Ementorhub

What you'll learn

The nature of discrete-time signals

Discrete-time signals are vectors in a vector space

Discrete-time signals can be analyzed in the frequency domain via the Fourier transform

Skills you'll gain

Digital Communications

Applied Mathematics

Advanced Mathematics

Electronics

Mathematical Modeling

Programming Principles

Linear Algebra

Telecommunications

Electrical and Computer Engineering

Computational Logic

Time Series Analysis and Forecasting

Algorithms

Engineering Analysis

There are 4 modules in this course

In this series of four courses, you will learn the fundamentals of Digital Signal Processing from the ground up. Starting from the basic definition of a discrete-time signal, we will work our way through Fourier analysis, filter design, sampling, interpolation and quantization to build a DSP toolset complete enough to analyze a practical communication system in detail. Hands-on examples and demonstration will be routinely used to close the gap between theory and practice. To make the best of this class, it is recommended that you are proficient in basic calculus and linear algebra; several programming examples will be provided in the form of Python notebooks but you can use your favorite programming language to test the algorithms described in the course.

Module 1.2: Signal Processing Meets Vector Space

Module 1.3: Fourier Analysis: the Basics

Module 1.4: Fourier Analysis: More Advanced Tools