Explores statistical signal processing tools for wireless communications, including spectral estimation and signal detection, classification, and adaptive filtering.
Covers statistical signal processing tools for wireless communications, including spread spectrum, spectral analysis, ultra-wide band communications, and heart rate variability analysis.
Explores the integration of machine learning into discrete choice models, emphasizing the importance of theory constraints and hybrid modeling approaches.
Covers spectral estimation techniques like tapering and parametric estimation, emphasizing the importance of AR models and Whittle likelihood in time series analysis.
