On determining a determinant: an algorithmic insight through statistical bounds

By Soubhik Chakraborty, Charu Wahi, Suman Kumar Sourabh, Lopamudra Ray Saraswati and Avi Mukherjee .

Abstract: Statistical bounds(asymptotic) and their empirical estimates over a finite range, the so called empirical O, were informally introduced in in S. Chakraborty and S. K. Sourabh[ On Why an algorithmic time complexity measure can be system invariant rather than system independent, Applied Mathematics and Computation, vol. 190, issue 1, 2007, p. 195-204] where it was claimed that they make average complexity more meaningful. The present paper shows that they are useful in worst cases as well as in best cases in addition to average cases with a case study on an efficient determinant algorithm.

Key Words: Determinant, {worst, average, best} case complexity, statistical bound, empirical O

Authors:
Soubhik Chakraborty, soubhikc@yahoo.co.in
Charu Wahi, charuwahiin@yahoo.co.in
Suman Kumar Sourabh, sourabh.suman@rediffmail.com
Lopamudra Ray Saraswati, lopamudrars@gmail.com
Avi Mukherjee, avimukherjee@hotmail.com

Editor: R. G. Graf, rgraf@sunstroke.sdsu.edu

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