Relevant bibliographies by topics / Algorithme cognitif

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Algorithme cognitif'

Author: Grafiati
Published: 25 May 2024
Last updated: 31 July 2025

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Journal articles on the topic "Algorithme cognitif"

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Jalenques, I. "SMP – Diagnostic et traitement personnalisés : un paradigme d’avenir dans les troubles schizophréniques." European Psychiatry 29, S3 (2014): 591–92. http://dx.doi.org/10.1016/j.eurpsy.2014.09.315.

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L’objectif d’un diagnostic et d’un programme thérapeutique personnalisés pour chaque patient souffrant de troubles schizophréniques n’est aujourd’hui qu’en partie atteint. Cette session fait le point sur les dernières avancées et celles à venir concernant les outils et stratégies diagnostiques ainsi que les thérapeutiques médicamenteuses et cognitives.Si l’hétérogénéité des tableaux cliniques répondant aux critères diagnostiques de schizophrénie est une constatation bien établie, on ne sait pas encore clairement ce que recouvre cette hétérogénéité : maladies distinctes ou variabilité d’express
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Abramova, I. "Methodology of the study block "algorithmic model" at the kindergarten and primary school." Bulletin of Science and Practice 4, no. 5 (2018): 689–99. https://doi.org/10.5281/zenodo.1246721.

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The formation of students’ skills of teaching computer literacy in the preschool educational institution (DOW) and in primary school (NSH) is a necessary component in the formation of professional competence of future teachers. The article deals with the methods of studying the content block “Algorithmic models”, the elements of which are aimed at fulfilling the following tasks: the formation of students’ ability to apply modern information techniques and technologies to ensure the quality of the educational process in DOW and NSH; the formation of a system of methodolo
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Foley, J. M., M. J. Wright, A. L. Gooding, et al. "Operationalization of the updated diagnostic algorithm for classifying HIV-related cognitive impairment and dementia." International Psychogeriatrics 23, no. 5 (2010): 835–43. http://dx.doi.org/10.1017/s1041610210002085.

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ABSTRACTBackground: This study applies the updated HIV-Associated Neurocognitive Disorders (HAND) diagnostic algorithm.Methods: Participants were 210 HIV-infected-adults, classified using proposed HAND criteria: HIV-Associated Dementia (HAD), Mild Neurocognitive Disorder (MND), Asymptomatic Neurocognitive Impairment (ANI).Results: The algorithm yielded: normal = 32.8%, ANI = 21.4%, MND = 34.3%, and HAD = 11.4%. Normal participants performed superior to HAND-defined participants on cognition, and HAD participants performed more poorly on global cognition and executive functioning. Two distinct
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Lee, Won Hee. "The Choice of Machine Learning Algorithms Impacts the Association between Brain-Predicted Age Difference and Cognitive Function." Mathematics 11, no. 5 (2023): 1229. http://dx.doi.org/10.3390/math11051229.

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Machine learning has been increasingly applied to neuroimaging data to compute personalized estimates of the biological age of an individual’s brain (brain age). The difference between an individual’s brain-predicted age and their chronological age (brainPAD) is used as a biomarker of brain aging and disease, but the potential contribution of different machine learning algorithms used for brain age prediction to the association between brainPAD and cognitive function has not been investigated yet. Here, we applied seven commonly used algorithms to the same multimodal brain imaging data (struct
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Dangi, Siddharth, Amy L. Orsborn, Helene G. Moorman, and Jose M. Carmena. "Design and Analysis of Closed-Loop Decoder Adaptation Algorithms for Brain-Machine Interfaces." Neural Computation 25, no. 7 (2013): 1693–731. http://dx.doi.org/10.1162/neco_a_00460.

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Closed-loop decoder adaptation (CLDA) is an emerging paradigm for achieving rapid performance improvements in online brain-machine interface (BMI) operation. Designing an effective CLDA algorithm requires making multiple important decisions, including choosing the timescale of adaptation, selecting which decoder parameters to adapt, crafting the corresponding update rules, and designing CLDA parameters. These design choices, combined with the specific settings of CLDA parameters, will directly affect the algorithm's ability to make decoder parameters converge to values that optimize performanc
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Grosse-Wentrup, Moritz, Akshey Kumar, Anja Meunier, and Manuel Zimmer. "Neuro-cognitive multilevel causal modeling: A framework that bridges the explanatory gap between neuronal activity and cognition." PLOS Computational Biology 20, no. 12 (2024): e1012674. https://doi.org/10.1371/journal.pcbi.1012674.

