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Full-Text Articles in Signal Processing
A Comprehensive Analysis On Eeg Signal Classification Using Advanced Computational Analysis, Kaushik Bhimraj
A Comprehensive Analysis On Eeg Signal Classification Using Advanced Computational Analysis, Kaushik Bhimraj
Electronic Theses and Dissertations
Electroencephalogram (EEG) has been used in a wide array of applications to study mental disorders. Due to its non-invasive and low-cost features, EEG has become a viable instrument in Brain-Computer Interfaces (BCI). These BCI systems integrate user's neural features with robotic machines to perform tasks. However, due to EEG signals being highly dynamic in nature, BCI systems are still unstable and prone to unanticipated noise interference. An important application of this technology is to help facilitate the lives of the tetraplegic through assimilating human brain impulses and converting them into mechanical motion. However, BCI systems are remarkably challenging to implement …
Independent Component Analysis Enhancements For Source Separation In Immersive Audio Environments, Yue Zhao
Independent Component Analysis Enhancements For Source Separation In Immersive Audio Environments, Yue Zhao
Theses and Dissertations--Electrical and Computer Engineering
In immersive audio environments with distributed microphones, Independent Component Analysis (ICA) can be applied to uncover signals from a mixture of other signals and noise, such as in a cocktail party recording. ICA algorithms have been developed for instantaneous source mixtures and convolutional source mixtures. While ICA for instantaneous mixtures works when no delays exist between the signals in each mixture, distributed microphone recordings typically result various delays of the signals over the recorded channels. The convolutive ICA algorithm should account for delays; however, it requires many parameters to be set and often has stability issues. This thesis introduces the …