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Tesis sobre el tema "Neural network adaptation"

Autor: Grafiati
Publicado: 25 de mayo de 2024
Última modificación: 31 de julio de 2025

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1

Donati, Lorenzo. "Domain Adaptation through Deep Neural Networks for Health Informatics." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/14888/.

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The PreventIT project is an EU Horizon 2020 project aimed at preventing early functional decline at younger old age. The analysis of causal links between risk factors and functional decline has been made possible by the cooperation of several research institutes' studies. However, since each research institute collects and delivers different kinds of data in different formats, so far the analysis has been assisted by expert geriatricians whose role is to detect the best candidates among hundreds of fields and offer a semantic interpretation of the values. This manual data harmonization approac
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2

Haskey, Stephen. "A modified One-Class-One-Network ANN architecture for dynamic phoneme adaptation." Thesis, Loughborough University, 1998. https://dspace.lboro.ac.uk/2134/12099.

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As computers begin to pervade aspects of our everyday lives, so the problem of communication from man-to-machine becomes increasingly evident. In recent years, there has been a concerted interest in speech recognition offering a user to communicate freely with a machine. However, this deceptively simple means for exchanging information is in fact extremely complex. A single utterance can contain a wealth of varied information concerning the speaker's gender, age, dialect and mood. Numerous subtle differences such as intonation, rhythm and stress further add to the complexity, increasing the va
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3

Grativol, Ribeiro Lucas. "Neural network compression in the context of federated learning and edge devices." Electronic Thesis or Diss., Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2024. http://www.theses.fr/2024IMTA0444.

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L’apprentissage fédéré est un cadre d’apprentissage automatique collaboratif et décentralisé, motivé par des préoccupations croissantes concernant la confidentialité desdonnées. En transférant l’entraînement des modèles vers des noeuds locaux et en conservant les données sur place, il favorise une approche plus respectueuse de la vie privée. Toutefois, cette méthode impose un surcoût en termes de communication et de calcul à ceux qui l’adoptent. Dans ce manuscrit, nous examinons les principaux défis de l’apprentissage fédéré et proposons des solutions visant à augumenter l’efficacité tout en r
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4

Wen, Tsung-Hsien. "Recurrent neural network language generation for dialogue systems." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/275648.

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Language is the principal medium for ideas, while dialogue is the most natural and effective way for humans to interact with and access information from machines. Natural language generation (NLG) is a critical component of spoken dialogue and it has a significant impact on usability and perceived quality. Many commonly used NLG systems employ rules and heuristics, which tend to generate inflexible and stylised responses without the natural variation of human language. However, the frequent repetition of identical output forms can quickly make dialogue become tedious for most real-world users.
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5

Gangireddy, Siva Reddy. "Recurrent neural network language models for automatic speech recognition." Thesis, University of Edinburgh, 2017. http://hdl.handle.net/1842/28990.

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The goal of this thesis is to advance the use of recurrent neural network language models (RNNLMs) for large vocabulary continuous speech recognition (LVCSR). RNNLMs are currently state-of-the-art and shown to consistently reduce the word error rates (WERs) of LVCSR tasks when compared to other language models. In this thesis we propose various advances to RNNLMs. The advances are: improved learning procedures for RNNLMs, enhancing the context, and adaptation of RNNLMs. We learned better parameters by a novel pre-training approach and enhanced the context using prosody and syntactic features.
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6

Tomashenko, Natalia. "Speaker adaptation of deep neural network acoustic models using Gaussian mixture model framework in automatic speech recognition systems." Thesis, Le Mans, 2017. http://www.theses.fr/2017LEMA1040/document.

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Les différences entre conditions d'apprentissage et conditions de test peuvent considérablement dégrader la qualité des transcriptions produites par un système de reconnaissance automatique de la parole (RAP). L'adaptation est un moyen efficace pour réduire l'inadéquation entre les modèles du système et les données liées à un locuteur ou un canal acoustique particulier. Il existe deux types dominants de modèles acoustiques utilisés en RAP : les modèles de mélanges gaussiens (GMM) et les réseaux de neurones profonds (DNN). L'approche par modèles de Markov cachés (HMM) combinés à des GMM (GMM-HM
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7

Buttar, Sarpreet Singh. "Applying Artificial Neural Networks to Reduce the Adaptation Space in Self-Adaptive Systems : an exploratory work." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-87117.

