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Fast Generalized Bruhat Decomposition

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6244))

Abstract

The deterministic recursive pivot-free algorithms for computing the generalized Bruhat decomposition of the matrix in the field and for the computation of the inverse matrix are presented. This method has the same complexity as algorithm of matrix multiplication, and it is suitable for the parallel computer systems.

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References

  1. Grigoriev, D.: Analogy of Bruhat decomposition for the closure of a cone of Chevalley group of a classical serie. Soviet Math. Dokl. 23(2), 393–397 (1981)

    Google Scholar 

  2. Grigoriev, D.: Additive complexity in directed computations. Theoretical Computer Science 19, 39–67 (1982)

    Article  MathSciNet  Google Scholar 

  3. Kolotilina, L.Y.: Sparsity of Bruhat decomposition factors of nonsingular matrices. Notes of Scientific Seminars of LOMI 202, 5–17 (1992)

    MATH  Google Scholar 

  4. Kolotilina, L.Y., Yemin, A.Y.: Bruhat decomposition and solution of linear algebraic systems with sparse matrices. Sov. J. Numer. Anal. and Math. Model. 2, 421–436 (1987)

    MATH  Google Scholar 

  5. Strassen, V.: Gaussian Eelimination is not optimal. Numerische Mathematik 13, 354–356 (1969)

    Article  MathSciNet  MATH  Google Scholar 

  6. Malaschonok, G.I.: Effective matrix methods in commutative domains. In: Formal Power Series and Algebraic Combinatorics, pp. 506–517. Springer, Berlin (2000)

    Chapter  Google Scholar 

  7. Malaschonok, G.I.: Matrix Computational Methods in Commutative Rings. Tambov State University, Tambov (2002)

    Google Scholar 

  8. Akritas, A., Malaschonok, G.: Computation of adjoint matrix. In: Alexandrov, V.N., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2006. LNCS, vol. 3992, pp. 486–489. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  9. Bunch, J., Hopkroft, J.: Triangular factorization and inversion by fast matrix multiplication. Mat. Comp. 28, 231–236 (1974)

    Article  MathSciNet  MATH  Google Scholar 

  10. Watt, S.M.: Pivot-free block matrix inversion. In: Maple Conf. 2006, Waterloo, Canada, July 23-26 (2006), http://www.csd.uwo.ca/~watt/pub/reprints/2006-mc-bminv-poster.pdf

  11. Watt, S.M.: Pivot-free block matrix inversion. In: Proc. 8th International Symposium on Symbolic and Numeric Algorithms in Symbolic Computation (SYNASC), pp. 151–155. IEEE Computer Society, Los Alamitos (2006)

    Google Scholar 

  12. Eberly, W.: Efficient parallel independent subsets and matrix factorization. In: Proc. 3rd IEEE Symposium on Parallel and Distributed Processing, Dallas, USA, pp. 204–211 (1991)

    Google Scholar 

  13. Kaltofen, E., Pan, V.: Processor-efficient parallel solution of linear systems over an abstract field. In: Proc. 3rd Annual ACM Symposium on Parallel Algorithms and Architectures, pp. 180–191. ACM Press, New York (1991)

    Google Scholar 

  14. Kaltofen, E., Pan, V.: Processor-efficient parallel solution of linear systems II: The general case. In: Proc. 33rd IEEE Symposium on Foundations of Computer Science, Pittsburgh, USA, pp. 714–723 (1992)

    Google Scholar 

  15. Kaltofen, E., Pan, V.: Parallel solution of Toeplitz and Toeplitz-like linear systems over fields of small positive characteristic. In: Proc. PASCO 1994: First International Symposium on Parallel Symbolic Computation, pp. 225–233. World Scientific Publishing, Singapore (1994)

    Google Scholar 

  16. Malaschonok, G.I.: Parallel Algorithms of Computer Algebra. In: Proc. Conference Dedicated to the 75 Years of the Mathematical and Physical Dept. of Tambov State University, November 22-24, pp. 44–56. Tambov State Univ., Tambov (2005)

    Google Scholar 

  17. Malaschonok, G.I., Zuyev, M.S.: Generalized algorithm for computing of inverse matrix. In: 11th Conf. “Derzhavinskie Chteniya”, February 2-6, pp. 58–62. Tambov State Univ., Tambov (2006)

    Google Scholar 

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Malaschonok, G. (2010). Fast Generalized Bruhat Decomposition. In: Gerdt, V.P., Koepf, W., Mayr, E.W., Vorozhtsov, E.V. (eds) Computer Algebra in Scientific Computing. CASC 2010. Lecture Notes in Computer Science, vol 6244. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15274-0_16

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  • DOI: https://doi.org/10.1007/978-3-642-15274-0_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15273-3

  • Online ISBN: 978-3-642-15274-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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