Dissertations / Theses on the topic 'Cognitive algorithm'
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El-Nainay, Mustafa Y. "Island Genetic Algorithm-based Cognitive Networks." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/28297.
Full textPh. D.
TESHOME, ABIY TEREFE. "FPGA based Eigenvalue Detection Algorithm for Cognitive Radio." Thesis, Högskolan i Gävle, Radio Center Gävle, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-7855.
Full textFaizan, Shah Ali. "SDN based security using cognitive algorithm against DDOS." Master's thesis, University of Cape Town, 2018. http://hdl.handle.net/11427/29880.
Full textThomas, Ryan William. "Cognitive Networks." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/28319.
Full textPh. D.
Cabrejos, David. "Implementation of a channel selection algorithm using cognitive radios." Thesis, Wichita State University, 2011. http://hdl.handle.net/10057/3945.
Full textThesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering.
Gardiye, Punchihewage Anjana. "Advanced transceiver algorithm design for cognitive radio physical layer." Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/30557.
Full textRazavian, Adam A. "Cognitive Based Adaptive Path Planning Algorithm for Autonomous Robotic Vehicles." NSUWorks, 2004. http://nsuworks.nova.edu/gscis_etd/793.
Full textCalandra, Joséphine. "L'algorithmie cognitive et ses applications musicales." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUL148.
Full textThis thesis presents the formalization and development of a music analysis software called "Multiscale Oracle Representations For Organized Sounds" (MORFOS). This software aims to implement a multi-scale model of musical form based on Jean-Marc Chouvel's Cognitive Algorithm. The work in this thesis is part of the cognitive analysis in musicology, aimed at understanding the cognitive processes involved in listening to music. We study a hierarchical representation of music and explore the influence of this hierarchy on the organization of musical events over time and on musical comprehension. We formalize the concepts of material, object, and formal diagram, and introduce the Multi-scale Formal Diagram, which describes musical structure at different temporal scales and levels of analysis. This comprises three planes, which we introduce: form, structure, and organization. MORFOS has been implemented in Python and accepts audio, symbolic, and vector representations. This software features a modular architecture integrating different modules for audio processing, classification, and segmentation: we present different measures implemented in the form of a set of rules and discuss the constraints associated with the study of classification and segmentation based on an audio representation. We also introduce the notion of Agenda, which corresponds to the user's choice of a set of rules to represent a "listening" model for the software's analysis of a musical work. The thesis also explores the question of the complexity of the musical structure: we propose the expression of a cost associated with the description of the acquired musical object depending on its context, according to Kolmogorov's definition. We also seek to compare the behavior of MORFOS software with attentional phenomena and cognitive load during musical listening. An experiment designed to measure cognitive load during the musical segmentation task has thus been devised. This thesis also presents reflections on the visualization of multi-scale formal diagrams. To this end, we have developed an interface to make the software accessible to all users. Finally, examples of musical analyses carried out with MORFOS are presented, on a pop music database and a corpus of classical works
Chen, Ye. "Fuzzy Cognitive Maps: Learning Algorithms and Biomedical Applications." University of Cincinnati / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1423581705.
Full textNguyen, Diep Ngoc. "RESOURCE ALLOCATION STRATEGIES FOR COGNITIVE AND COOPERATIVE MIMO COMMUNICATIONS: ALGORITHM AND PROTOCOL DESIGN." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/292674.
Full textAkbari, Masoomeh. "Probabilistic Transitive Closure of Fuzzy Cognitive Maps: Algorithm Enhancement and an Application to Work-Integrated Learning." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/41401.
Full textMyers, Tracy S. (Tracy Scott). "Reasoning with incomplete probabilistic knowledge : the RIP algorithm for de Finetti's fundamental theorem of probability." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11885.
Full textReje, 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.
Full textSabih, Ann Faik. "Cognitive smart agents for optimising OpenFlow rules in software defined networks." Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/15743.
Full textfarooq, Muhammad, and Abdullah Aslam Raja. "Genetic Algorithm for Selecting Optimal Secondary Users to Collaborate in Spectrum sensing." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3418.
