Udemy – Undergraduate course on signals and systems(Course-II) 2025-3

Udemy – Undergraduate course on signals and systems(Course-II) 2025-3 Downloadly IRSpace

Aug 16, 2025 - 07:18 Updated: Aug 17, 2025 - 19:56

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Udemy – Undergraduate course on signals and systems(Course-II) 2025-3

Undergraduate course on signals and systems(Course-II), This is an undergraduate course on signals and systems. This course is the second part in a series of two courses on basics of signals and systems For any electrical, electronics, Instrumentation or bio-medical engineering student applying transformation theory to signal processing and system analysis is necessary. My previous course “undergraduate course on signals and systems-I” is a prerequisite for complete understanding of this course. Or one must have a good knowledge in introductory signals, system properties and Convlution techniques. Fourier series: Fourier series is a powerful mathematical tool that converts a periodic signal in continuous time domain into frequency domain. Fourier series splits up a periodic signal into infinite harmonically related sinusoidal components or inotherwords by combining infinite harmonically related sinusoidal signals a periodic signal(usually non-sinusoidal) can be synthesized. Fourier transform: A power-packed mathematical tool that synthesizes aperiodic signals. The Fourier spectrum obtained here is used in analog communication techniques and in Analog filters. Signal processing through an LTI system can be visualized in frequency domain. Laplace transform: Laplace transform is a simple yet powerful mathematical tool which gives the S-domain representation for a time domain signal. Some of the limitations of Fourier techniques can be overcomed by Laplace transform. Laplace transform is the back-bone of Control systems and Analog network analysis. Transfer function of any system is defined in laplace domain. Sampling theorem: It is a bridge between continuous-analog signals and discrete-digital signals. Sampling theorem lies the foundation for my next coureses in discrete signal processing.

What you’ll learn

Transformation techniques in Continuous -time domain
Sampling theorem to convert a continuous signal to discrete domain
All properties of Transformation techniques that are required to simplify the problem solving
All basics required to understand discrete transformation techniques and digital filters

Who this course is for

Undergraduate engineering students with Electrical engineering, Electronics engineering, Biomedical engineering, Instrumentation engineering as specialisation
Diploma/Polytechnic students with Electronics engineering, Communication engineering, Instrumentation as specialisation
GATE and PSU preparing students
Any Electronics or communication engineer who wants strengthen signal processing fundamentals