element of a given matrix, Ann.
Because the traditional greedy pursuit algorithm needs to compute the
inverse matrix of the sensing matrix, this process requires a significant amount of computation time and storage space, resulting in lower reconstruction probability.
This means that the matrix [[parallel][r.sub.ij](x)[parallel].sup.3.sub.1] is invertible and its
inverse matrix with S reduces A(x) to B(x).
where [Q.sub.m.sup.-1] is the
inverse matrix of [Q.sub.m], [H.sub.m.sup.T] is the transpose matrix of [H.sub.m], and [[[H.sub.m.sup.T] [Q.sub.m.sup.-1] [H.sub.m]].sup.-1] is the
inverse matrix of [[[H.sub.m.sup.T] [Q.sub.m.sup.-1] [H.sub.m]]].
In case of (4x4) coefficient matrix in (6), its
inverse matrix is given by
It is noteworthy to mention a family of preconditioners that are based on the physical properties of the problem and more specifically on the idea that
inverse matrix that is approximately represented by the preconditioner is essentially an approximate solution of the electromagnetic problem.
To achieve synchronization between systems (16) and (17), we assume that M is an invertible matrix and [M.sup.-]1 its
inverse matrix. Hence, we have the following result.
where [A.sup.(1)T] is a sub-matrix of the matrix [A.sup.T] =[[A.sup.(1)] [A.sup.(2)]] that has an
inverse matrix (corresponds to the sub-matrix [D.sup.(1)] of the flexibility matrix D and to sub-vector [[theta].sup.(1).sub.p]; selection method of the lines for sub-matrix [A.sup.(1)T] is based only on the existence of its
inverse matrix).