Full textCognitive Radio is an innovative technology that allows the secondary unlicensed users to share the spectrum with licensed primary users to utilize the spectrum. For maximum utilization of spectrum, in cognitive radio network spectrum sensing is an important issue. Cognitive user under extreme shadowing and channel fading can‟t sense the primary licensed user signal correctly and thus to improve the performance of spectrum sensing, collaboration between secondary unlicensed users is required. In collaborative spectrum sensing the observation of each secondary user is received by a base station acting as a central entity, where a final conclusion about the presence or absence of the primary user signal is made using a particular decision and fusion rule. Due to spatially correlated shadowing the collaborative spectrum sensing performance decreases, and thus optimum secondary users must be selected to, not only improve spectrum sensing performance but also lessen the processing overhead of the central entity. A particular situation is depicted in the project where according to some performance parameters, first those optimum secondary users that have enough spatial separation and high average received SNR are selected using Genetic Algorithm, and then collaboration among these optimum secondary users is done to evaluate the performance. The collaboration of optimal secondary user providing high probability of detection and low probability of false alarm, for sensing the spectrum is compared with the collaboration of all the available secondary users in that radio environment. At the end a conclusion has been made that collaboration of selected optimum secondary users provides better performance, then the collaboration of all the secondary users available.
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.
Full textCh?en, Chin-chang. "Using similarity ratings and the pathfinder algorithm for evaluating students' cognitive structures in Newtonian mechanics /." The Ohio State University, 1996. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487935573773081.
Full textFriend, Daniel. "Cognitive Networks: Foundations to Applications." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/26449.
Full textPh. D.
Elnourani, Mohamed. "COGNITIVE RADIO AND GAME THEORY : OVERVIEW AND SIMULATION." Thesis, Blekinge Tekniska Högskola, Avdelningen för signalbehandling, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5646.
Full textAtahary, Tanvir. "Acceleration of Cognitive Domain Ontologies." University of Dayton / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=dayton1460734067.
Full textFeng, Zhenhua. "Cross-Layer Optimization and Distributed Algorithm Design for Frequency-Agile Radio Networks." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/37207.
Full textPh. D.
Crossen, Samantha Lokelani. "Investigation of Variability in Cognitive State Assessment based on Electroencephalogram-derived Features." Wright State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=wright1316025164.
Full textBarnes, Simon Daniel. "Cognitive radio performance optimisation through spectrum availability prediction." Diss., University of Pretoria, 2012. http://hdl.handle.net/2263/25908.
Full textDissertation (MEng)--University of Pretoria, 2012.
Electrical, Electronic and Computer Engineering
unrestricted
Le, Bin. "Building a Cognitive Radio: From Architecture Definition to Prototype Implementation." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/28320.
Full textPh. D.
Devanarayana, Chamara. "Spectrum access in cognitive radio networks based on prediction and estimation." EURASIP Journal on Wireless Communications and Networking, 2011. http://hdl.handle.net/1993/31605.
Full textOctober 2016
Said, Laila Refiana. "The influences of cognitive, experiential and habitual factors in online games playing." University of Western Australia. Faculty of Economics and Commerce, 2006. http://theses.library.uwa.edu.au/adt-WU2006.0100.
Full textBlot, Guillaume. "Élaboration, parcours et automatisation de traces et savoirs numériques." Thesis, Paris 4, 2017. http://www.theses.fr/2017PA040089.
Full textHow access to knowledge can be impacted by Information Technology? In the earlier 2000s, communication tools caused a significant turn : media convergence, participative practices and massive data. In this way, free access to knowledge might tend to be democratized. People seem to regain spaces, reversing traditional top-down model, going from producer to consumer, for the benefit of an horizontal model based on collective intelligence. However, it should not automatically be assumed that this leads to a simple model reversing. Collective intelligence is subject to cognitive biases, leading to potential irrational situations. Formerly, those social mechanisms had limited consequences. Nowadays, digital knowledge are massive communicating spaces, giving birth to new access paths and new cleavages. Why this massive and open knowledge, is actually so selective? I propose to explore this paradox. Massive and constant tracking of traces and individuals hyper-connection, these two facts help organizational structures design, where social dynamics are digitalized in a complex way. These structures formalize human trajectories. On this basis, computer scientists set up prediction algorithms and recommender engines. This way, knowledge access is automatized. It can then be asked about people governance, in this context of infrastructure submission: recording traces, designing knowledge structure and automating algorithms
Song, Zhiguo. "Systèmes de numérisation hautes performances - Architectures robustes adaptées à la radio cognitive." Phd thesis, Supélec, 2010. http://tel.archives-ouvertes.fr/tel-00589826.
