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Books on the topic 'Algorithme cognitif'

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Author: Grafiati
Published: 25 May 2024

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1

Foster, C. L. Algorithms, abstraction, and implementation: Levels of detail in cognitive science. London: Academic Press, 1992.

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2

Perlovsky, Leonid, Ross Deming, and Roman Ilin. Emotional Cognitive Neural Algorithms with Engineering Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22830-8.

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3

Robbins, Trevor W., Peter M. Todd, and Thomas Trenholm Hills. Cognitive search: Evolution, algorithms, and the brain. Cambridge, MA: MIT Press, 2012.

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4

Esposito, Anna, Amir Hussain, Maria Marinaro, and Raffaele Martone, eds. Multimodal Signals: Cognitive and Algorithmic Issues. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00525-1.

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5

Pinna, Simone. Extended Cognition and the Dynamics of Algorithmic Skills. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51841-1.

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6

Talvitie, Vesa. Freudian unconscious and cognitive neuroscience: From unconscious fantasies to neural algorithms. London: Karnac, 2009.

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7

Talvitie, Vesa. Freudian unconscious and cognitive neuroscience: From unconscious fantasies to neural algorithms. London: Karnac, 2009.

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8

Perlovsky, Leonid. Emotional Cognitive Neural Algorithms with Engineering Applications: Dynamic Logic: FromVague to Crisp. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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9

Günthner, W. Enhancing cognitive assistance systems with inertial measurement units. Berlin: Springer, 2008.

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10

Esposito, Anna. Multimodal signals: Cognitive and algorithmic issues : COST Action 2102 and euCognition International School Vietri Sul Mare, Italy, April 21-26, 2008 : revised selected and invited papers. Berlin: Springer, 2009.

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11

Dohler, Mischa. Cooperative communications: Hardware, channel & PHY. Chichester, West Sussex, U.K: Wiley, 2010.

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12

Cvetkov, Viktor. Basics of complexity theory. ru: INFRA-M Academic Publishing LLC., 2024. http://dx.doi.org/10.12737/2110856.

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Abstract:
The monograph reveals the basics of complexity theory and methods for assessing complexity. The concept of complexity consideration is based on the analysis of complexity as a common attribute in processes and systems. The monograph describes the main methods for assessing different types of complexity. The concept of considering complexity in this monograph is also based on the fact that complexity is a comparative characteristic. It is given on a relative scale of difficulty. Therefore, complexity must be defined on a relative scale of “simplicity-complexity.” This concept motivates the consideration and analysis of the concept of “simplicity” as a complement to the concept of “complexity”. These concepts set the scale of complexity. The monograph provides a comparative analysis of the related concepts of simplicity and complexity. Three methods for assessing complexity are described: expert assessment of complexity, assessment of complexity using mathematical metrics, comparative assessment of complexity based on the theory of comparative analysis. The monograph contains a taxonomy of the main types of complexity. The content of the main types of complexity is revealed in detail: descriptive complexity, system complexity, modeling complexity, computational complexity. algorithmic complexity, deterministic complexity. Specific cognitive difficulties are described in detail. For cognitive complexity, special assessment methods are used. An interpretation of the concept of cognitive filter is given. Complexity is associated with the concept of complex systems. In most monographs on complex systems, the complexity aspect has not been considered or is viewed in a simplified manner. This monograph examines complexity as a characteristic of complex systems and the basis for their classification. Emergence is described as a characteristic of the complexity of systems and complex processes. The monograph contains a taxonomy of complex systems with characteristics of the complexity of different systems. Complex data systems have been explored. An analysis of organizational complex systems is given. Various types of complex ergatic systems have been described. An analysis of complex technical systems is given. Self-developing complex systems are described. autopoiesis of a complex organizational and technical system has been studied as a principle of systems development. Cyber-physical systems are described as an example of the development of complex systems. The monograph is intended for specialists in the field of computer science, systems analysis, artificial intelligence and philosophy of information.
13

Dahlstedt, Palle. Action and Perception. Edited by Roger T. Dean and Alex McLean. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780190226992.013.4.

