Digital Signal Processing (DSP) Fundamentals Training Course

Introduction

Overview of Core Electronics Concepts and Principles Applied in DSP

• The relevance and depth of DSP in modern technologies

Recollecting Mathematics and Physics Fundamentals Implemented in DSP

• Applying statistics, probability, and noise principles
• Reviewing linear systems and superposition physics concepts
• Understanding ADC and DAC manipulation

Overview of Useful DSP Software Platform and Tools

Getting Started with Digital Signal Processors Architecture

• System requirements for DSP processors

Working with Convolution Properties and Algorithms

• Delta function v.s. impulse response
• Understanding the input side and output side algorithms
• Comprehending electronics correlation and speed in DSP

Getting Started with the Discrete Fourier Transform

• What are Fourier Transforms?
• Manipulating DFT notations, format, and variables
• Synthesizing and analyzing DFT calculations
• Working with DFT properties and polar attributes

Applying DFT Principles and Processes to DSP Functionalities

• Practicing spectral analysis and evaluating frequency responses

Operating Different DSP Domains and Choosing the Right Implementations

• Time and space domains
• Frequency and wavelet domains

Carrying Out Convolution Using the Frequency Domain

Employing Advanced Fourier Transform Properties and Applications

• What are Fourier Transform pairs and how do they work?
• Fast Fourier Transform v.s. Discrete Fourier Transform

Implementing Continuous Signal Processing

Overview of Digital Filters Types and its Primary Functions

Understanding How Information Filtering Works and Operating Basic Digital Filters

• Step response v.s. noise reduction

Employing Moving Average Filters and Applying Convolution Implementations

Working with Window-Sinc Filters and Removing Frequency Components

Operating Recursive Filters and Chebyshev Filters

• What is the recursive method in DSP?
• What are Butterworth responses?

Choosing the Appropriate DSP Filter for an Electronics Application

Creating and Building a Custom DSP Filter Based on Arbitrary Frequency Response

• Testing and optimizing a DSP filter

Integrating a Tested DSP Filter within the Preferred Electronics System

• Understanding DSP for data compression, imaging techniques, and more
• Carrying out exercises for various DSP applications and use cases

Overview of Advanced Software Tools for Achieving DSP Implementations

Implementing Complex DSP Techniques for Future Applications

• Exploring complex Fourier Transforms, z-Domain, etc.

Troubleshooting

Summary and Conclusion