Full textKomali, Ramakant S. "Game-Theoretic Analysis of Topology Control." Diss., Virginia Tech, 2008. http://hdl.handle.net/10919/28358.
Full textPh. D.
Bri, Molinero Diana. "ESTUDIO DEL EFECTO DE FACTORES EXTERNOS SOBRE LAS REDES WLAN Y DISEÑO DE UN ALGORITMO COGNITIVO ENERGÉTICAMENTE EFICIENTE." Doctoral thesis, Universitat Politècnica de València, 2015. http://hdl.handle.net/10251/53450.
Full text[ES] Hoy en día existen muchos trabajos que analizan e intentan mejorar el rendimiento de las redes de área local inalámbricas desde diferentes perspectivas. Gran parte de estos trabajos se centran en aspectos de diseño, como son la distribución de frecuencias o la asignación de canales. Por lo tanto, como estos aspectos ya han sido ampliamente estudiados, los esfuerzos de esta tesis se han dirigido a estudiar otros factores que también podrían afectar a su rendimiento y que no han sido analizadas en profundidad todavía. El objetivo principal de esta tesis doctoral ha sido realizar un estudio detallado que analice el impacto de las condiciones meteorológicas sobre el rendimiento de las redes IEEE 802.11b/g. Para realizar este estudio, se han analizado dos escenarios reales con el fin de verificar los resultados y encontrar relaciones precisas. A partir de las conclusiones de estos análisis previos, el segundo objetivo ha sido diseñar un algoritmo cognitivo que, en base a las condiciones meteorológicas y a los parámetros de rendimiento de red, permita a las redes ajustar sus características de transmisión con el fin de superar tal impacto. Con el fin de llevar a cabo este estudio, primero fue necesario estudiar qué métodos estadísticos podían ser utilizados para extraer el nivel de correlación entre los parámetros de rendimiento de las redes y las condiciones meteorológicas del entorno. En segundo lugar, se tuvo que analizar qué parámetros de rendimiento de red se podían extraer de la red exterior de la UPV y seleccionarlos de acuerdo con el objetivo perseguido. A continuación, se definió el periodo de tiempo durante el cual se almacenarían los parámetros seleccionados de forma periódica. El siguiente paso fue seleccionar y almacenar las condiciones meteorológicas de una estación cercana durante el mismo periodo de tiempo. Finalmente, se realizó un preprocesado detallado con el fin de poner en orden todo el volumen de datos y se analizaron estadísticamente. Los resultados fueron exitosos, sin embargo aparecieron varios problemas por el hecho de estudiar una red real muy variable. Por lo tanto, se tuvo que desarrollar un escenario experimental con el fin de verificar los resultados. Para ello se diseñó y desarrolló un enlace exterior IEEE 802.11b/g punto a multipunto, y se analizó de nuevo el impacto de las condiciones meteorológicas. Se consideró un enlace multipunto para analizar también cómo influía el impacto del tiempo según la distancia y los diferentes esquemas de modulación. A partir de los resultados, se diseñó un algoritmo cognitivo energéticamente eficiente con el fin de reducir el impacto de los fenómenos meteorológicos en las redes IEEE 802.11b/g. Dicho algoritmo ha sido simulado y los resultados obtenidos han sido satisfactorios, tanto en términos de eficiencia energética como de rendimiento de la red. Para concluir, otro factor externo que se ha estudiado en esta tesis ha sido la tasa de absorción específica. Este parámetro está relacionado con una de las grandes preocupaciones actuales en cuanto a salud pública, ya que se utiliza para medir la exposición de los tejidos del cuerpo humano a los campos electromagnéticos. Obviamente, la absorción de señal por parte del cuerpo humano afecta a las redes y, por lo tanto, este parámetro se debería tener en cuenta a la hora de diseñar redes eficientes. Por esta razón se ha incluido en esta tesis doctoral.