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Self-adaptive systems have limited time to adjust their configurations whenever their adaptation goals, i.e., quality requirements, are violated due to some runtime uncertainties. Within the available time, they need to analyze their adaptation space, i.e., a set of configurations, to find the best adaptation option, i.e., configuration, that can achieve their adaptation goals. Existing formal analysis approaches find the best adaptation option by analyzing the entire adaptation space. However, exhaustive analysis requires time and resources and is therefore only efficient when the adaptation
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8

Palapelas, Kantola Philip. "Extreme Quantile Estimation of Downlink Radio Channel Quality." Thesis, Linköpings universitet, Artificiell intelligens och integrerade datorsystem, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177657.

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The application area of Fifth Generation New Radio (5G-NR) called Ultra-Reliable and Low-Latency Communication (URLLC) requires a reliability, the probability of receiving and decoding a data packet correctly, of 1 - 10^5. For this requirement to be fulfilled in a resource-efficient manner, it is necessary to have a good estimation of extremely low quan- tiles of the channel quality distribution, so that appropriate resources can be distributed to users of the network system.  This study proposes and evaluates two methods for estimating extreme quantiles of the downlink channel quality distrib
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9

Fic, Miloslav. "Adaptace parametrů ve fuzzy systémech." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-221163.

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This Master’s thesis deals with adaptation of fuzzy system parameters with main aim on artificial neural network. Current knowledge of methods connecting fuzzy systems and artificial neural networks is discussed in the search part of this work. The search in Student’s works is discussed either. Chapter focused on methods application deals with classifying ability verification of the chosen fuzzy-neural network with Kohonen learning algorithm. Later the model of fuzzy system with parameters adaptation based on fuzzyneural network with Kohonen learning algorithm is shown.
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10

Vu, Hien Duc. "Adaptation des méthodes d'apprentissage automatique pour la détection de défauts d'arc électriques." Electronic Thesis or Diss., Université de Lorraine, 2019. http://docnum.univ-lorraine.fr/ulprive/DDOC_T_2019_0152_VU.pdf.

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La détection des arcs électriques se produisant dans un réseau électrique par des approches d’apprentissage représente le cœur des travaux exposés dans cette thèse. Le problème a d’abord été vu comme la classification de séries temporelles à taille fixe en deux classes: normal et défaut. Cette première partie s’appuie sur les travaux de la littérature où les algorithmes de détection sont organisés principalement sur une étape de transformation des signaux acquis sur le réseau, suivie d’une étape d’extraction de caractéristiques descriptives et enfin d’une étape de décision. L’approche multicri
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11

Ainapure, Abhijeet Narhar. "Application and Performance Enhancement of Intelligent Cross-Domain Fault Diagnosis in Rotating Machinery." University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1623164772153736.

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12

Goudarzi, Alireza. "On the Effect of Topology on Learning and Generalization in Random Automata Networks." PDXScholar, 2011. https://pdxscholar.library.pdx.edu/open_access_etds/193.

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We extend the study of learning and generalization in feed forward Boolean networks to random Boolean networks (RBNs). We explore the relationship between the learning capability and the network topology, the system size, the training sample size, and the complexity of the computational tasks. We show experimentally that there exists a critical connectivity Kc that improves the generalization and adaptation in networks. In addition, we show that in finite size networks, the critical K is a power-law function of the system size N and the fraction of inputs used during the training. We explain w
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13

Ahn, Euijoon. "Unsupervised Deep Feature Learning for Medical Image Analysis." Thesis, University of Sydney, 2020. https://hdl.handle.net/2123/23002.

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The availability of annotated image datasets and recent advances in supervised deep learning methods are enabling the end-to-end derivation of representative image features that can impact a variety of image analysis problems. These supervised methods use prior knowledge derived from labelled training data and approaches, for example, convolutional neural networks (CNNs) have produced impressive results in natural (photographic) image classification. CNNs learn image features in a hierarchical fashion. Each deeper layer of the network learns a representation of the image data that is higher le
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14

Lin, Fanqing. "Flow Adaptive Video Object Segmentation." BYU ScholarsArchive, 2018. https://scholarsarchive.byu.edu/etd/7067.