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Explaining how neuronal activity gives rise to cognition arguably remains the most significant challenge in cognitive neuroscience. We introduce neuro-cognitive multilevel causal modeling (NC-MCM), a framework that bridges the explanatory gap between neuronal activity and cognition by construing cognitive states as (behaviorally and dynamically) causally consistent abstractions of neuronal states. Multilevel causal modeling allows us to interchangeably reason about the neuronal- and cognitive causes of behavior while maintaining a physicalist (in contrast to a strong dualist) position. We intr
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Zhao, Lu, and Mingyue Zhou. "A Robust Power Allocation Algorithm for Cognitive Radio Networks Based on Hybrid PSO." Sensors 22, no. 18 (2022): 6796. http://dx.doi.org/10.3390/s22186796.

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The use of a cognitive radio power allocation algorithm is an effective method to improve spectral utilization. However, there are three problems with traditional cognitive radio power allocation algorithms: (1) based on the ideal channel model analysis, channel fluctuation is not considered; (2) they do not consider fairness among cognitive users; and (3) some algorithms are complex and locating the optimal power allocation scheme is not an easy task. For the above problems, this study establishes a robust model which adds the cognitive user transmission rate variance constraint to solve the
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Zhang, Chudi, Yunqi Song, Rundong Jiang, Jun Hu, and Shiyou Xu. "A Cognitive Electronic Jamming Decision-Making Method Based on Q-Learning and Ant Colony Fusion Algorithm." Remote Sensing 15, no. 12 (2023): 3108. http://dx.doi.org/10.3390/rs15123108.

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In order to improve the efficiency and adaptability of cognitive radar jamming decision-making, a fusion algorithm (Ant-QL) based on ant colony and Q-Learning is proposed in this paper. The algorithm does not rely on a priori information and enhances adaptability through real-time interactions between the jammer and the target radar. At the same time, it can be applied to single jammer and multiple jammer countermeasure scenarios with high jamming effects. First, traditional Q-Learning and DQN algorithms are discussed, and a radar jamming decision-making model is built for the simulation verif
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N. Sirhan, Najem, and Manel Martinez-Ramon. "Cognitive Radio Resource Scheduling using Multi-Agent Q-Learning for LTE." International journal of Computer Networks & Communications 14, no. 02 (2022): 77–95. http://dx.doi.org/10.5121/ijcnc.2022.14205.

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In this paper, we propose, implement, and test two novel downlink LTE scheduling algorithms. The implementation and testing of these algorithms were in Matlab, and they are based on the use of Reinforcement Learning (RL), more specifically, the Q-learning technique for scheduling two types of users. The first algorithm is called a Collaborative scheduling algorithm, and the second algorithm is called a Competitive scheduling algorithm. The first type of the scheduled users is the Primary Users (PUs), and they are the licensed subscribers that pay for their service. The second type of the sched
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Rostami, Soheil, Sajad Alabadi, Soheir Noori, Hayder Ahmed Shihab, Kamran Arshad, and Predrag Rapajic. "Spectrum Assignment Algorithm for Cognitive Machine-to-Machine Networks." Mobile Information Systems 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/3282505.

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A novel aggregation-based spectrum assignment algorithm for Cognitive Machine-To-Machine (CM2M) networks is proposed. The introduced algorithm takes practical constraints including interference to the Licensed Users (LUs), co-channel interference (CCI) among CM2M devices, and Maximum Aggregation Span (MAS) into consideration. Simulation results show clearly that the proposed algorithm outperforms State-Of-The-Art (SOTA) algorithms in terms of spectrum utilisation and network capacity. Furthermore, the convergence analysis of the proposed algorithm verifies its high convergence rate.
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Dissertations / Theses on the topic "Algorithme cognitif"

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Calandra, Joséphine. "L'algorithmie cognitive et ses applications musicales." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUL148.