[CAT] Actualment hi ha molts treballs que analitzen i intenten millorar el rendiment de les xarxes d'àrea local sense fils des de diferents perspectives. Gran part d'aquests treballs es focalitzen en aspectes de disseny, com són la distribució de freqüències o l'assignació de canals. Per tant, com aquests aspectes ja han sigut àmpliament estudiats, els esforços d'aquesta tesi doctoral s'han dirigit a estudiar altres factors que també podrien afectar al seu rendiment i que encara no han sigut analitzats amb profunditat. L'objectiu principal d'aquesta tesi doctoral ha sigut realitzar un estudi minuciós per analitzar l'impacte de les condicions meteorològiques sobre el rendiment de les xarxes IEEE 802.11b/g. Per a realitzar aquest estudi s'han analitzat dos escenaris reals per tal de verificar els resultats i trobar relacions precises. A partir de les conclusions d'aquests anàlisis previ, el següent objectiu ha sigut dissenyar un algoritme cognitiu que, en base a les condicions meteorològiques i als paràmetres de rendiment de la xarxa, permeti a les xarxes ajustar les seues característiques de transmissió per tal de superar tal impacte. Per tal de dur a terme aquest estudi, primer va ser necessari estudiar quins mètodes estadístics podien ser utilitzats per extraure el nivell de correlació entre els paràmetres de rendiment de les xarxes i les condicions meteorològiques de l'entorn. En segon lloc, es va haver d'analitzar quins paràmetres de rendiment es podien extraure de la xarxa exterior de la UPV i es van seleccionar d'acord a l'objectiu plantejat. A continuació, es va definir el període temporal al llarg del qual s'emmagatzemarien els paràmetres seleccionats de manera periòdica. El següent pas va ser seleccionar i emmagatzemar les condicions meteorològiques d'una estació propera durant el mateix període de temps. Finalment, es va realitzar un preprocessat per tal de posar en ordre tot el volum de dades i es van analitzar estadísticament. Els resultats van ser exitosos, però van aparèixer diversos problemes pel fet d'estudiar una xarxa real molt variable. Per tant, es va haver de desenvolupar un escenari experimental amb l'objectiu de verificar els resultats. Per aquesta raó es va dissenyar i implementar un enllaç exterior IEEE 802.11b/g punt a multipunt, i es va analitzar de nou l'impacte de les condicions meteorològiques. Es va considerar un enllaç multipunt per tal de d'analitzar també com influïa el impacte del temps segons la distància i els diferents esquemes de modulació. A partir d'aquests resultats, es va dissenyar un algoritme cognitiu energèticament eficient per tal de reduir l'impacte dels fenòmens meteorològics sobre les xarxes IEEE 802.11b/g. Aquest algoritme va ser simulat i els resultats obtinguts van ser satisfactoris, tant en termes d'eficiència energètica com de rendiment de la xarxa. va comprovar que la proposta aporta millores. Per concloure, un altre factor extern que s'ha estudiat en aquesta tesi doctoral ha sigut la taxa d'absorció específica. Aquest paràmetre està relacionat amb una de les preocupacions actuals pel que fa a la salut pública, ja que s'utilitza per a mesurar l'exposició dels teixits del cos humà als camps electromagnètics. Òbviament, aquesta absorció de la senyal afecta el rendiment de les xarxes i, per això, aquest paràmetre s'hauria de tenir en compte a l'hora d'implementar futures xarxes sense fils eficients. Per aquesta raó s'ha inclòs en aquesta tesi doctoral.
Bri Molinero, D. (2015). ESTUDIO DEL EFECTO DE FACTORES EXTERNOS SOBRE LAS REDES WLAN Y DISEÑO DE UN ALGORITMO COGNITIVO ENERGÉTICAMENTE EFICIENTE [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/53450
TESIS
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.
Full textPaula, Amanda Souza de. "Sistemas de sensoriamento espectral cooperativos." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/3/3142/tde-29122014-183230/.
Full textThis doctorate thesis deals with cooperative detection algorithms applied to the spectral sensing problem. The cooperative detection problem is approached under two different paradigms: centralized and distributed detection. In the first case, is considered that a fusion center responsible for detection decision is presented in the system. On the other hand, in the second case, is considered that the cognitive radios in the network exchange information among them. Concerning the centralized spectrum sensing system, the case in which the cognitive radios send only one decision bit (hard decision) to the fusion center and the case in which the detector send the statistic test (soft decision) are considered. Regarding the spectrum sensing system with distributed detection, the work analysis three different scenarios. In the first one, where the cognitive radios explore an a priori knowledge of the primary user signal and the channel between the primary user and the cognitive radio. In the second one, the cognitive radios use an a priori knowledge of only the primary user signal. And, in the las scenario, there is no a priori knowledge about the primary user signal. Besides the distributed detection problem, the thesis also presents a chapter dedicated to the estimation problem, which is directed related to the detection problem. This last issue is approached using adaptive algorithms derived from the classic adaptive filtering theory.