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We tackle the task of semi-supervised video object segmentation, i.e, pixel-level object classification of the images in video sequences using very limited ground truth training data of its corresponding video. Recently introduced online adaptation of convolutional neural networks for video object segmentation (OnAVOS) has achieved good results by pretraining the network, fine-tuning on the first frame and training the network at test time using its approximate prediction as newly obtained ground truth. We propose Flow Adaptive Video Object Segmentation (FAVOS) that refines the generated ad
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15

Cherif, Wael. "Adaptation de contexte basée sur la Qualité d'Expérience dans les réseaux Internet du Futur." Phd thesis, Université Rennes 1, 2013. http://tel.archives-ouvertes.fr/tel-00940287.

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Pour avoir une idée sur la qualité du réseau, la majorité des acteurs concernés (opérateurs réseau, fournisseurs de service) se basent sur la Qualité de Service (Quality of Service). Cette mesure a montré des limites et beaucoup d'efforts ont été déployés pour mettre en place une nouvelle métrique qui reflète, de façon plus précise, la qualité du service offert. Cette mesure s'appelle la qualité d'expérience (Quality of Experience). La qualité d'expérience reflète la satisfaction de l'utilisateur par rapport au service qu'il utilise. Aujourd'hui, évaluer la qualité d'expérience est devenu prim
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16

MAGGIOLO, LUCA. "Deep Learning and Advanced Statistical Methods for Domain Adaptation and Classification of Remote Sensing Images". Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1070050.

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In the recent years, remote sensing has faced a huge evolution. The constantly growing availability of remote sensing data has opened up new opportunities and laid the foundations for many new challenges. The continuous space missions and new constellations of satellites allow in fact more and more frequent acquisitions, at increasingly higher spatial resolutions, and at an almost total coverage of the globe. The availability of such an huge amount data has highlighted the need for automatic techniques capable of processing the data and exploiting all the available information. Meanwhile, the
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17

UNO, Yoji, Kouichi TAJI, Masashi OTANI, 洋二 宇野, 宏一 田地 та 将司 大谷. "逆ダイナミックスモデルを用いた反復制御による運動適応". 電子情報通信学会, 2012. https://search.ieice.org/.

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18

VOLPI, RICCARDO. "Regularization, Adaptation and Generalization of Neural Networks." Doctoral thesis, Università degli studi di Genova, 2019. http://hdl.handle.net/11567/940909.

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The ability to generalize to unseen data is one of the fundamental, desired properties in a learning system. This thesis reports dierent research eorts in improving the generalization properties of machine learning systems at dierent levels, focusing on neural networks for computer vision tasks. First, a novel regularization method is presented, Curriculum Dropout. It combines Curriculum Learning and Dropout, and shows better regularization eects than the original algorithm in a variety of tasks, without requiring substantially any additional implementation eorts. While regularization
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19

Narmack, Kirilll. "Dynamic Speed Adaptation for Curves using Machine Learning." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233545.

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The vehicles of tomorrow will be more sophisticated, intelligent and safe than the vehicles of today. The future is leaning towards fully autonomous vehicles. This degree project provides a data driven solution for a speed adaptation system that can be used to compute a vehicle speed for curves, suitable for the underlying driving style of the driver, road properties and weather conditions. A speed adaptation system for curves aims to compute a vehicle speed suitable for curves that can be used in Advanced Driver Assistance Systems (ADAS) or in Autonomous Driving (AD) applications. This degree
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20

Silva, Joelson Coelho da. "Uma proposta de controle neural adaptativo para a navegação de veículos autônomos." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 1999. http://hdl.handle.net/10183/18631.

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Os equipamentos robóticos foram inicialmente criados para atuarem em ambientes industriais fechados. Com o passar do tempo, melhorias foram conquistadas. Atualmente, não se limitam mais à realização de tarefas simples e repetitivas em locais especialmente preparados. Novos equipamentos, capazes de atuarem em ambientes abertos e de realizarem as mais diversas atividades, estão sendo desenvolvidos. Para tanto, é necessário que seus sistemas de controle realizem uma efetiva interação com o mundo onde estão inseridos. Fazem-se necessários, portanto, novos sistemas controladores com capacidade de u
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21

Le, Lan Gaël. "Analyse en locuteurs de collections de documents multimédia." Thesis, Le Mans, 2017. http://www.theses.fr/2017LEMA1020/document.