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Cette thèse présente la formalisation et le développement d’un logiciel d'analyse musicale appelé "Multiscale Oracle Representations For Organized Sounds" (MORFOS). Ce logiciel vise à mettre en œuvre un modèle multi-échelle de la forme musicale basé sur l’Algorithme Cognitif de Jean-Marc Chouvel. Les travaux de cette thèse s'inscrivent dans la continuité de l'analyse cognitive en musicologie, visant à comprendre les processus cognitifs qui interviennent lors de l'écoute musicale. Nous étudions une représentation hiérarchisée de la musique et explorons l’influence de cette hiérarchisation dans
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Li, Jun. "Genetic Granular Cognitive Fuzzy Neural Networks and Human Brains for Comparative Cognition." Digital Archive @ GSU, 2005. http://digitalarchive.gsu.edu/cs_theses/7.

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In this thesis, Genetic Granular Cognitive Fuzzy Neural Networks (GGCFNN), combining genetic algorithms (GA) and granular cognitive fuzzy neural networks (GCFNN), is proposed for pattern recognition problems. According to cognitive patterns, biological neural networks in the human brain can recognize different patterns. Since GA and neural networks represent two learning methods based on biological science, it is indispensable and valuable to investigate how biological neural networks and artificial neural networks recognize different patterns. The new GGCFNN, based on granular computing, soft
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Ginhac, Dominique. "Adéquation Algorithme architecture : Aspects logiciels, matériels et cognitifs." Habilitation à diriger des recherches, Université de Bourgogne, 2008. http://tel.archives-ouvertes.fr/tel-00646480.

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Les travaux présentés dans le cadre de cette Habilitation à Diriger des Recherches s'inscrivent principalement dans la problématique dite d'" Adéquation Algorithme Architecture ". Ils ont pour objectif commun la mise en œuvre de systèmes matériels et logiciels dédiés à la vision artificielle à fortes contraintes temporelles. Ils se focalisent sur différents aspects cruciaux tels que l'acquisition d'images par des capteurs dédiés, le développement et la programmation d'architectures optimisées de traitement des images et l'implantation d'algorithmes de traitement du signal et d'images en temps
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El-Nainay, Mustafa Y. "Island Genetic Algorithm-based Cognitive Networks." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/28297.

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The heterogeneity and complexity of modern communication networks demands coupling network nodes with intelligence to perceive and adapt to different network conditions autonomously. Cognitive Networking is an emerging networking research area that aims to achieve this goal by applying distributed reasoning and learning across the protocol stack and throughout the network. Various cognitive node and cognitive network architectures with different levels of maturity have been proposed in the literature. All of them adopt the idea of coupling network devices with sensors to sense network conditio
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Butterfield, Aaron S. "Using Synthetic Cognits and The Combined Cumulative Squared Deviation as Tools to Quantify the Performance of Cognitive Radar Algorithms." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1461242979.

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Béler, Cédrick. "Modélisation générique d'un retour d'expérience cognitif : application à la prévention des risques." Phd thesis, Toulouse, INPT, 2008. http://oatao.univ-toulouse.fr/7249/1/beler.pdf.

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Nous avons défini dans cette thèse une architecture logicielle générique permettant de réaliser des applications de retour d'expérience cognitif. Ces derniers intègrent une formalisation de l'analyse experte et sont une alternative aux Systèmes à Bases de Connaissance. Les applications sont opérationnalisées à partir de la définition du modèle de l'expérience qui est basé sur une structure objet simple couplée avec le modèle des croyances transférables pour prendre en compte les intertitudes. Nous avons développé des algorithmes génériques de recherche adaptés à la formalisation retenue de l'e
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Mäkeläinen, M. (Marko). "Algorithms for opportunistic load balancing cognitive engine." Master's thesis, University of Oulu, 2013. http://urn.fi/URN:NBN:fi:oulu-201303011071.

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Due to the increasing use of more and more powerful smart devices demands on the scarce radio spectrum are becoming more intense. One way to cope with increasing demands on radio spectrum is to apply innovative and flexible authorization schemes like spectrum sharing. Under the spectrum sharing paradigm, multiple users and/or systems are authorized to utilize the same spectrum band in a defined sharing agreement. A technology that is generally recommended for the implementation of spectrum sharing is called cognitive radio (CR). In this thesis, we design and implement a cognitive engine (CE) t
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Mariani, Andrea <1984&gt. "Spectrum Sensing Algorithms for Cognitive Radio Applications." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5615/2/Mariani_Andrea_SpectrumSensingforCognitiveRadio.pdf.

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Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission. In the present work, we study different spectrum sensing al
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Mariani, Andrea <1984&gt. "Spectrum Sensing Algorithms for Cognitive Radio Applications." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5615/.