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.
Full textYhä tehokkaampien älykkäiden langattomien päätelaitteiden nopea lisääntyminen johtaa niukan radiospektrin yhä kiihtyvään käyttöön. Eräs menetelmä radiospektrin lisääntyvän kysynnän tyydyttämiseen on hyödyntää innovatiivista ja joustavaa resurssin käytönjakoa kuten spektrin jakamista. Spektrinjakamismalli mahdollistaa useiden käyttäjien ja/tai järjestelmien yhtäaikaisen käytön samalla taajuuskaistalla hyödyntämällä sovittua käytäntöä resurssien jakamisesta. Radiospektrin jakaminen on tänä päivänä yleisesti suositeltu toteuttamaan hyödyntämällä kognitiivista radioteknologiaa. Tässä työssä suunnittellaan ja toteutetaan kognitiivinen päätöksentekokone, joka jakaa radiospektriresursseja käyttäjille älykkäästi ja dynaamisesti. Kognitiivista päätöksentekokonetta radioresurssien jakamisessa hyödynnetään kahdessa skenaariossa. Ensimmäisessä skenaariossa radioverkolla on yksinomainen pääsy taajuuskaistalle, jonka käyttöä kognitiivinen päätöksentekokone säätelee joko hyväksymällä tai hylkäämällä verkkoon liittyviä käyttäjiä. Kognitiivinen päätöksentekokoneen päätökset perustuu algoritmiin, joka ottaa huomioon käyttäjien määritetyn tärkeyden ja käyttäjän vaatiman kaistanleveyden. Seuraavassa skenaariossa radioverkko voi oman yksinomaisen taajuuskaistan lisäksi hyödyntää opportunisesti toisen radioverkon taajuuskaistaa silloin, kun siellä ei ole liikennettä. Tätä skenaariota varten suunnitteltiin kognitiivinen päätöksentekokone, jolla on kaksi päätehtävää: 1) hyväksyä tai hylätä verkkoon liittyviä käyttäjiä edellämainitun tärkeysperusteisen algoritmin avulla; ja 2) jakaa käyttäjien liikennettä kahden tarjolla olevan verkon välillä samalla ottaen huomioon opportunistisen resurssin pääkäyttäjien liikenteen jaetulla taajuuskaistalla. Tässä työssä esitellään toteutettu kuormantasausalgoritmi, jonka suorituskykyä tarkastellaan erilaisissa pääkäyttäjien ja toissijaisien käyttäjien liikenneskenaarioissa. Simulaatiotulokset osoittavat, että esitellyn kuormanjakoalgoritmin hyödyntäminen kognitiivisessa päätöksentekokoneessa parantaa verkon keskimääräistä siirtonopeutta, sekä vähentää keskimääräistä käyttäjien hylkäysastetta verkossa. Algoritmimme parantaa opportunistisen taajuuskaistan käyttöastetta. Algoritmimme ottaa myös huomioon käyttäjille asetetut prioriteetit ja parantaa korkeampi prioriteettisten käyttäjien asemaa verkossa. Tämä tulee ilmi muun muassa korkeampi prioriteettisten käyttäjien pienemmässä hylkäysasteessa
Mariani, Andrea <1984>. "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.
Full textMariani, Andrea <1984>. "Spectrum Sensing Algorithms for Cognitive Radio Applications." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5615/.
Full textGad, Mahmoud M. "Connectivity-Aware Routing Algorithms for Cognitive Radio Networks." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/32353.
Full textTeguig, Djamel. "Cooperative Spectrum Sensing Algorithms For Cognitive Radio Networks." Doctoral thesis, Universite Libre de Bruxelles, 2015. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/219942.
