Avtomatika i Telemekhanika
RUS  ENG    JOURNALS   PEOPLE   ORGANISATIONS   CONFERENCES   SEMINARS   VIDEO LIBRARY   PACKAGE AMSBIB  
General information
Latest issue
Archive
Impact factor
Guidelines for authors
Submit a manuscript

Search papers
Search references

RSS
Latest issue
Current issues
Archive issues
What is RSS


Avtomat. i Telemekh.:
Year:
Volume:
Issue:
Page:
Find




Personal entry:
Login:
Password:
Save password
Enter
Forgotten password?
Register

Avtomatika i Telemekhanika, 1982, Issue 12, Pages 65–75 (Mi at5674)  
Adaptive Systems

On one way то design randomised algorithms

A. I. Kaplinskii, A. M. Pesin

Voronezh, Moscow
Full-text PDF (1480 kB)
Abstract: A probabilistic approach is developed to minimizing a scalar function of a vectorvalued argument. Convergence conditions of randomised algorithms and a way to incorporate prior information on the zome of global extremum of the goal function are described.

Received: 22.09.1981
Bibliographic databases:
Document Type: Article
UDC: 62-505:518.5
Language: Russian
Citation: A. I. Kaplinskii, A. M. Pesin, “On one way то design randomised algorithms”, Avtomat. i Telemekh., 1982, no. 12, 65–75; Autom. Remote Control, 43:12 (1982), 1551–1559
Citation in format AMSBIB
\Bibitem{KapPes82}
\by A.~I.~Kaplinskii, A.~M.~Pesin
\paper On one way то design randomised algorithms
\jour Avtomat. i Telemekh.
\yr 1982
\issue 12
\pages 65--75
\mathnet{http://mi.mathnet.ru/at5674}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=712018}
\zmath{https://zbmath.org/?q=an:0512.90086}
\transl
\jour Autom. Remote Control
\yr 1982
\vol 43
\issue 12
\pages 1551--1559
Linking options:
  • https://www.mathnet.ru/eng/at5674
  • https://www.mathnet.ru/eng/at/y1982/i12/p65
    • Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    		Avtomatika i Telemekhanika
     
      Contact us:
    		  Terms of Use  Registration to the website  Logotypes © Steklov Mathematical Institute RAS, 2024