VLSI architecture for matrix inversion using modified gram-schmidt based QR decomposition

Proceedings of the IEEE International Conference on VLSI Design

Volumn , Issue , 2007, Pages 836-841

  Singh, Chitranjan K ^a   Prasad, Sushma Honnavara ^a   Balsara, Poras T ^a  

^a The University of Texas at Dallas   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARCHITECTURE; COMMUNICATION; COMMUNICATION SYSTEMS; COMPUTER PROGRAMMING LANGUAGES; DECODING; EIGENVALUES AND EIGENFUNCTIONS; EMBEDDED SYSTEMS; HARDWARE; INTEGRATED CIRCUITS; LEARNING SYSTEMS; LINEAR EQUATIONS; MIM DEVICES; SIGNAL PROCESSING; TECHNOLOGY;

CHALLENGING PROBLEM; CLOCK RATES; CMOS TECHNOLOGIES; COMPUTATIONALLY INTENSIVE PROCESS; GRAM-SCHMIDT; HARDWARE IMPLEMENTATIONS; INTEGRAL MULTIPLES; INTERNATIONAL CONFERENCES; INVERSE COMPUTATION; MACHINE PRECISION; MATRIX INVERSIONS; MIMO COMMUNICATION SYSTEMS; ORTHOGONALIZATION; QR DECOMPOSITION (QRD); SIGNAL PROCESSING APPLICATIONS; SINGULAR MATRIX; SQUARE MATRICES; TIME UNITS; VLSI ARCHITECTURES; VLSI DESIGNS;

MATRIX ALGEBRA;

EID: 44849086279     PISSN: 10639667     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/VLSID.2007.177     Document Type: Conference Paper

References (11)

1. I. Telatar, "Capacity of muli-antenna gaussian channels," European Transactions on Telecommunications, vol. 10, no. 6, pp. 585-595, Nov./Dec. 1999.
2. T. Kailath, H. Vikalo, and B. Hassibi, "Mimo receive algorithms," in in Space-Time Wireless Systems: From Array Processing to MIMO Communications. Cambridge University Press, 2005.
3. A. Burian, J. Takala, and M. Ylinen, "A fi xed-point implementation of matrix inversion using cholesky decomposition," in Proc. IEEE Int. Midwest Symp. Circuits Systems, Midwest, Dec. 2003, pp. 1431-1434.
4. I. LaRoche and S. Roy, "An effi cient regular matrix inversion circuit architecture for mimo processing," in Proc. IEEE Int. Symp. Circuits Systems, Greece, May 2006, pp. 4819-4822.
5. A. El-Amawy and K. R. Dharmarajan, "Parallel vlsi algorithm for stable inversion of dense matrices," IEE Proceedings on Computers and Digital Techniques, vol. 136, no. 6, pp. 575-580, Nov. 1989.
6. G. H. Golub and C. F. V. Loan, Matrix Computations, 3rd ed. Baltimore, MD: John Hopkins University Press, 1996.
7. A. Björck, Numerical Methods for Least Squares Problems. Philadelphia, Pa: SIAM, 1996.
8. _, "Solving linear least squares problems by gram-schmidt orthogonalization," BIT 7, pp. 1-21, 1967.
9. A. Björck and C. Paige, "Loss and recapture of orthogonality in the modifi ed gram-schmidt algorithm," SIAM J. Matrix Anal. Appl., vol. 13(1), pp. 176-190, 1992.
10. A. Björck, "Numerics of gram-schmidt orthogonalization," Linear Algebra and Its Applications, vol. 198, pp. 297-316, 1994.
11. C.K. Singh, S. H. Prasad, and P. T. Balsara, "A fi xed-point implementation of qr decomposition," in Proc. IEEE Dallas Workshop Circuits Systems, Dallas, TX, Oct. 2006, to appear.