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La segmentation et regroupement en locuteurs (SRL) de collection cherche à répondre à la question « qui parle quand ? » dans une collection de documents multimédia. C’est un prérequis indispensable à l’indexation des contenus audiovisuels. La tâche de SRL consiste d’abord à segmenter chaque document en locuteurs, avant de les regrouper à l'échelle de la collection. Le but est de positionner des labels anonymes identifiant les locuteurs, y compris ceux apparaissant dans plusieurs documents, sans connaître à l'avance ni leur identité ni leur nombre. La difficulté posée par le regroupement en loc
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22

Morvan, Ludivine. "Prédiction de la progression du myélome multiple par imagerie TEP : Adaptation des forêts de survie aléatoires et de réseaux de neurones convolutionnels." Thesis, Ecole centrale de Nantes, 2021. http://www.theses.fr/2021ECDN0045.

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L’objectif de ces travaux est de fournir un modèle permettant la prédiction de la survie et l’identification de biomarqueurs dans le contexte du myélome multiple (MM) à l’aide de l’imagerie TEP (Tomographie à émission de positons) et de données cliniques. Cette thèse fut divisée en deux parties : La première permet d’obtenir un modèle basé sur les forêts de survie aléatoires (RSF). La seconde est basée sur l’adaptation de l’apprentissage profond à la survie et à nos données. Les contributions principales sont les suivantes : 1) Production d’un modèle basé sur les RSF et les images TEP permetta
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23

Roy, Subhankar. "Learning to Adapt Neural Networks Across Visual Domains." Doctoral thesis, Università degli studi di Trento, 2022. http://hdl.handle.net/11572/354343.

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In the field of machine learning (ML) a very commonly encountered problem is the lack of generalizability of learnt classification functions when subjected to new samples that are not representative of the training distribution. The discrepancy between the training (a.k.a. source) and test (a.k.a.target) distributions are caused by several latent factors such as change in appearance, illumination, viewpoints and so on, which is also popularly known as domain-shift. In order to make a classifier cope with such domain-shifts, a sub-field in machine learning called domain adaptation (DA) has emer
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24

Haverinen, J. (Janne). "Adaptation through a Stochastic Evolutionary Neuron Migration Process." Doctoral thesis, University of Oulu, 2004. http://urn.fi/urn:isbn:9514273079.

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Abstract Artificial Life is an interdisciplinary scientific and engineering enterprise investigating the fundamental properties of living systems through the simulation and synthesis of life-like processes in artificial media. One of the avenues of investigation is autonomous robots and agents. Mimicking of the growth and adaptation of a biological neural circuit in an artificial medium is a challenging task owing to our limited knowledge of the complex process taking place in a living organism. By combining several developmental mechanisms, including the chemical, mechanical, genetic, and el
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25

Duroselle, Raphaël. "Robustesse au canal des systèmes de reconnaissance de la langue." Electronic Thesis or Diss., Université de Lorraine, 2021. http://www.theses.fr/2021LORR0250.

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La tâche de reconnaissance de la langue consiste à prédire la langue utilisée dans un énoncé audio contenant de la parole. Depuis 2017, les systèmes atteignant les meilleures performances reposent sur un réseau de neurones profond, entraîné à identifier la langue pour l’ensemble du segment. Ces systèmes subissent une perte de performance lorsqu’ils sont exposés à une variation des canaux de transmission entre les données d’entraînement et d’évaluation. L’objet de cette thèse est l’exploration d’approches permettant de limiter cette perte de performance dans le cadre de ces nouveaux systèmes. N
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26

Swietojanski, Paweł. "Learning representations for speech recognition using artificial neural networks." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/22835.

