A New Technique for Multidimensional Signal Compression

1. ABSTRACT The problem of efficiently compressing a large number, L, of fl dimensional signal vectors is considered. The approach suggested here achieves efficiencies over current preprocessing and Karhunen-LoCve techniques when both L and N are large. Preprocessing and partitioning techniques are first ap plied to the L x hf data matrix 3 to reduce the database to a manageable number of subblocks of lower dimension. Within each subblock an iterative chain approhation is proposed that effects a transform at each stage of the iterative scheme. A particularly appealing transform, using prolate spheroidal sequences, is suggested. To evaluate a reduced dimensionality approximation for the expansion coefficients, the approach used in the orthogonal Procrustes problem solution is combined with an iterative interlacing technique due to Daugavet for factorizing matrices.