Accession Number : ADA266606


Title :   Reducing Data Dimension to Lower Signal Processing Computational Requirements and Maximize Performance


Descriptive Note : Final rept. 1 Sep 1989-31 Mar 1993


Corporate Author : WISCONSIN UNIV-MADISON


Personal Author(s) : Van Veen, Barry D


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a266606.pdf


Report Date : 11 May 1993


Pagination or Media Count : 5


Abstract : The problem studied concerns reducing the dimension of data by mapping it through rectangular matrix transformations before application of signal processing algorithms. Our work addressed applications of this principle in adaptive beamforming, spectral estimation, and detection problems. While dimension reduction often leads to dramatic reductions in the computational burden of the signal processing algorithm, it can also introduce significant asymptotic performance losses if the transformation is not chosen properly. We choose dimension reducing transformations to optimize performance criteria associated with the problem of interest. Our results indicate that dramatic reductions in dimension can be achieved with relatively small asymptotic performance losses using these design procedures. Performance analyses demonstrate that dimension reduction is most profitably used in applications where relatively short data records are available or fast response time is required. In these cases dimension reduction actually improves performance. Partially adaptive beamforming, Minimum variance spectrum analysis, Adaptive detection, Beamspace processing, Dimension reduction.


Descriptors :   *SIGNAL PROCESSING , *DATA REDUCTION , *BEAM FORMING , ALGORITHMS , OPTIMIZATION , COMPUTATIONS , MAPPING , SPECTRUM ANALYSIS , RECORDS , LOSSES , DETECTION , TIME , TRANSFORMATIONS(MATHEMATICS) , SIGNALS


Subject Categories : Electrical and Electronic Equipment


Distribution Statement : APPROVED FOR PUBLIC RELEASE