Foundations of Signal Processing: Continuous and Discrete Systems

Raw data from physical systems is noisy and complex, making signal processing an essential skill for modern engineering and data analysis. This course introduces you to the core mathematical and conceptual frameworks needed to interpret, filter, and analyze signals.\n\nYou will transition from understanding basic wave properties to designing digital filters and identifying system behaviors, giving you the tools to handle real-world experimental data with confidence.\n\nWhat you'll learn:\n- Understand the foundational terminology of continuous and discrete-time signals.\n- Apply Fourier analysis and spectral techniques to identify frequency components in noisy data.\n- Design and analyze basic digital and analog filters to isolate key signal features.\n- Practice system identification techniques to model physical processes from experimental inputs.\n- Explore modern digital signal processing concepts, including sampling theorems and noise reduction.\n- Simulate continuous and discrete-time system behaviors through detailed written walkthroughs.\n\nThe course begins with essential mathematical definitions and signal representation before moving into spectral analysis, filter design, and practical data-processing scenarios. You will work through structured written exercises to solidify your analytical skills.\n\nThis course is designed for beginners in engineering, science, or data analysis, and requires no prior background in advanced signal processing.\n\nStart reading today to unlock the power of signal analysis.