WO2006005665A3 - Method for reacting to changes in context by means of a neural network, and neural network used for reacting to changes in context - Google Patents

Method for reacting to changes in context by means of a neural network, and neural network used for reacting to changes in context Download PDF

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Publication number
WO2006005665A3
WO2006005665A3 PCT/EP2005/052859 EP2005052859W WO2006005665A3 WO 2006005665 A3 WO2006005665 A3 WO 2006005665A3 EP 2005052859 W EP2005052859 W EP 2005052859W WO 2006005665 A3 WO2006005665 A3 WO 2006005665A3
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WO
WIPO (PCT)
Prior art keywords
neural network
context
reacting
changes
piece
Prior art date
Application number
PCT/EP2005/052859
Other languages
German (de)
French (fr)
Other versions
WO2006005665A2 (en
Inventor
Gustavo Deco
Martin Stetter
Original Assignee
Siemens Ag
Gustavo Deco
Martin Stetter
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Application filed by Siemens Ag, Gustavo Deco, Martin Stetter filed Critical Siemens Ag
Publication of WO2006005665A2 publication Critical patent/WO2006005665A2/en
Publication of WO2006005665A3 publication Critical patent/WO2006005665A3/en

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks

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  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Computing Systems (AREA)
  • Biomedical Technology (AREA)
  • Biophysics (AREA)
  • Computational Linguistics (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Molecular Biology (AREA)
  • Artificial Intelligence (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Health & Medical Sciences (AREA)
  • Image Analysis (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

Disclosed is a method for reacting to changes in context by means of a neural network (1). According to said method, input data is fed to an input layer (10) of the neural network (1) while output data is retrieved from an output layer (30) of the neural network (1). Several models which predefine one respective copy of the input data to the output data are stored in the neural network (1), only one model being active at the same time. The following steps are then repeated: the neural network (1) copies a piece of fed input data (2) to a piece of output data (3). Said piece of output data (3) is then retrieved from the output layer (30). If the retrieved piece of output data (3) is incorrect in a current context for the fed piece of data (2), the neural network (1) receives an error feedback message (4), whereupon the neural network (1) activates another model.
PCT/EP2005/052859 2004-07-09 2005-06-21 Method for reacting to changes in context by means of a neural network, and neural network used for reacting to changes in context WO2006005665A2 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102004033391 2004-07-09
DE102004033391.2 2004-07-09

Publications (2)

Publication Number Publication Date
WO2006005665A2 WO2006005665A2 (en) 2006-01-19
WO2006005665A3 true WO2006005665A3 (en) 2006-12-07

Family

ID=35448080

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2005/052859 WO2006005665A2 (en) 2004-07-09 2005-06-21 Method for reacting to changes in context by means of a neural network, and neural network used for reacting to changes in context

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WO (1) WO2006005665A2 (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7577099B1 (en) * 2006-04-06 2009-08-18 At&T Corp. Method and apparatus for fault localization in a network
DE102007014650B3 (en) * 2007-03-27 2008-06-12 Siemens Ag Method for computerized processing of data detected in sensor network, involves establishing data in sensor node by multiple adjacent sensor nodes, by which each sensor node is assigned to neural area

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5155801A (en) * 1990-10-09 1992-10-13 Hughes Aircraft Company Clustered neural networks
US5239594A (en) * 1991-02-12 1993-08-24 Mitsubishi Denki Kabushiki Kaisha Self-organizing pattern classification neural network system
EP0574951A2 (en) * 1992-06-18 1993-12-22 Seiko Epson Corporation Speech recognition system
EP1073012A1 (en) * 1999-07-30 2001-01-31 Eidgenössische Technische Hochschule Zürich A method and circuit for neuron-like processing of data
EP1327959A2 (en) * 2002-01-11 2003-07-16 EADS Deutschland GmbH Neural network for modelling a physical system and method for building the neural network

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5155801A (en) * 1990-10-09 1992-10-13 Hughes Aircraft Company Clustered neural networks
US5239594A (en) * 1991-02-12 1993-08-24 Mitsubishi Denki Kabushiki Kaisha Self-organizing pattern classification neural network system
EP0574951A2 (en) * 1992-06-18 1993-12-22 Seiko Epson Corporation Speech recognition system
EP1073012A1 (en) * 1999-07-30 2001-01-31 Eidgenössische Technische Hochschule Zürich A method and circuit for neuron-like processing of data
EP1327959A2 (en) * 2002-01-11 2003-07-16 EADS Deutschland GmbH Neural network for modelling a physical system and method for building the neural network

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
SZABO MIRUNA ET AL: "COORPERATION AND BIASED COMPETITION MODEL CAN EXPLAIN ATTENTIANAL FILTERING IN THE PREFRONTAL CORTEX", EUROPEAN JOURNAL OF NEUROSCIENCE, OXFORD UNIVERSITY PRESS, GB, vol. 19, no. 6, April 2004 (2004-04-01), pages 1969 - 1977, XP008069137, ISSN: 0953-816X *

Also Published As

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WO2006005665A2 (en) 2006-01-19

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