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Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission. In the present work, we study different spectrum sensing al
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Reje, Franzén Fanny, and Saga Gardelin. "Hide and seek with algorithm : En intervjustudie av cosplay-kreatörers "folk" teorier i förhållande till TikToks algoritm." Thesis, Linnéuniversitetet, Institutionen för medier och journalistik (MJ), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-104833.

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This essay aims to study the relationship between cosplay content creators and TikTok’s algorithm. To study this relationship the essay will conduct a qualitative semi-structured interviews with creators from the cosplay community on TikTok. Since the rise of digital plattforms the media and the role of producer as well as consumer has changed drastically. TikTok has been growing rapidly in popularity since its entry on the market, and by 2020 it had 500 million active users. Since many of today's digital platforms have consumer produced content, the consumer of today has taken on a mixed role
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Books on the topic "Algorithme cognitif"

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

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

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

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

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Ross, Deming, Ilin Roman, and SpringerLink (Online service), eds. Emotional Cognitive Neural Algorithms with Engineering Applications: Dynamic Logic: FromVague to Crisp. Springer-Verlag Berlin Heidelberg, 2011.

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(Project), COST Action 2102, euCognition (Project), and COST Action 2102 and euCognition International School (2008 : Vietri sul Mare, Italy), eds. 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. Springer, 2009.

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

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

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

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Book chapters on the topic "Algorithme cognitif"

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Hausser, Roland. "Algorithm." In Computational Cognition. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37499-9_2.

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Poursanidis, Miltiadis, Patrick Link, Jochen Schmid, and Uwe Teicher. "Incorporating Shape Knowledge into Regression Models." In Cognitive Technologies. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-83097-6_7.

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Abstract Informed learning is an emerging field in Machine Learning that aims at compensating for insufficient data with prior knowledge. Shape knowledge covers many types of prior knowledge concerning the relationship of a function’s output with respect to input variables, for example, monotonicity, convexity, etc. This shape knowledge—when formalized into algebraic inequalities (shape constraints)—can then be incorporated into the training of regression models via a constrained optimization problem. The defined shape-constrained regression problem is, mathematically speaking, a semi-infinite
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Frühwirth, Thom, and Slim Abdennadher. "Algorithm = Logic + Control." In Cognitive Technologies. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-05138-2_2.

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Kaur, Kiranjit, and Vijay Laxmi. "A Novel Method of Data Partitioning Using Genetic Algorithm Work Load Driven Approach Utilizing Machine Learning." In Cognitive Computing in Human Cognition. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-48118-6_5.

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Der, Ralf, and Georg Martius. "Algorithmic Implementation." In Cognitive Systems Monographs. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20253-7_15.

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Kaindl, H. "Tree Searching Algorithms." In Computers, Chess, and Cognition. Springer New York, 1990. http://dx.doi.org/10.1007/978-1-4613-9080-0_8.

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Leiser, David, and Christiane Gillièron. "The Extraction Algorithm beneath the Basic Algorithm." In Cognitive Science and Genetic Epistemology. Springer US, 1990. http://dx.doi.org/10.1007/978-1-4684-5649-3_5.

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Fetzer, James H. "Mental Algorithms." In Computers and Cognition: Why Minds are not Machines. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-010-0973-7_5.

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Conrardy, Céline, Roland de Guio, and Bruno Zuber. "Facetwise Study of Modelling Activities in the Algorithm for Inventive Problem Solving ARIZ and Evolutionary Algorithms." In Design Computing and Cognition ’10. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0510-4_11.

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Palestro, James J., Per B. Sederberg, Adam F. Osth, Trisha Van Zandt, and Brandon M. Turner. "Likelihood-Free Algorithms." In Likelihood-Free Methods for Cognitive Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-72425-6_2.

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Conference papers on the topic "Algorithme cognitif"

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Tan, Zhengtao, Jimin Bao, Zhuangzhuang He, and Dacao Zhang. "Logit Adjustment for Imbalanced Cognitive Diagnosis." In 2025 4th Asia Conference on Algorithms, Computing and Machine Learning (CACML). IEEE, 2025. https://doi.org/10.1109/cacml64929.2025.11010969.