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Learning representations is a central challenge in machine learning. For speech recognition, we are interested in learning robust representations that are stable across different acoustic environments, recording equipment and irrelevant inter– and intra– speaker variabilities. This thesis is concerned with representation learning for acoustic model adaptation to speakers and environments, construction of acoustic models in low-resource settings, and learning representations from multiple acoustic channels. The investigations are primarily focused on the hybrid approach to acoustic modelling ba
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27

RAGONESI, RUGGERO. "Addressing Dataset Bias in Deep Neural Networks." Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1069001.

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Deep Learning has achieved tremendous success in recent years in several areas such as image classification, text translation, autonomous agents, to name a few. Deep Neural Networks are able to learn non-linear features in a data-driven fashion from complex, large scale datasets to solve tasks. However, some fundamental issues remain to be fixed: the kind of data that is provided to the neural network directly influences its capability to generalize. This is especially true when training and test data come from different distributions (the so called domain gap or domain shift problem): in thi
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28

Couairon, Guillaume. "Text-Based Semantic Image Editing." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS248.

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L’objectif de cette thèse est de proposer des algorithmes pour la tâche d’édition d’images basée sur le texte (TIE), qui consiste à éditer des images numériques selon une instruction formulée en langage naturel. Par exemple, étant donné une image d’un chien et la requête "Changez le chien en un chat", nous voulons produire une nouvelle image où le chien a été remplacé par un chat, en gardant tous les autres aspects de l’image inchangés (couleur et pose de l’animal, arrière- plan). L’objectif de l’étoile du nord est de permettre à tout un chacun de modifier ses images en util
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29

Kämpfe, Tanja Katharina. "Content-based image retrieval and the use of neural networks for user adaptation." [S.l.] : [s.n.], 2006. http://deposit.ddb.de/cgi-bin/dokserv?idn=98305066X.

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30

Ekinci, Ozgur. "Adaptation Of A Control System To Varying Missile Configurations." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/3/12611361/index.pdf.

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Varying missile configurations may create uncertainty for a missile control algorithm developed with linear control theory, for instance the control system performance requirements may not be satisfied anymore. Missile configuration may change during the missile design period due to variations in subsystem locations, subsystem weights and missile geometry. Likewise, burning propellant, deployment of aerodynamic surfaces and wings with varying sweep angle can be considered as in-flight missile configuration changes. This thesis study addresses development and analysis of an adaptive missile con
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31

Mazzapioda, Mariagiovanna. "On the evolutionary co-adaptation of morphology and distributed neural controllers in adaptive agents." Thesis, University of Plymouth, 2012. http://hdl.handle.net/10026.1/1011.

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The attempt to evolve complete embodied and situated artificial creatures in which both morphological and control characteristics are adapted during the evolutionary process has been and still represents a long term goal key for the artificial life and the evolutionary robotics community. Loosely inspired by ancient biological organisms which are not provided with a central nervous system and by simple organisms such as stick insects, this thesis proposes a new genotype encoding which allows development and evolution of mor- phology and neural controller in artificial agents provided with a di
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32

Peris, Abril Álvaro. "Interactivity, Adaptation and Multimodality in Neural Sequence-to-sequence Learning." Doctoral thesis, Universitat Politècnica de València, 2020. http://hdl.handle.net/10251/134058.

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[ES] El problema conocido como de secuencia a secuencia consiste en transformar una secuencia de entrada en una secuencia de salida. Bajo esta perspectiva se puede atacar una amplia cantidad de problemas, entre los cuales destacan la traducción automática o la descripción automática de objetos multimedia. La aplicación de redes neuronales profundas ha revolucionado esta disciplina, y se han logrado avances notables. Pero los sistemas automáticos todavía producen predicciones que distan mucho de ser perfectas. Para obtener predicciones de gran calidad, los sistemas automáticos se utilizan bajo
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33

Charles, Eugene Yougarajah Andrew. "Supervised and unsupervised weight and delay adaptation learning in temporal coding spiking neural networks." Thesis, Cardiff University, 2006. http://orca.cf.ac.uk/56168/.