Full textLe travail présenté dans cette thèse concerne l'une des techniques clés dans les fonctionnalités de la radio cognitive qui est la détection du spectre ainsi que la détection coopérative du spectre. La détection coopérative est couramment utilisée pour la lutte contre l’évanouissement du canal à fin d'améliorer les performances de la détection. Les performances de la détection coopérative en utilisant différentes règles de fusion ont été analysées. En raison sa simplicité, la détection du spectre par les testes d’adéquation a été étudiée pour les applications de la radio cognitive. Motivé par la caractéristique d’être indépendant de bruit, ces testes d’adéquation ont été utilisés pour la détection locale, pour la détection coopérative distribuée.
Doctorat en Sciences de l'ingénieur et technologie
info:eu-repo/semantics/nonPublished
Awe, Olusegun P. "Machine learning algorithms for cognitive radio wireless networks." Thesis, Loughborough University, 2015. https://dspace.lboro.ac.uk/2134/19609.
Full textLini, Sami. "L’anticipation et sa représentation dans les interfaces homme-système en aéronautique : L’anticipation et sa représentation dans les interfaces homme-système en aéronautique." Thesis, Bordeaux 1, 2013. http://www.theses.fr/2013BOR14843/document.
Full textCivil aviation pursues the objective of moving people or goods through the air with an optimal level of safety. For more than thirty years, despite a stricter and stricter regulatory framework and highly reliable automation, the ratio between performance and acceptable risk is not improving anymore.Human factors are a major action lever to break this glass floor. In the constrained context of aviation, designing tools aiming at assisting pilots’ cognition is thus a promising direction. Anticipation has been identified central in the process of cognitive resources management. In a human factors engineering approach, we undertook the design of an anticipation support tool involving pilots at each step of the development.From an activity analysis performed on the basis of in-cockpit recordings and interviews we constructed a model of the actual pilots’ activity during the descent and approach phases on Rio de Janeiro airport. The state of the art highlighted the key elements related to anticipation which could take benefit of a preliminary experiment. Experimental results brought together with our hypotheses about how anticipation works completed the requirements of the functional core of our anticipation support tool. A dynamic planning algorithm was then designed and implemented within ASAP (Anticipation Support for Aeronautical Planning), Thales Avionics’ proof of concept. 36 commercial pilots took part to its evaluation in a simulated environment
Hashmi, Ziaul Hasan. "Dynamic resource allocation for cognitive radio systems." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/961.
Full textEllis, Kevin Ph D. (Kevin M. )Massachusetts Institute of Technology. "Algorithms for learning to induce programs." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/130184.
Full textCataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 213-224).
The future of machine learning should have a knowledge representation that supports, at a minimum, several features: Expressivity, interpretability, the potential for reuse by both humans and machines, while also enabling sample-efficient generalization. Here we argue that programs-i.e., source code-are a knowledge representation which can contribute to the project of capturing these elements of intelligence. This research direction however requires new program synthesis algorithms which can induce programs solving a range of AI tasks. This program induction challenge confronts two primary obstacles: the space of all programs is infinite, so we need a strong inductive bias or prior to steer us toward the correct programs; and even if we have that prior, effectively searching through the vast combinatorial space of all programs is generally intractable. We introduce algorithms that learn to induce programs, with the goal of addressing these two primary obstacles. Focusing on case studies in vision, computational linguistics, and learning-to-learn, we develop an algorithmic toolkit for learning inductive biases over programs as well as learning to search for programs, drawing on probabilistic, neural, and symbolic methods. Together this toolkit suggests ways in which program induction can contribute to AI, and how we can use learning to improve program synthesis technologies.
by Kevin Ellis.
Ph. D. in Cognitive Science
Ph.D.inCognitiveScience Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences
Kit, Chun Yu. "Unsupervised lexical learning as inductive inference." Thesis, University of Sheffield, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340205.
Full textStuhlmüller, Andreas. "Modeling cognition with probabilistic programs : representations and algorithms." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/100860.
Full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 167-176).
