Bidirectional Associative Memory Function by Kumar Somesh (7 results)
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Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Paperback. Condition: Brand New. 104 pages. 8.66x5.91x0.24 inches. In Stock.
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Taschenbuch. Condition: Neu. Bidirectional Associative Memory for Function Approximation | Somesh Kumar (u. a.) | Taschenbuch | 104 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659865602 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de…| Anbieter: preigu.
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paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Language: English
Published by LAP LAMBERT Academic Publishing Mrz 2016 2016
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Capturing the implicit relationship between the input and output patterns such that when test input pattern is given, the pattern corresponding to the output of the generalized system is retrieved, is called the problem of pattern m…apping. Since the very objective of pattern mapping problem is to capture the implied function and mimic its behavior and therefore it is also termed as function approximation problem. Alternatively, function approximation is the task of learning or constructing a function that generates approximately the same outputs from input vectors as the process being modeled, based on available training data. The approximate mapping system should give an output which is fairly close to the values of the real function for inputs close to the current input used during learning. 104 pp. Englisch.
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Seller: moluna, Greven, Germanymoluna
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kumar SomeshDr Somesh Kumar presently spearheads the IT department in NIET, Greater Noida, India. He has completed his MCA in 2000, ME (CS&E) in 2006, PhD (CS) in 2011. Since 2000, he has been in teachi…ng profession and is involved i.
Language: English
Published by LAP LAMBERT Academic Publishing Mär 2016 2016
- Softcover
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Seller: buchversandmimpf2000, Emtmannsberg, Germanybuchversandmimpf2000
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Capturing the implicit relationship between the input and output patterns such that when test input pattern is given, the pattern corresponding to the output of the generalized system is retrieved, is called the problem of pattern mappi…ng. Since the very objective of pattern mapping problem is to capture the implied function and mimic its behavior and therefore it is also termed as function approximation problem. Alternatively, function approximation is the task of learning or constructing a function that generates approximately the same outputs from input vectors as the process being modeled, based on available training data. The approximate mapping system should give an output which is fairly close to the values of the real function for inputs close to the current input used during learning.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 104 pp. Englisch.
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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Capturing the implicit relationship between the input and output patterns such that when test input pattern is given, the pattern corresponding to the output of the generalized system is retrieved, is called the problem of pattern mappin…g. Since the very objective of pattern mapping problem is to capture the implied function and mimic its behavior and therefore it is also termed as function approximation problem. Alternatively, function approximation is the task of learning or constructing a function that generates approximately the same outputs from input vectors as the process being modeled, based on available training data. The approximate mapping system should give an output which is fairly close to the values of the real function for inputs close to the current input used during learning.
