Digital Signal Processing (DSP) From Ground Up™ on Arm Processors

Practical Signal Processing : DFT, Filter Design, Convolution, IIR, FIR, CMSIS-DSP, Linear Systems

15+ hours | Complete Source Code Included

Do you want to learn practical digital signal processing (dsp) without confusion?

Here’s an overview of what you’re getting in this dsp on Arm processors course...

Understanding the foundations of signal processing without complications

Before going on to implement practical dsp algorithms from scratch, this course teaches you the foundation of signal processing step-by-step. We shall look at key topics in signal processing including:

Signal statistics and noise
Quantization and sampling theorem
Analog filter design
Performance metrics of the Chebyshev, Butterworth, and Bessel filters
Linear systems and their properties
Finite Impulse Response Filters (FIR)
Infinite Impulse Response Filters (IIR)
Superposition, synthesis, and decomposition
Convolution and its properties
Discrete Fourier Transform (DFT) and IDFT

Developing Digital Signal Processing Algorithms

We shall practically develop the signal processing algorithms we discussed in the theory class. Over here rather than use live signals we shall use some already acquired and generated signals to test our algorithms, to keep the focus on developing the algorithms and testing them, rather than signal acquisition.

We shall develop the following algorithms:

Signal statistics algorithms: signal mean, signal standard deviation, signal variance
The Convolution algorithm
The Running Sum algorithm
The Discrete Fourier Transform (DFT) algorithm
The Inverse Discrete Fourier Transform (IDFT) algorithm

We shall also implement some of these algorithms using the CMSIS-DSP library and then compare the dynamic performance of our algorithm to that of the ones provided by CMSIS-DSP

Developing Drivers and Data Structures for Signal Acquisition

To be able to properly acquire signals from the external world and then apply our signal processing algorithms, we first need to develop analog-to-digital converter (ADC) drivers for acquiring the signals and appropriate data structures more storing and managing the signal. Over here we shall develop :

A bare-Metal ADC driver for acquiring the signal
A First-In-First-Out data structure for storing and managing the signal

Digital Filter Design and Implementations

We shall learn about the various types of digital filters available and then go on to implement them from scratch. We shall implement:

The Moving Average Filter
The Finite Impulse Response (FIR) filter
The Infinite Impulse Response (IIR) Filter

We shall also see how to design the filter kernel of the finite impulse response filters using Matlab.

Practical DSP Application on Live Signal

Over here, we shall apply all that we have learnt to process live signals from our microcontroller’s ADC

This course is more than just getting the code to work. It will teach you how to ….

Write Practical DSP Algorithms WITHOUT a fancy Engineering Degree

You will be able to understand the foundations of signal processing without the hassle of complex mathematical derivations.

**Taken by 3000+ Students with 290+ Reviews**

This course is the fully updated version of the 1st edition of the course. The first edition has been taken by over 3000 students with over 290 reviews.

Here is what one student had to say about the course :

"The information covered in this course is exactly what I needed to learn for a new assignment. Both general information about DSP as well as how to implement things on the ARM Cortex M4."

Here is what another student had to say:

"It is exciting to see how MATLAB is used in embedded systems for signal generation and filter design. The explanation here is simple and to the point. Keeps the viewer's interest captured and avoids unnecessary details."

In summary, you really have nothing to lose. Give it a try, it comes with a full money back guarantee. Hope to see you in the course.

Preview

Lesson : Programming : Developing the Convolution Algorithm

Setting Up
Downloading CubeIDE
Installing CubeIDE
Getting the required documentation
Getting the required package for bare-metal development
Testing the project setup
Getting Stasrted
Programming : Enabling the Floating Point Unit (FPU)
Programming : Plotting Signals using the Internal Logic Analyzer
Programming : UART Driver - Analyzing the Documentation
Programming : UART Driver - GPIO Pin Configuration
Programming : UART Driver - Protocol Paramters Configuration
Programming : UART Driver - Transmission Function
Programming : UART Driver - Testing the Driver
Programming : UART Driver - Plotting Signals
Programming : Integrating the CMSIS-DSP Library
Programming : Testing the CMSIS-DSP float32_t
Signal Statistics and Noise
Introduction to Signals
The Signal Mean and Standard Deviation
Programming : Developing the Signal Mean Algorithm
Programming : Developing the Signal Variance Algortihm
Programming : Developing the Signal Standard Deviation Algorithm
Programming : Computing the Signal Standard Deviation using CMSIS-DSP
Quantization and The Sampling Theorem
Understanding the Sampling Theorem
The Passive Low-Pass Filter
The Passive High-Pass Filter
The Active Filter
Chebyshev, Butterworth and Bessel Filters

ARM Cortex-M DSP Support Features
Overview of Arm Cortex-M DSP Support Features

Linear Systems and Superposition
Introduction to Linear Systems
Understanding Superposition
Impulse and Step Decomposition
Convolution
Introduction to Convolution
The Convolution Operation
Examining the Output of Convolution
The Convolution Sum Equation
Programming : Analyzing the Input Signals of Convolution
Programming : Developing the Convolution Algorithm
Programming : Analyzing the Output Signal of Convolution
Programming : Computing Convolution using CMSIS-DSP
Programming : Developing a SysTick Driver to Measure Dynamic Efficiency
Programming : Measuring the Dynamic Performance of CMSIS-DSP (Part I)
Programming : Measuring the Dynamic Performance of CMSIS-DSP (Part II)
A closer look at the Delta function
The First Difference and Running Sum
Programming : Implementing the Running Sum Algorithm

Discrete Fourier Transform (DFT)
Introduction to Fourier Transform
The Discrete Fourier Transform (DFT) Engine
The Inverse Discrete Fourier Transform (IDFT)
Programming : Developing the Discrete Fourier Transform (DFT) Algorithm
Programming : Analyzing the ECG Signal for Inverse DFT
Programming : Developing the Inverse DFT Algorithm (Part I)
Programming : Developing the Inverse DFT Algorithm (Part II)

A little about me : Israel Ninsaw Gbati

Some of you may have taken some of my embedded systems courses from other online platforms.

This is my private channel.

I have been writing embedded firmware for years, I have built embedded devices like consumer products and robotic arms.

Till date I have

trained over 75,000 students in embedded

firmware development online till date

...including third year undergraduate university students in-person.

If you have taken any of my courses before you will know I start from the absolute basics, I do not assume that the student has any prior knowledge of the topic under discussion. You will also know that by the end of the course you understand the functions of every register used in developing the particular firmware or driver.

This method is the same for all of my published embedded systems courses.

Our courses have been reviewed by 1000+ students

Here are some of the reviews