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Abstract:
While computational models of human music making are a hot research topic, the human side of computer-based music making has been largely neglected. What are our cognitive processes like when we create musical algorithms, and when we compose and perform with them? Musical human–algorithm interaction involves embodied action, perception and interaction, and some kind of internalization of the algorithms in the performer’s mind. How does the cognitive relate to the physical here? Departing from the age-old mind–body problem, this chapter tries to answer these questions and review relevant research, drawing from a number of related fields, such as musical cognition, cognition and psychology of programming, embodied performance, and neurological research, as well as from the author’s personal experience as an artist working in the field.
14

Grenander, Ulf. Calculus of Ideas: A Mathematical Study of Human Thought. World Scientific Publishing Co Pte Ltd, 2012.

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15

Tranter, William H., Tamal Bose, Alireza Babaei, and Barathram Ramkumar. Blind Signal Classification Algorithms for Cognitive Radios. Springer, 2020.

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16

Robbins, Trevor W., Peter M. Todd, Julia Lupp, and Thomas T. Hills. Cognitive Search: Evolution, Algorithms, and the Brain. MIT Press, 2012.

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17

Robbins, Trevor W., Peter M. Todd, and Thomas T. Hills. Cognitive Search: Evolution, Algorithms, and the Brain. MIT Press, 2019.

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18

Tranter, William H., Tamal Bose, Alireza Babaei, Barathram Ramkumar, and Munawwar Mahmud Sohul. Blind Signal Classification Algorithms for Cognitive Radios. Springer London, Limited, 2020.

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19

Papageorgiou, Elpiniki. Fuzzy Cognitive Maps for Applied Sciences and Engineering. Springer, 2013.

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20

Hosseini, Seyyed Abed, ed. Cognitive and Computational Neuroscience - Principles, Algorithms and Applications. InTech, 2018. http://dx.doi.org/10.5772/intechopen.68377.

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21

Saha, Apu, and Mrinmoy Majumder. Application of Cognitive Algorithms in Optimal Power Allocation. Independently Published, 2017.

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22

Dhope, Tanuja S. Cognitive Radio Networks Optimization with Spectrum Sensing Algorithms. River Publishers, 2022.

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23

Dhope, Tanuja S. Cognitive Radio Networks Optimization with Spectrum Sensing Algorithms. River Publishers, 2015.

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24

Dhope, Tanuja S. Cognitive Radio Networks Optimization with Spectrum Sensing Algorithms. River Publishers, 2022.

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25

Dhope, Tanuja S. Cognitive Radio Networks Optimization with Spectrum Sensing Algorithms. River Publishers, 2015.

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26

Barrios, Luis. Modeling of Complex Processes and Systems: An Integrated Approach from Measurement to Cognition. Springer London, Limited, 2020.

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27

Barrios, Luis. Modeling of Complex Processes and Systems: An Integrated Approach from Measurement to Cognition. Springer London, Limited, 2020.

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28

Kumar, Sunil, and Fei Hu. Multimedia over Cognitive Radio Networks: Algorithms, Protocols, and Experiments. Taylor & Francis Group, 2014.

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29

Kumar, Sunil, and Fei Hu. Multimedia over Cognitive Radio Networks: Algorithms, Protocols, and Experiments. Taylor & Francis Group, 2016.

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30

Kumar, Sunil, and Fei Hu. Multimedia over Cognitive Radio Networks: Algorithms, Protocols, and Experiments. Taylor & Francis Group, 2014.

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31

Kumar, Sunil, and Fei Hu. Multimedia over Cognitive Radio Networks: Algorithms, Protocols, and Experiments. Taylor & Francis Group, 2014.

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32

Pinna, Simone. Extended Cognition and the Dynamics of Algorithmic Skills. Springer, 2017.

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33

Pinna, Simone. Extended Cognition and the Dynamics of Algorithmic Skills. Springer, 2018.

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34

Papageorgiou, Elpiniki I. Fuzzy Cognitive Maps for Applied Sciences and Engineering: From Fundamentals to Extensions and Learning Algorithms. Springer, 2016.

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35

Papageorgiou, Elpiniki I. Fuzzy Cognitive Maps for Applied Sciences and Engineering: From Fundamentals to Extensions and Learning Algorithms. Springer, 2013.

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36

Talvitie, Vesa. Freudian Unconscious and Cognitive Neuroscience: From Unconscious Fantasies to Neural Algorithms. Taylor & Francis Group, 2018.

