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Encyclopedia > Andrei Andreevich Markov

Andrey Andreyevich Markov (Андрей Андреевич Марков) (June 14, 1856 N.S. _ July 20, 1922) was a Russian mathematician.


Markov was born in Ryazan. He studied at St. Petersburg University in 1874 under the tutelage of Chebyshev. In 1886, he became a member of the St. Petersburg Academy of Science. He is best known for his work on theory of stochastic processes. His research later became known as Markov chains.


See also

References

  • A. A. Markov. "Rasprostranenie zakona bol'shih chisel na velichiny, zavisyaschie drug ot druga". Izvestiya Fiziko-matematicheskogo obschestva pri Kazanskom universitete, 2-ya seriya, tom 15, pp 135-156, 1906.
  • A.A. Markov. "Extension of the limit theorems of probability theory to a sum of variables connected in a chain". reprinted in Appendix B of: R. Howard. Dynamic Probabilistic Systems, volume 1: Markov Chains. John Wiley and Sons, 1971.

External links

  • Andrei Andreyevich Markov (http://www-gap.dcs.st-and.ac.uk/~history/Mathematicians/Markov.html) (at the MacTutor History of Mathematics archive)
  • The Life and Work of AA Markov (http://mac03-204ha.math.ncsu.edu/~langville/naoumov.pdf)
  • Andrey Andreevich Markov (1903-1979) (http://logic.pdmi.ras.ru/Markov/) (page at the Steklov Institute of Mathematics at St.Petersburg)







  Results from FactBites:
 
Andrey Markov Summary (1675 words)
Markov involved himself in anti-Czarist, liberal politics and protested Czar Nicholas II (1868-1918) refusal to elect writer Maxim Gorky (1868-1936) to the St. Petersburg Academy in 1902.
Markov then stayed on at St. Petersburg to work for his master's degree, which was granted in 1880, then for his doctorate, which he received in 1884.
Andrey (Andrei) Andreyevich Markov (Russian: Андрей Андреевич Марков) (June 14, 1856 N.S. July 20, 1922) was a Russian mathematician.
Markov chain (268 words)
A Markov chain (named in honor of Andrei Andreevich Markov) is a stochastic process with what is called the Markov property[?], of which there is a "discrete-time" version and a "continuous-time" version.
Markov chains are used to model various processes in queuing theory and statistics, and can also be used as a signal model in entropy coding techniques such as arithmetic coding.
Markov chains also have many biological applications, particularly population processes, which are useful in modelling processes that are (at least) analogous to biological populations.
  More results at FactBites »


 
 

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