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Artificial neural networks are learning paradigms which mimic the biological neural system. The temporal coding Spiking Neural Network, a relatively new artificial neural network paradigm, is considered to be computationally more powerful than the conventional neural network. Research on the network of spiking neurons is an emerging field and has potential for wider investigation. This research explores alternative learning models with temporal coding spiking neural networks for clustering and classification tasks. Neurons are known to be operating in two modes namely, as integrators and coinc
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34

Piat, Guilhem Xavier. "Incorporating expert knowledge in deep neural networks for domain adaptation in natural language processing." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG087.

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Les Modèles de Langage (LMs) de pointe sont capables de converser, résumer, traduire, résoudre des problèmes inédits, raisonner, et manipuler des concepts abstraits à niveau quasi-humain. Cependant, pour acquérir ces capacités, et en particulier pour acquérir une forme de ``bon sens'' ou des connaissances spécifiques à un domaine, ils requièrent de vastes quantités de texte, qui ne sont pas disponibles pour toutes les langues ou tous les domaines. De surcroît, leurs besoins en puissance de calcul ne sont atteignables que par quelques organisations, limitant leur spécificité ainsi que leur appl
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35

Banda, Peter. "Novel Methods for Learning and Adaptation in Chemical Reaction Networks." PDXScholar, 2015. https://pdxscholar.library.pdx.edu/open_access_etds/2329.

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State-of-the-art biochemical systems for medical applications and chemical computing are application-specific and cannot be re-programmed or trained once fabricated. The implementation of adaptive biochemical systems that would offer flexibility through programmability and autonomous adaptation faces major challenges because of the large number of required chemical species as well as the timing-sensitive feedback loops required for learning. Currently, biochemistry lacks a systems vision on how the user-level programming interface and abstraction with a subsequent translation to chemistry shou
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36

Moura, Geraldo de Araújo. "Sistemas de controle fuzzy neural e neural adaptativo destinados ao controle de pressão em rede de distribuição de água." Universidade Federal da Paraíba, 2016. http://tede.biblioteca.ufpb.br:8080/handle/tede/8971.

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Submitted by Maike Costa (maiksebas@gmail.com) on 2017-05-30T13:07:14Z No. of bitstreams: 1 - Geraldo Moura -.pdf: 5891648 bytes, checksum: 9ca720ba25a16879f0da2a9a837d1f4b (MD5)<br>Made available in DSpace on 2017-05-30T13:07:14Z (GMT). No. of bitstreams: 1 - Geraldo Moura -.pdf: 5891648 bytes, checksum: 9ca720ba25a16879f0da2a9a837d1f4b (MD5) Previous issue date: 2016-11-21<br>This work deals with pressure control in water distribution networks to promote the optimization of hydraulic loads in order to minimize water losses in the pipes and energy in the corresponding pumping system. Th
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Davoian, Kristina [Verfasser], and Wolfram-M. [Akademischer Betreuer] Lippe. "Advancing evolution of artifcial neural networks through behavioral adaptation / Kristina Davoian. Betreuer: Wolfram-M. Lippe." Münster : Universitäts- und Landesbibliothek der Westfälischen Wilhelms-Universität, 2012. http://d-nb.info/102701903X/34.

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Davoian, Kristina Verfasser], and Wolfram-Manfred [Akademischer Betreuer] [Lippe. "Advancing evolution of artifcial neural networks through behavioral adaptation / Kristina Davoian. Betreuer: Wolfram-M. Lippe." Münster : Universitäts- und Landesbibliothek der Westfälischen Wilhelms-Universität, 2012. http://nbn-resolving.de/urn:nbn:de:hbz:6-71459415133.

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Gonçalves, João Bosco. "Desenvolvimento de um sistema de controle adaptativo e integrado para locomoção de um robo bipede com tronco." [s.n.], 2004. http://repositorio.unicamp.br/jspui/handle/REPOSIP/263888.

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Orientador: Douglas Eduardo Zampieri<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica<br>Made available in DSpace on 2018-08-04T03:12:52Z (GMT). No. of bitstreams: 1 Goncalves_JoaoBosco_D.pdf: 9689870 bytes, checksum: db2fb279a1080765ab5bddf9068a356d (MD5) Previous issue date: 2004<br>Resumo: Este trabalho concebeu um robô bípede composto por uma sucessão de elos rígidos interconectados por 12 articulações rotativas, permitindo movimentos tridimensionais. O robô bípede é constituído por dois subsistemas: tronco e membros inferiores. A modelagem matemá
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Kulkarni, Anirudh. "Dynamics of neuronal networks." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066377/document.