This thesis develops probabilistic programming as a productive metaphor for understanding cognition, both with respect to mental representations and the manipulation of such representations. In the first half of the thesis, I demonstrate the representational power of probabilistic programs in the domains of concept learning and social reasoning. I provide examples of richly structured concepts, defined in terms of systems of relations, subparts, and recursive embeddings, that are naturally expressed as programs and show initial experimental evidence that they match human generalization patterns. I then proceed to models of reasoning about reasoning, a domain where the expressive power of probabilistic programs is necessary to formalize our intuitive domain understanding due to the fact that, unlike previous formalisms, probabilistic programs allow conditioning to be represented in a model, not just applied to a model. I illustrate this insight with programs that model nested reasoning in game theory, artificial intelligence, and linguistics. In the second half, I develop three inference algorithms with the dual intent of showing how to efficiently compute the marginal distributions defined by probabilistic programs, and providing building blocks for process-level accounts of human cognition. First, I describe a Dynamic Programming algorithm for computing the marginal distribution of discrete probabilistic programs by compiling to systems of equations and show that it can make inference in models of "reasoning about reasoning" tractable by merging and reusing subcomputations. Second, I introduce the setting of amortized inference and show how learning inverse models lets us leverage samples generated by other inference algorithms to compile probabilistic models into fast recognition functions. Third, I develop a generic approach to coarse-to-fine inference in probabilistic programs and provide evidence that it can speed up inference in models with large state spaces that have appropriate hierarchical structure. Finally, I substantiate the claim that probabilistic programming is a productive metaphor by outlining new research questions that have been opened up by this line of investigation.
by Andreas Stuhlmüller.
Ph. D.
Wang, Nan. "Threshold setting algorithms for spectrum sensing in cognitive radio networks." Thesis, Queen Mary, University of London, 2014. http://qmro.qmul.ac.uk/xmlui/handle/123456789/9064.
Full textAbdel-Rahman, Mohammad Jamal. "Robust Cognitive Algorithms For Fast-Varying Spectrum-Agile Wireless Networks." Diss., The University of Arizona, 2014. http://hdl.handle.net/10150/338872.
Full textBouzegzi, Abdelaziz. "Algorithmes de discrimination de signaux pour la radio cognitive." Paris, Télécom ParisTech, 2009. http://www.theses.fr/2009ENST0048.
Full textIn the context of cognitive radio it is a crucial task to distinguish blindly various wireless systems (e. G. , Wifi, Wimax, 3GPP/LTE, DVB-T) from each others. We focus on the OFDM based systems which differ from their subcarrier spacing used in OFDM modulation. One can thus carry out recognition algorithms based on the value of the subcarrier spacing. Standard approaches developed in the literature rely on the detection of the cyclic prefix which enables to exhibit the value of the used subcarrier spacing. Nevertheless, these approaches fail when either the cyclic prefix duration is small or the channel impulse response is almost as large as the cyclic prefix. Therefore, this thesis proposes new algorithms to estimate the parameters of OFDM modulated signal (especially the subcarrier spacing) relying on i) the normalized kurtosis, ii) the maximum-likelihood principle, iii) the matched filter, and iv) the second-order cyclostationary property. We have shown the strong robustness of proposed algorithms to short cyclic prefix, multipath channel, time offset, and frequency offset
Chandler, Benjamin. "Cognitive computing: algorithm design in the intersection of cognitive science and emerging computer architectures." Thesis, 2014. https://hdl.handle.net/2144/14318.
Full text"Low complexity distributed algorithm in MIMO cognitive radio networks." 2014. http://library.cuhk.edu.hk/record=b6116023.
Full text从优化的角度处理这种解耦问题,最常用的方法是原始分解法和对偶分解法。然而这两种方法都需要用戶之间有大量的消息传递,这对于频谱效率来说是有害的。在对偶分解法中,指向授权用戶的耦合干扰被一协调者估测(通常是授权用戶本身)。协调者需要在每次迭代中更新和广播参数给认知无线电用戶。对于原始分解法,算法同样需要一协调者进行收集认知无线电用戶的目标函数信息以此计算每个用戶的最优干扰约束上限。协调者同样需要更新和广播大量消息给认知无线电用戶。这种大量的信息计算和传递在分布式系统中是不理想的,问题在认知无线电网络显得格外严重。因为授权用戶不希望担任这样的协调者除非他的计算参与降到最低。
在此论文中,我们提出了几种新型的基于认知无线电网络的分布式算法。目的是最小化授权用戶和认知无线电用戶的消息传递。通过研究半定规划中的最优分割法,我们指出不影响最优性条件下授权用戶和认知无线电用戶的大量消息传递是可以避免的。我们又提出了在多输入多数出认知无线电网络中一种基于对偶分解的鲁捧干扰控制。在此论文中提出的低消息传递算法大大地提高了多用戶多输入多数认知无线电网络的实用性。
Cognitive radio (CR) is a promising solution to alleviate spectrum scarcity. In CR networks where mobile stations are equipped with multiple antennas, secondary users (SUs) can transmit at the same time as the primary users (PUs) by carefully controlling the interference through transmit beamforming, thus significantly enhancing the spectrum efficiency. In practical systems, it is desirable to have multiple SUs optimize their transmit beamforming vectors in a decentralized manner, and yet achieve an optimal system performance. In CR networks, the interference received by the PU is attributed to the transmission of all SUs. To facilitate distributed beamforming, the aggregate-interference constraint imposed by the PU must be decoupled, so that each individual SU knows the "fair share" of interference that is allowed to generate to the PU.
