Discover digital signal processing fundamentals, delve into signal design and analysis, learn about transforms, and develop practical OFDM systems focusing on modulation and demodulation. Gain insights into time and frequency domains.

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We live in a world filled with signals which can be represented by sequences of numbers in a digital machine. These sequences of numbers can be manipulated by algorithms and have numerous applications in audio, images, video, wireless transmission and countless other domains. 

In this course, you’ll understand the field of digital signal processing with a focus on the design and analysis of signals, and algorithms. You’ll cover the DSP fundamentals of signals, systems and transforms. You’lll learn about the basic signal types and perform different operations. You’ll develop an understanding about the frequency domain and how to represent signals in time, and the transformation from one domain to the other using the Fourier transform. You’ll also learn about digital systems. Finally, you’ll develop a practical OFDM system focusing on modulation and demodulation.

By the end of this course, you’ll be able to model, analyze and design signals and systems in greater depth, in the time and frequency domains.

Fundamentals of Digital Signal Processing

We‘ve just learned how the world is driven by natural signals, almost all of which are analog. Now let’s turn toward the power of digital signals.

## Exploring DSP

In analog signals, the independent variable of time is represented on a continuous scale. On the other hand, a **discrete-time signal** is a sequence of samples that can be stored in computer memory and operated on with a processor. **Sampling** is the process through which analog signals are sampled at regular intervals to produce a discrete-time signal.

With these discrete numbers in hand, DSP is simply a skillset of how to best utilize these sequences towards achieving our desired outcomes. This skillset is comprised of various tools and techniques that enable us to view the same number patterns through different lenses and manipulate them by using efficient algorithms. Even machine learning is a kind of DSP that utilizes advanced mathematical techniques to extract information and make predictions and decisions from diverse data sets.

# Exploring DSP

In analog signals, the independent variable of time is represented on a continuous scale. On the other hand, a **discrete-time signal** is a sequence of samples that can be stored in computer memory and operated on with a processor. **Sampling** is the process through which analog signals are sampled at regular intervals to produce a discrete-time signal.

With these discrete numbers in hand, DSP is simply a skillset of how to best utilize these sequences towards achieving our desired outcomes. This skillset is comprised of various tools and techniques that enable us to view the same number patterns through different lenses and manipulate them by using efficient algorithms. Even machine learning is a kind of DSP that utilizes advanced mathematical techniques to extract information and make predictions and decisions from diverse data sets.

Introduction to Signals

Basic Signals and Operations

Complex Signals and the Frequency Domain

Sampling a Signal

The Discrete Fourier Transform

Fourier Transform Properties

Digital Systems

Putting It All Together: An OFDM Modem

Demodulating an OFDM Signal Stream

The Last Words

Bibliography

What is Digital Signal Processing?

Exploring DSP