Signals and Systems: Core Concepts and Transformations

Signals and Systems is the cornerstone of modern electrical engineering, telecommunications, and digital processing. Mastering these concepts is essential for analyzing how information is transmitted and modified. By the end of this course, you will have a solid mathematical and conceptual framework for understanding signals (continuous and discrete) and the fundamental properties of systems. You will be able to perform basic time-domain analysis, apply essential signal transformations, and lay the groundwork for frequency domain analysis and advanced Digital Signal Processing (DSP) topics. What you'll learn: * Understand the definition and mathematical representation of continuous-time and discrete-time signals. * Classify signals based on core properties, including energy, power, periodicity, and symmetry. * Apply fundamental transformations to the independent variable, such as time shifting, scaling, and reversal. * Analyze the core properties of systems, including linearity, time-invariance, causality, and stability. * Practice calculating the output of Linear Time-Invariant (LTI) systems using convolution sums and integrals. * Grasp the basic concepts of sampling theory and its role in converting continuous signals to discrete representations. The course begins with essential terminology and mathematical definitions, progresses through signal classification and manipulation, and concludes with an introduction to system analysis techniques. This introductory course is designed for absolute beginners in engineering, physics, or computer science. No prior specialized knowledge of signals or systems is required, but a basic understanding of calculus is helpful. Start building your fundamental knowledge base for signal processing and system analysis today.