Covers the Fourier transform, its properties, applications in signal processing, and differential equations, emphasizing the concept of derivatives becoming multiplications in the frequency domain.
Covers statistical signal processing tools for wireless communications, focusing on signals like train of pulses, harmonic signals, and smooth spectrum signals.
Introduces mathematical tools for communication systems and data science, focusing on stochastic processes and preparing students for advanced courses.
Explores neurobiological signal processing, covering spike modeling, signal classification, and data characterization using principal component analysis.
Covers the Fourier transform, its properties, and applications in signal processing and differential equations, demonstrating its importance in mathematical analysis.
