Hardware and Systems Engineering Essentials: From Circuit to Machine Learning
Motivations
Basic principles in electrical and systems engineering are essential for understanding a broad spectrum of technologies, from electrical system design to signals and linear system processing, probabilistic modeling, and machine learning systems. Rooted in foundational concepts from physics, mathematics, probability and statistics, and computer science, these principles find applications in traditional domains like digital and analog signal processing in consumer electronics. They are also increasingly relevant in emerging fields such as hardware-software systems and modern data science. The purpose of this overview is not just to introduce these key theories and principles, but to foster a deeper engineering intuition. By exploring these fundamental concepts, we aim to enhance first-principles thinking, equipping engineers and practitioners with the insights needed to analyze component behavior, system analysis techniques, and the underlying logic that governs complex systems. Whether the focus is on electronic circuits, signal processing, data science, or machine learning models, a first-principles understanding will be invaluable in tackling real-world engineering challenges
Topics
Positive vs. Negative Feedback
Fourier Transform vs. Lapace Transform
Regulated vs Unregulated Output
Common Mode vs Differential Mode Signals
Transformer vs. Coupled Inductor
Independent and Identically Distributed Random Variables (i.i.d)
Foundation of the Study of Linear Algebra and Functional Analysis