Essays about: "multiple time series"
Showing result 6 - 10 of 152 essays containing the words multiple time series.
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6. DRONAR: Obstacle echolocation using ego-noise
University essay from Linköpings universitet/Institutionen för systemteknikAbstract : You do not want your drone to crash. Therefore, safety systems should be put in place to prevent such an event, and obstacle avoidance is a major part of this. Today, the most successful techniques use cameras or light detection and ranging (LIDAR) to find and avoid obstacles; but to improve resiliency, multiple systems should be used. READ MORE
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7. Applying unprocessed companydata to time series forecasting : An investigative pilot study
University essay from Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)Abstract : Demand forecasting for sales is a widely researched topic that is essential for a business to prepare for market changes and increase profits. Existing research primarily focus on data that is more suitable for machine learning applications compared to the data accessible to companies lacking prior machine learning experience. READ MORE
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8. Multidimensional Classification of Radar Signals : A comparison between unidimensional and multidimensional classification models for pulsed radar signals
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Radar is a technique used by many different types of remote sensing systems to keep track of their surroundings. The transmitted radar signals may carry information that could be used to infer the type of transmitter. Multiple papers have investigated the classification of pulse repetition intervals produced by radar systems. READ MORE
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9. Embedded digital filter design and implementation
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : Digital filters have been widely used in signal processing, to reduce or remove unwanted signals of different types, such as noise, and interference, and to enhance or keep desired signals. They are implemented as algorithms on an embedded system (a microcontroller) or a computer. READ MORE
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10. EVALUATING PERFORMANCE OF GENERATIVE MODELS FOR TIME SERIES SYNTHESIS
University essay from Mälardalens universitet/Akademin för innovation, design och teknikAbstract : Motivated by successes in the image generation domain, this thesis presents a novel Hybrid VQ-VAE (H-VQ-VAE) approach for generating realistic synthetic time series data with categorical features. The primary motivation behind this work is to address the limitations of existing generative models in accurately capturing the underlying structure and patterns of time series data, especially when dealing with categorical features. READ MORE