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- W2977362258 abstract "In telecommunication baseband signal processing systems, thousands oftasks are executed every millisecond. These tasks take in dierentparameters and cause heavy load to the system. The aim of the thesis is tobuild proper mathematical models for these tasks, enabling the predictionof their load given the corresponding parameters.For each task, data samples of task load measure and correspondingparameters are provided. No prior knowledge on the task load and itsparameters is available. By studying the data samples, an explicit, accurateand simple model is expected. Graphical skills like scatter plots are usedas a preliminary analysis of the data. Then rst-order and second-orderlinear models, piecewise-linear models and tree-based models are taken asprototypes for the task modeling. Methods like stepwise linear regressionand partial correlation analysis are applied to select proper parameters frommany available parameters to simplify the models. An automatic tool isfurther developed to automate the whole modeling process.There are 17 tasks in total. For 15 tasks, acceptable models are builtwith aRMSE lower than 2 times of the estimated noise standard deviationwith the assumption of a Gaussian noise, while for the other 2, no adequatemodels are given. Reasons for not getting acceptable models are discussedand suggestions on future work are proposed." @default.
- W2977362258 created "2019-10-10" @default.
- W2977362258 creator A5022256556 @default.
- W2977362258 date "2014-01-01" @default.
- W2977362258 modified "2023-09-28" @default.
- W2977362258 title "Task Load Modeling for LTE Baseband Signal Processing with Regression Analysis Approach" @default.
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- W2977362258 hasPublicationYear "2014" @default.
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