Least-squares lattice interpolation filters

This paper develops a time as well as order update recursion for linear least-squares lattice (LSL) interpolation filters. The LSL interpolation filter has the nice stage-to-stage modularity which allows its length to be increased or decreased “two-sidedly” (i.e., both past and future) without affecting the already computed parameters. The LSL interpolation filter is also efficient in computation, flexible in implementation and fast in convergence. The computer simulation results shown in this paper reveal that although interpolation needs more computing power than prediction does, interpolation can generate much smaller error power and thus reduces much more temporal redundancy than prediction does