Essays about: "Singular Value Decomposition SVD"
Showing result 1 - 5 of 24 essays containing the words Singular Value Decomposition SVD.
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1. Graph Neural Network for Traffic Flow Forecasting : Does an enriched adjacency matrix with low dimensional dataenhance the performance of GNN for traffic flow forecasting?
University essay from Högskolan i Halmstad/Akademin för informationsteknologiAbstract : Nowadays, machine learning methods are used in many applications and deployed in manyelectronic devices to solve problems and predict future states. One of the challenges mostbig cities confront is traffic jams since the roads are crammed with more and more vehicles, which will easily cause traffic congestion. READ MORE
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2. Ingredient-based Group Recommender for Recipes (IGR2)
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : The number of food recipe options in modern society is vast and growing. While often being considered positive, the abundant options also lead to the so-called paradox of choice, i.e. that more options can lead to less happiness. READ MORE
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3. Sparse Approximation of Spatial Channel Model with Dictionary Learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In large antenna systems, traditional channel estimation is costly and infeasible in some situations. Compressive sensing was proposed to estimate the channel with fewer measurements. Most of the previous work uses a predefined discrete Fourier transform matrix or overcomplete Fourier transform matrix to approximate the channel. READ MORE
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4. Classification of EEG Data Using Convolutional Neural Networks and the Scaled Reassigned Spectrogram
University essay from Lunds universitet/Matematisk statistikAbstract : Electroencephalography (EEG) is a medical technique for measuring brain activity through several channels connected to the scalp. Interpreting EEG data is a difficult problem because of the large amount of noise contained in the data. READ MORE
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5. Automated error matching system using machine learning and data clustering : Evaluating unsupervised learning methods for categorizing error types, capturing bugs, and detecting outliers.
University essay from Linköpings universitet/Programvara och systemAbstract : For large and complex software systems, it is a time-consuming process to manually inspect error logs produced from the test suites of such systems. Whether it is for identifyingabnormal faults, or finding bugs; it is a process that limits development progress, and requires experience. READ MORE