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Bhardwaj, Ritu, and Ashwani kush. "Review on Localization Algorithm in Underwater Sensor Network." In International Conference on Cognitive & Cloud Computing. SCITEPRESS - Science and Technology Publications, 2024. https://doi.org/10.5220/0013343100004646.

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Carpenter, Steven, Xinming Yu, Melih Altun, James Graham, J. Jim Zhu, and Janusz Starzyk. "Vision Guided Motion Control of a Biomimetic Quadruped Robot: RoboCat." In ASME 2011 International Mechanical Engineering Congress and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/imece2011-63805.

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This paper presents the vision system and visual processing for a biomimetic elastic cable-driven quadruped robot—RoboCat. The paper is geared towards selection of appropriate visual servoing techniques for RoboCat such as vision algorithms, high-level cognition algorithms, software architecture and hardware implementation. The system uses two video cameras for stereo vision data acquisition and a SUMIT-ism form factor embedded computer for vision data processing. The vision system employs a color based target recognition algorithm, a neural network based shape recognition algorithm and a Colo
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STRAT, Vasile. "The Trustworthiness of AI Algorithms and the Simulator Bias in Trading." In The International Conference on Economics and Social Sciences. Editura ASE, 2024. http://dx.doi.org/10.24818/icess/2024/022.

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The application of AI technology is changing dramatically investment decisions in the financial and banking industry. Neural networks (NN) are a special type of machine learning algorithm employed in training trading robots. They might be associated with advanced analysis of the specific software simulators used fundamentally in algorithm training and testing to alleviate risk in the trading activities. Our research focuses on a couple of key aspects: a methodical literature review using Natural Language Processing (NLP) tools, to delve into major themes directing to the efforts of understandi
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Huang, Shan, Haiyan Wang, Chengqi Xue, and Shuang Xia. "Icon Similarity Algorithm Based on Skeleton Comparison." In Intelligent Human Systems Integration (IHSI 2022) Integrating People and Intelligent Systems. AHFE International, 2022. http://dx.doi.org/10.54941/ahfe100963.

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Icon plays a crucial role in infographics, which additionally carries essential functions in the human-computer graphical user interface (GUI). However, too similar icon is easy to trigger confusion in the process of using. In this paper, we explored the use of the cognitive rules from global to local based on the theory of topological perception and built a computational discrimination tool from the human perception to describe similarity. Screening out icons that are too similar is the primary purpose of this research to avoid errors in use. We utilized the skeleton algorithm to extract the
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Amanna, Ashwin, Matthew J. Price, Soumava Bera, Manik Gadhiok, and Jeffrey H. Reed. "Cognitive Engine Architecture for Railway Communications." In ASME 2010 Rail Transportation Division Fall Technical Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/rtdf2010-42011.

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This paper discusses a railway specific cognitive radio that builds upon software defined radio (SDR) platforms to adapt the radio based situational awareness. Cognitive Radio incorporates artificial intelligence based algorithms with reconfigurable software-defined radios that enable automatic adjustments of the radio to improve performance and overcome obstacles the radio may confront in the field (i.e. environmental/man-made interference, occupying the same channel as a user with higher priority, etc.). This paper describes the Railway Cognitive Radio (Rail-CR) architecture and illustrates
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Farahani, Hojjatollah, Peter Watson, Timea Bezan, et al. "PsAIchology: An Intelligent Direction in Psychological Sciences." In Proceedings TIЕ 2024. University of Kragujevac, Faculty of Technical Sciences, Čačak, 2024. http://dx.doi.org/10.46793/tie24.060f.

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The intersection of machine learning (ML) and cognition is often referred to as ‘artificial intelligence’, whereas the intersection of psychology and ML is a term we would like to coin as ‘Artificial Psychology’ or “PsAIchology”. The main purpose of this paper is to introduce three commonly used machine learning algorithms for mind research along with their R codes. This paper aims not only to introduce these methods for analyzing data but also tries to provide the answers for questions that may arise for a mind researcher including a) how to choose which algorithm needs to be used for a given
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Gilg, Marc, Yaser Yousef, and Pascal Lorenz. "Using Image Processing Algorithms for Energy Efficient Routing Algorithm in Sensor Networks." In 2009 Computation World: Future Computing, Service Computation, Cognitive, Adaptive, Content, Patterns (COMPUTATIONWORLD). IEEE, 2009. http://dx.doi.org/10.1109/computationworld.2009.98.