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Dans cette thèse, nous étudions le vaste domaine des neurosciences à travers des outils théoriques, numériques et expérimentaux. Nous étudions comment les modèles à taux de décharge peuvent être utilisés pour capturer différents phénomènes observés dans le cerveau. Nous étudions les régimes dynamiques des réseaux couplés de neurones excitateurs (E) et inhibiteurs (I): Nous utilisons une description fournie par un modèle à taux de décharge et la comparons avec les simulations numériques des réseaux de neurones à potentiel d'action décrits par le modèle EIF. Nous nous concentrons sur le régime o
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Meftah, Sara. "Neural Transfer Learning for Domain Adaptation in Natural Language Processing." Thesis, université Paris-Saclay, 2021. http://www.theses.fr/2021UPASG021.

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Les méthodes d’apprentissage automatique qui reposent sur les Réseaux de Neurones (RNs) ont démontré des performances de prédiction qui s'approchent de plus en plus de la performance humaine dans plusieurs applications du Traitement Automatique de la Langue (TAL) qui bénéficient de la capacité des différentes architectures des RNs à généraliser à partir des régularités apprises à partir d'exemples d'apprentissage. Toutefois, ces modèles sont limités par leur dépendance aux données annotées. En effet, pour être performants, ces modèles neuronaux ont besoin de corpus annotés de taille importante
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Tworski, Marcelin. "Automatic analysis of image quality criteria in natural scenes using deep neural networks." Electronic Thesis or Diss., Institut polytechnique de Paris, 2023. http://www.theses.fr/2023IPPAT031.

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Alors que les caméras de smartphones sont devenues plus répandues que les systèmes de caméras traditionnels, la demande de mesures précises de qualité a augmenté. Cette thèse de doctorat propose d'utiliser des systèmes d'apprentissage profond pour évaluer de manière plus approfondie les critères de qualité d'image spécifiques à l'évaluation des caméras de smartphones, et plus particulièrement l'évaluation de la texture, là où les approches précédentes reposaient sur la photographie de mires en laboratoire ou bien n'évaluaient qu'une qualité globale de l'image. Cette thèse aborde de manière exh
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Langlois, Thibault. "Algorithmes d'apprentissage par renforcement pour la commande adaptative : Texte imprimé." Compiègne, 1992. http://www.theses.fr/1992COMPD530.

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Cette thèse présente différentes méthodes d'identification d'une loi de commande pour le contrôle de systèmes dynamiques. Ces méthodes sont basées sur l'utilisation de réseaux de neurones artificiels pour l'approximation de fonctions à partir d'exemples. Une synthèse bibliographique des différentes applications des réseaux de neurones pour le contrôle de processus est présentée. Trois types d'utilisation des réseaux de neurones sont décrits : l'identification directe d'un système ou d'un contrôleur à partir d'exemples, l'identification d'un contrôleur grâce à l'algorithme de «rétropropagation
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Foucault, Cédric. "Adaptive learning in humans, brains and neural networks : the role of uncertainty and probabilities." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS629.

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Lors de l’apprentissage, le cerveau est confronté à un problème difficile. Il apprend d’un environnement qui est à la fois stochastique et dynamique, c’est-à-dire qui se caractérise par des distributions de probabilité qui sont susceptibles de changer. La stochasticité incite le cerveau à intégrer un grand nombre d’observations passées pour arriver à une meilleure précision des connaissances acquises, tandis que la propension au changement l’incite à ne prendre en compte que les observations les plus récentes. Cette tension donne lieu à un compromis dans le taux d’apprentissage à utiliser, que
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Ribeiro, Pleycienne Trajano. "Desenvolvimento, implementação e avaliação de desempenho de um controlador adaptativo do tipo self-tuning regulator aplicado a um processo FCC." [s.n.], 2010. http://repositorio.unicamp.br/jspui/handle/REPOSIP/266952.

