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Complexity theory and numerical analysis

  • Steve Smale (a1)
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Complexity theory of numerical analysis is the study of the number of arithmetic operations required to pass from the input to the output of a numerical problem.

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Shub M. and Smale S. (1993 a), ‘Complexity of Bézout's theorem I: geometric aspect’, J. Amer. Math. Soc. 6, 459501. Referred to as Bez I.
Shub M. and Smale S. (1993 b), Complexity of Bézout's theorem II: volumes and probabilities, in Computational Algebraic Geometry (Eyssette F. and Galligo A., eds), Vol. 109 of Progress in Mathematics, pp. 267285. Referred to as Bez II.
Shub M. and Smale S. (1993 c), ‘Complexity of Bézout's theorem III: condition number and packing’, J. Complexity 9, 414. Referred to as Bez III.
Shub M. and Smale S. (1994), ‘Complexity of Bézout's theorem V: polynomial time’, Theoret. Comput. Sci. 133, 141164. Referred to as Bez V.
Shub M. and Smale S. (1996), ‘Complexity of Bézout's theorem IV: probability of success; extensions’, SIAM J. Numer. Anal. 33, 128148. Referred to as Bez IV.
Smale S. (1976), ‘A convergent process of price adjustment and global Newton method’, J. Math. Economy 3, 107120.
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Acta Numerica
  • ISSN: 0962-4929
  • EISSN: 1474-0508
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