Essays about: "Dynamic Time Warping"
Showing result 6 - 10 of 28 essays containing the words Dynamic Time Warping.
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6. Clustering of Unevenly Spaced Mixed Data Time Series
University essay from KTH/Matematisk statistikAbstract : This thesis explores the feasibility of clustering mixed data and unevenly spaced time series for customer segmentation. The proposed method implements the Gower dissimilarity as the local distance function in dynamic time warping to calculate dissimilarities between mixed data time series. READ MORE
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7. Radio Environment Classification
University essay from Umeå universitet/Institutionen för fysikAbstract : This thesis has looked into the possibility of classifying radio environment scenarios based on data received in base stations. It was done in order to improve forecasting of electrical output in these base stations. READ MORE
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8. AUGMENTATION AND CLASSIFICATION OF TIME SERIES FOR FINDING ACL INJURIES
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : This thesis addresses the problem where we want to apply machine learning over a small data set of multivariate time series. A challenge when classifying data is when the data set is small and overfitting is at risk. Augmentation of small data sets might avoid overfitting. READ MORE
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9. Automatic Annotation of Speech: Exploring Boundaries within Forced Alignment for Swedish and Norwegian
University essay from Uppsala universitet/Institutionen för lingvistik och filologiAbstract : In Automatic Speech Recognition, there is an extensive need for time-aligned data. Manual speech segmentation has been shown to be more laborious than manual transcription, especially when dealing with tens of hours of speech. READ MORE
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10. LSTM Feature Engineering Through Time Series Similarity Embedding
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : Time series prediction has many applications. In cases with simultaneous series (like measurements of weather from multiple stations, or multiple stocks on the stock market)it is not unlikely that these series from different measurement origins behave similarly, or respond to the same contextual signals. READ MORE