A commonly used technique for decoupling coupled constraintsin optimization problems is optimization decomposition, including dual and primal decompositions. Both the dual and primal decomposition methods require frequent message passing among users, which potentially offsets the spectrum benefit brought by cognitive radio techniques. Specifically, with dual decomposition, the aggregate interference generated to the PU must be measured by a coordinator,which is, naturally, the PU. The coordinator then updates and broadcasts the Lagrangian multiplier to all SUs. Likewise, the primal decomposition needs a coordinator, which can again be the PU, to gather the subgradient of the objective functions of each SUs for given interference partition. The coordinator then updates and broadcasts the permissible interference to all SUs. Whereas the large overhead incurred message computation and passing is undesirable in distributed systems, the problem is more acute in CR networks, because a typical PU would not be willing to take the coordinating role unless its involvement is minimized.
In this thesis, we propose several novel distributed optimization algorithms for CR networks with minimum message passing between the primary and secondary systems. By exploiting the theory of optimal partition (OP) for semi-definite programming (SDP), we show that most message passings between the primary and secondary systems can be eliminated without compromising the optimality of the solution. We also derive a robust interference control scheme based on the duality theory for MIMO CR network. The low message-passing distributed algorithms presented in this thesis greatly enhance the practicality of multiuser MIMO CR networks.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Yao, Leiyi.
Thesis (Ph.D.) Chinese University of Hong Kong, 2014.
Includes bibliographical references (leaves 114-123).
Abstracts also in Chinese.
Yen-LingChen and 陳妍伶. "Resource Allocation Algorithm for Distributed Wireless Cognitive Radio Network." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/54472515347834479746.
Full text國立成功大學
電腦與通信工程研究所
98
We consider the secondary users have to carry out a distributed network optimization through the exchange of information between each other without infrastructure support in a cognitive radio network. Therefore, we propose the cross-layer system model including physical layer, data link layer and network layer. The physical layer involves the control of transmission power and data link layer includes the channel assignment and time scheduling while the network layer involves the selection of the routing path. For this system model, we design an inner loop and an outer loop algorithm to solve the nonconvex problem and the mixed-integer programming problem. In the inner loop, we use the gradient method to achieve the functionality of the distributed system. In the outer loop, we implement two kinds of method to allocate the time slots and channel to solve the network maximum throughput problem heuristically. According our modeling, the proposed algorithm is an effective resource allocator implemented distributed wireless cognitive radio network.
Ke, Chang-Ting, and 柯長廷. "A Universal Channel Rendezvous Algorithm for Cognitive Radio Networks." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/39222518435996764501.
Full text國立清華大學
通訊工程研究所
102
In cognitive radio networks (CRNs), primary users (PUs) have the absolute priority to access the license channels. To efficiently utilize the spectrum, secondary users (SUs) can dynamically access the unused channels by channel hopping (CH) schemes. Most existing CH schemes focus on the symmetric model that assumes all SUs have the same available channel set. However, the asymmetric model, where SUs may have different available channels sets, is more critical in the real CRN environment. In this thesis, we propose a universal channel hopping algorithm called Triple-Double Matrix (TDM) that can guarantee rendezvous within shorter period than the previous works under the asymmetric model without any constraints on the available channels of each SU. According to our simulation results, TDM has better maximum conditional time-to-rendezvous (MCTTR) than previous works.