Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 34 for “"Perceptrons"”.
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Inference of Kolmogorov-Arnold Networks on FPGA-based SoC
… των περισσότερο διαδεδομένων Multi-Layer Perceptrons. Βασίζονται στην αναπαράσταση Kolmogorov-Arnold και δημιουργούν νευρωνικά δίκτυα με εκπαιδεύσιμες συναρτήσεις ενεργοποίησης ως βάρη. Παρότι συχνά παρουσιάζουν καλύτερα αποτέλεσματα από τα συμβατικά Multi-Layer Perceptrons παράγουν …
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Investigating pre-touch sensing to predict grip success in compliant grippers using machine learning techniques
… trees, support vector machines, multi-layer perceptrons and a naive Bayes classifier. The various sensor configuration-machine learning combinations were tested and evaluated based on their ability to predict grip success. Additional training was conducted to demonstrate the ability to …
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Neural Fuzzy Techniques in Vehicle Acoustic Signal Classification
… two main paradigms are considered: multilayer perceptrons and adaptive fuzzy logic systems. A multilayer perceptron is a network inspired by biological neural systems. Even though it is far from a biological system, it possesses the capability to solve many interesting problems in variety …
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Interpolants, Error Bounds, and Mathematical Software for Modeling and Predicting Variability in Computer Systems
… splines, support vector regressors, multilayer perceptrons, Shepard variants, and the Delaunay mesh are investigated in the context of computer variability modeling. New methods of approximation using Box splines, Voronoi cells, and Delaunay for interpolating distributions of data with …
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Computational Studies of PbS Quantum Dots
… expansion formulation alongside multilayer perceptrons, in training neural network potentials, as well as in directly accelerating geometry relaxations for PbS quantum dots. Noticing some unexpected nontrivial behavior during the geometry relaxation runs, we sought to quantify and clarify …
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Hardware software co-design of machine learning accelerators using univariate functions
… a 2×compression in hidden size of Multi-Layer Perceptrons (MLP), while matching accuracy. Applying this to an MLP-based vision model on CIFAR-10, we cut the number of operations by 45%–28%, boosting hardware efficiency. We validate PSA with two hardware accelerators while maintaining the same …
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Data fusion based optimal EEG electrode selection for early diagnosis of Alzheimer's disease
… disease. Through the use of multilayer perceptrons and support vector machines, classifiers were generated on different portions of the EEG. These classifiers are then combined using combination methods such as sum rule, product rule, simple and weighted majority voting.</p> …
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Predicting cardiovascular risks using pattern recognition and data mining.
… investigated techniques include multilayer perceptrons, radial basis functions, and support vector machines for supervised classification, and self organizing maps, KMIX and WKMIX algorithms for unsupervised clustering. The Physiological and Operative Severity Score for enUmeration of …
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Solving Machine Learning Problems
… (i) basic machine learning principles; (ii) perceptrons; (iii) feature extraction and selection; (iv) logistic regression; (v) regression; (vi) neural networks; (vii) advanced neural networks; (viii) convolutional neural networks; (ix) recurrent neural networks; (x) state machines and MDPs; …
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Understanding Representations and Reducing their Redundancy in Deep Networks
… linear models then proceeds to deep multilayer perceptrons and convolutional neural networks, presenting the core details of each. However, the introduction also focuses on intuition by visualizing concrete examples of the parts of a modern network. The second part of this thesis investigates …
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Modelos neurais autônomos para classificação e localização de defeitos em linhas de transmissão
… bayesiana para especificação e treinamento de perceptrons de múltiplas camadas (MLPs), o sistema inteligente fornece respostas probabilísticas para classificação do tipo de defeito e também para a distância da falta em relação à subestação monitorada. Para desenvolvimento dos modelos são …
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Understanding Concept Representations and their Transformations in Transformer Models
… of the first layer of the multi-layer perceptrons (MLPs) in transformers are the salient basis for represent the information the model is using for computation. However, there currently do not exist any empirical studies comparing these internal representations to others that have been …
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Wavelets na compactação e processamento de sinais de distúrbios em sistemas de potência para classificação via redes neurais artificiais
… é submetido à Rede Neural tipo Multilayer Perceptrons - MLP, que indicará o tipo de distúrbio presente no sinal. Cada rede implementada foi treinada com uma base de conhecimento, cujos atributos foram constituídos dos coeficientes wavelets de aproximação, ou de detalhes, ou de ambos. Na …
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Convolutional Conditional Neural Processes
… neural networks rather than multi-layer perceptrons. Second, we propose Gaussian neural processes (GNPs). GNPs directly parametrise dependencies in the predictions of a neural process. Current approaches to modelling dependencies in the predictions depend on a latent variable, which …
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Reducing Global Memory Accesses in DNN Training using Structured Weight Masking
… network composed exclusively of Multi-Layer Perceptrons. A novel framework implementing block-wise masking based on L2 norm magnitude and top-k selection was developed and evaluated on the CIFAR-10 dataset. The study systematically varied block sizes and sparsity ratios, analyzing the impact …
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Analysis of breast tissue microarray spots
… classifiers based on either multi-layer perceptrons or latent Dirichlet allocation models. A classification accuracy of 74.6 % was achieved. Tumour and normal spots were scored via an approach that involved the computation of global features formalising the quickscore values used by …
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