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Orientador: Rubens Maciel Filho<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Química<br>Made available in DSpace on 2018-08-17T00:14:12Z (GMT). No. of bitstreams: 1 Ribeiro_PleycienneTrajano_D.pdf: 5889372 bytes, checksum: fb40a08b4781dc281483bc320321f3ff (MD5) Previous issue date: 2010<br>Resumo: Este trabalho teve como principal objetivo o desenvolvimento e implementação de um controlador adaptativo do tipo regulador auto-ajustável (STR - Self Tuning Regulator), com a subsequente comparação de seu desempenho com um controlador PID (proporcionalintegrativ
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John-Baptiste, Peter Jr. "Advancing Fully Adaptive Radar Concepts for Real-Time Parameter Adaptation and Decision Making." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1595501564082873.

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Sousa, Tiago Fernando Barbosa de. "Equaliza??o neural aplicada a sistemas com modula??o bidimensional em fibra ?ptica." Universidade Federal do Rio Grande do Norte, 2014. http://repositorio.ufrn.br:8080/jspui/handle/123456789/15498.

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Made available in DSpace on 2014-12-17T14:56:18Z (GMT). No. of bitstreams: 1 TiagoFBS_DISSERT.pdf: 1617004 bytes, checksum: 989c53485329a28af611291f87ca09f0 (MD5) Previous issue date: 2014-02-28<br>Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior<br>Nowadays, optic fiber is one of the most used communication methods, mainly due to the fact that the data transmission rates of those systems exceed all of the other means of digital communication. Despite the great advantage, there are problems that prevent full utilization of the optical channel: by increasing the transmission speed
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Matos, Lucas Guilhem de. "Control and identification of non-linear systems using neural networks and reinforcement learning." reponame:Repositório Institucional da UnB, 2018. http://repositorio.unb.br/handle/10482/32804.

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Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2018.<br>Submitted by Fabiana Santos (fabianacamargo@bce.unb.br) on 2018-09-27T20:19:43Z No. of bitstreams: 1 2018_LucasGuilhemdeMatos_RESUMO.pdf: 59314 bytes, checksum: fcca0edce88c4bbe8975f96cfb38ac6f (MD5)<br>Rejected by Fabiana Santos (fabianacamargo@bce.unb.br), reason: O arquivo PDF está errado. on 2018-10-08T21:05:29Z (GMT)<br>Submitted by Fabiana Santos (fabianacamargo@bce.unb.br) on 2018-10-08T21:06:22Z No. of bitstreams: 1 2018_LucasGuilhemdeMatos.pdf: 22624129 bytes, checks
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Marza, Pierre. "Learning spatial representations for single-task navigation and multi-task policies." Electronic Thesis or Diss., Lyon, INSA, 2024. http://www.theses.fr/2024ISAL0105.

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Agir de manière autonome dans notre monde 3D requiert un large éventail de compétences, parmi lesquelles se trouvent la perception du milieu environnant, sa représentation précise et suffisamment efficace pour garder une trace du passé, la prise de décisions et l’action en vue d’atteindre des objectifs. Les animaux, par exemple les humains, se distinguent par leur robustesse lorsqu’il s’agit d’agir dans le monde. En particulier, ils savent s’adapter efficacement à de nouveaux environnements, mais sont aussi capables de maîtriser rapidement de nombreuses tâches à partir de quelques exemples. Ce
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Santos, Junior Carlos Roberto dos [UNESP]. "Teoria da ressonância adaptativa através da linguagem Java para detecção e classificação de e-mails indesejados." Universidade Estadual Paulista (UNESP), 2013. http://hdl.handle.net/11449/87167.

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Made available in DSpace on 2014-06-11T19:22:34Z (GMT). No. of bitstreams: 0 Previous issue date: 2013-02-28Bitstream added on 2014-06-13T19:28:06Z : No. of bitstreams: 1 santosjunior_cr_me_ilha.pdf: 674616 bytes, checksum: 0eb6d5afdb466f77cd53efea2c4e4db7 (MD5)<br>O problema de mensagens não solicitadas pelos usuários em meios de comunicação eletrônica, apesar de ter surgido antes mesmo da popularização da Internet, ainda é um assunto preocupante. Desperdício de largura de banda, perda de tempo, de produtividade e de dados, ou atraso na leitura de e-mails legítimos, são alguns dos problemas
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