  The article discusses the matrices of the three forms whose inversions are:
tridiagonal matrix, banded matrix or block-tridiagonal matrix and their
relationships with the covariance matrices of measurements of ordinary (simple)
Markov Random Processes (MRP), multiconnected MRP and vector MRP respectively.
Such covariance matrices are frequently occurring in the problems of optimal
filtering, extrapolation and interpolation of MRP and Markov Random Fields
(MRF). It is shown, that the structure of these three forms of matrices has the
same form, but the matrix elements in the first case are scalar quantities; in
the second case matrix elements representing a product of vectors of dimension
m; and in the third case, the off-diagonal elements are the product of matrices
and vectors of dimension m. The properties of such matrices were investigated
and a simple formulas of their inversion was founded. Also computational
efficiency in the storage and inverse of such matrices have been considered. To
illustrate the acquired results an example of the covariance matrix inversions
of two-dimensional MRP is given.