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Guo, Yan, and Ning Li. "Cognitive beamforming algorithm." In 2011 International Conference on Electrical and Control Engineering (ICECE). IEEE, 2011. http://dx.doi.org/10.1109/iceceng.2011.6057249.

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Saidala, Ravi Kumar, and Nagaraju Devarakonda. "The tornadogenesis optimization algorithm." In 2017 IEEE 16th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC). IEEE, 2017. http://dx.doi.org/10.1109/icci-cc.2017.8109777.

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Reports on the topic "Algorithme cognitif"

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Pasupuleti, Murali Krishna. Quantum Cognition: Modeling Decision-Making with Quantum Theory. National Education Services, 2025. https://doi.org/10.62311/nesx/rrvi225.

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Abstract Quantum cognition applies quantum probability theory and mathematical principles from quantum mechanics to model human decision-making, reasoning, and cognitive processes beyond the constraints of classical probability models. Traditional decision theories, such as expected utility theory and Bayesian inference, struggle to explain context-dependent reasoning, preference reversals, order effects, and cognitive biases observed in human behavior. By incorporating superposition, interference, and entanglement, quantum cognitive models offer a probabilistic framework that better accounts
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Perlovsky, Leonid I. Cognitive Algorithms for Signal Processing. Defense Technical Information Center, 2011. http://dx.doi.org/10.21236/ada546287.

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Anandkumar, Animashree, Nithin Michael, Ao K. Tang, and Ananthram Swami. Distributed Algorithms for Learning and Cognitive Medium Access with Logarithmic Regret. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada524660.

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Oleksiuk, Vasyl P., and Olesia R. Oleksiuk. Exploring the potential of augmented reality for teaching school computer science. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4404.

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The article analyzes the phenomenon of augmented reality (AR) in education. AR is a new technology that complements the real world with the help of computer data. Such content is tied to specific locations or activities. Over the last few years, AR applications have become available on mobile devices. AR becomes available in the media (news, entertainment, sports). It is starting to enter other areas of life (such as e-commerce, travel, marketing). But education has the biggest impact on AR. Based on the analysis of scientific publications, the authors explored the possibilities of using augme
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Osadchyi, Viacheslav V., Hanna B. Varina, Kateryna P. Osadcha, Olesia O. Prokofieva, Olha V. Kovalova, and Arnold E. Kiv. Features of implementation of modern AR technologies in the process of psychological and pedagogical support of children with autism spectrum disorders. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4413.

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The article deals with the actual issue of the specificity and algorithm of the introduction of innovative AR technologies in the process of psychological and pedagogical support of children with autism spectrum disorders (ASD). An innovative element of theoretical and methodological analysis of the problem and empirical research is the detection of vectors of a constructive combination of traditional psycho-correctional and psycho-diagnostic approaches with modern AR technologies. The analysis of publications on the role and possibilities of using AR technologies in the process of support chi
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Petrovych, Olha B., Alla P. Vinnichuk, Viktor P. Krupka, Iryna A. Zelenenka, and Andrei V. Voznyak. The usage of augmented reality technologies in professional training of future teachers of Ukrainian language and literature. CEUR Workshop Proceedings, 2021. http://dx.doi.org/10.31812/123456789/4635.

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The article deals with the peculiarities of creation and practical application of augmented reality (AR) technologies for the organization of students-philologists’ individual and group work in studying the discipline “Methodic of teaching literature”. The relevance of the introduction of AR technologies for the future teachers-philologists’ readiness formation to the professional activity is substantiated. Analysis of the scientific sources suggested that the professional training process requires the modernization of teaching methods, and the usage of information and communication technologi
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Osadchyi, Viacheslav V., Hanna B. Varina, Kateryna P. Osadcha, et al. The use of augmented reality technologies in the development of emotional intelligence of future specialists of socionomic professions under the conditions of adaptive learning. CEUR Workshop Proceedings, 2020. http://dx.doi.org/10.31812/123456789/4633.

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In modern conditions, innovative augmented reality technologies are actively developing, which are widespread in many areas of human activity. Introduction of advanced developments in the process of professional training of future specialists of socionomic professions in the conditions of adaptive training, contributes to the implementation of the principles of a personalized approach and increase the overall level of competitiveness. The relevant scientific article is devoted to the theoretical and empirical analysis result of conducting a psychodiagnostic study on an innovative computer comp
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