Covers the theory of numerical methods for frequency estimation on deterministic signals, including Fourier series and transform, Discrete Fourier transform, and the Sampling theorem.
Introduces a project-based course in communications and robotics, emphasizing practical projects and independent learning to prepare students for real-world challenges.
Covers examples of signal processing, analog signal processing, continuous amplitude modulation, image processing, compression, micro-systems, and medical electronics.
Introduces the course on information systems, covering its structure, objectives, and foundational concepts essential for understanding data management and decision-making.
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.
