Explores the integration of machine learning into discrete choice models, emphasizing the importance of theory constraints and hybrid modeling approaches.
Explores statistical signal processing tools for wireless communications, including spectral estimation and signal detection, classification, and adaptive filtering.
Explores sampling signals and their spectrum, highlighting the significance of choosing the right sampling frequency for accurate signal representation.
Introduces the Time-Frequency Discretization for processing digital signals and covers the quality of discrete approximation and main properties of TFD.
