... downdating algorithm % % snrloss_stabhyp % % resulting ratio when the stabilized hyperbolic Householder transformation is used in the downdating algorithm % r_seed seed for the random number generator % n number of sensors % m number of ...

... downdating problems in the next section . The lower - triangular matrix L , the upper - triangular matrix R and diagonal matrix are small for low rank matrix A. We further assign a general name for these three types of decomposition as ...

... downdating , since it is more complex than updating . To set the stage for ULVD downdating , in §4.1 , we give a brief outline of a Gram - Schmidt procedure for downdating the Q - R decomposition . In §4.2 and §4.3 , we give the ULVD ...

... downdating of matrix decompositions have been intensively studied [ 13 , 17 ] , for example , updating and downdating of least squares solutions [ 18 , 19 ] , the QR decomposition [ 20 , 21 ] , adaptive condition estimation [ 22–24 ] ...

... downdating the Cholesky factorization , and describe two existing algorithms , the LINPACK method and the hyperbolic method , used com- monly now in downdating . The applications , especially to recursive least squares filtering , are ...

Here [epsilon] is some tolerance. If the matrix A results from statistical observations, it is often desired to remove old observations, thus deleting a row from C. In matrix terms, this is called a downdate.

... downdating . Updating methods discussed here are closely related to the ideas and methods of the Kalman filter , which is discussed in Chapter 4 . The problem of suitably modifying a regression equation arises in sev- eral contexts ...