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37

Shapiro, Lawrence A. Embodied Cognition. Edited by Eric Margolis, Richard Samuels, and Stephen P. Stich. Oxford University Press, 2012. http://dx.doi.org/10.1093/oxfordhb/9780195309799.013.0006.

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Abstract:
The article explains the history, core concepts, methodological practices, and future prospects of embodied cognition. Cognitivism treats cognition, including perception, as a constructive process in which computational operations transform a static representation into a goal state. Cognition begins with an input representation so that the psychological subject can be conceived as a passive receptor of information. The cognitivist's primary concern is the discovery of algorithms by which inputs such as those representing shading are transformed into outputs such as those representing shape. The experimental methods need to provide an environment that isolates the stimuli that will be relevant to an investigation of the mental process of interest. Gibson's theory of perception explains that information in the optic array sufficed to specify opportunities for action, thus providing observers with an ability to perceive. Gibson explains that perception is the detection of information that, with no further embellishment, suffices to specify features of an observer's world. The active observer could, by collecting and sampling the wealth of information contained within the optic array, know its world in terms relative to its needs. Embodied cognition researchers conceive of themselves as offering a new framework for studying the mind.
38

Lytras, Miltiadis D., Kwok Tai Chui, Ryan Wen Liu, and Mingbo Zhao. Innovations, Algorithms, and Applications in Cognitive Informatics and Natural Intelligence. IGI Global, 2020.

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39

Lytras, Miltiadis D., Kwok Tai Chui, Ryan Wen Liu, and Mingbo Zhao. Innovations, Algorithms, and Applications in Cognitive Informatics and Natural Intelligence. IGI Global, 2020.

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40

Lytras, Miltiadis D., Kwok Tai Chui, Ryan Wen Liu, and Mingbo Zhao. Innovations, Algorithms, and Applications in Cognitive Informatics and Natural Intelligence. IGI Global, 2020.

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41

Lytras, Miltiadis D., Kwok Tai Chui, Ryan Wen Liu, and Mingbo Zhao. Innovations, Algorithms, and Applications in Cognitive Informatics and Natural Intelligence. IGI Global, 2020.

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42

Lytras, Miltiadis D., Kwok Tai Chui, Ryan Wen Liu, and Mingbo Zhao. Innovations, Algorithms, and Applications in Cognitive Informatics and Natural Intelligence. IGI Global, 2020.

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43

Durmus, Murat. COGNITIVE BIASES - a Brief Overview of over 160 Cognitive Biases : + Bonus Chapter: Algorithmic Bias. Lulu Press, Inc., 2022.

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44

Kumar, Sandeep, Rohit Raja, Shilpa Rani, and Shrikant Tiwari. Cognitive Behavior and Human Computer Interaction Based on Machine Learning Algorithms. Wiley & Sons, Incorporated, John, 2021.

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45

Talvitie, Vesa. Freudian Unconscious and Cognitive Neuroscience: From Unconscious Fantasies to Neural Algorithms. Taylor & Francis Group, 2018.

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46

Kumar, Sandeep, Rohit Raja, Shilpa Rani, and Shrikant Tiwari. Cognitive Behavior and Human Computer Interaction Based on Machine Learning Algorithms. Wiley & Sons, Incorporated, John, 2021.

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47

Talvitie, Vesa. Freudian Unconscious and Cognitive Neuroscience: From Unconscious Fantasies to Neural Algorithms. Karnac Books, 2009.

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48

Kumar, Sandeep, Rohit Raja, Shilpa Rani, and Shrikant Tiwari. Cognitive Behavior and Human Computer Interaction Based on Machine Learning Algorithms. Wiley & Sons, Incorporated, John, 2021.

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49

Kumar, Sandeep, Rohit Raja, Shilpa Rani, and Shrikant Tiwari. Cognitive Behavior and Human Computer Interaction Based on Machine Learning Algorithm. Wiley & Sons, Limited, John, 2022.

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50

Kumar, Sandeep, Rohit Raja, Shrikant Tiwari, and Shilpa Rani, eds. Cognitive Behavior and Human Computer Interaction Based on Machine Learning Algorithm. Wiley, 2021. http://dx.doi.org/10.1002/9781119792109.

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