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Course: Engineering Sciences & Systems

Signals and Systems

Imagine being able to understand, manipulate, and predict all kinds of signals, from music streaming to heartbeats to data flows in a network. This Signals and Systems course dives into the fundamental concepts of signal processing and system behavior, equipping you with tools to analyze everything from sound waves to electronic circuits. By learning how signals interact with systems, you'll gain the ability to solve complex engineering problems across a range of fields. Each chapter introduces crucial topics, such as continuous and discrete signals, Fourier transforms, and system.

• Engineering Sciences & Systems

14 chapters. Online and self-paced, in English, on the BMEssentia Platform.

What you will learn

• Signal Classification and Analysis: Learn to differentiate between continuous and discrete signals, periodic and aperiodic signals, and understand their unique applications.
• Fourier Series and Transform Techniques: Master Fourier methods to analyze signals in the frequency domain, crucial for fields like communications and audio engineering
• Convolution and System Response: Gain skills in convolution to determine system response, a fundamental concept for predicting system behavior.
• Time and Frequency Domain Analysis: Discover how to analyze signals and systems in both time and frequency domains for a comprehensive understanding of their characteristics.
• Sampling Theorem and Aliasing Prevention: Learn the principles of signal sampling and how to prevent aliasing, essential for digital signal processing.
• Laplace and z-Transform Applications: Explore advanced techniques like the Laplace and z-transforms for analyzing and solving complex systems.
• Stability and Causality in Systems: Understand the principles of system stability and causality, ensuring reliable performance across applications.
• Signal Processing Tools and Techniques: Develop proficiency in using various signal processing tools, from filtering noise to amplifying key information.
• Energy and Power Calculations: Gain insight into measuring signal energy and power, important for applications requiring efficient information transmission.
• Practical Applications in Engineering: Apply your knowledge to real-world engineering problems, from designing filters to improving wireless communication systems.

Modules

1. Introduction to Signals and Systems
2. Basic Continuous-Time and Discrete-Time Signals
3. Convolution
4. Properties of Linear, Time-Invariant (LTI) Systems
5. Systems Represented by Differential and Difference Equations
6. Fourier Series Representation of Continuous-Time Periodic Signals
7. Fourier Series Representation of Discrete-Time Periodic Signals
8. Sampling and Reconstruction of Signals
9. Continuous-Time Fourier Transform
10. Properties of Continuous-Time Fourier Transform
11. Systems Characterized by Linear Constant Coefficient Differential Equations
12. Discrete Fourier Transform (DFT) and Sampling
13. The Laplace Transform
14. The z-Transform

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