If you wish to gain knowledge in fields that employ digital signals of any sort need to learn the processing techniques inherent to digital signals. Since the invention of the integrated circuit, the need to perform extensive operations on digital signals has increased. Today, we have application-specific integrated circuits that are only used for handling and processing digital signals.
Additionally, almost all digital computers, embedded systems and microcontrollers are capable of performing digital signal processing. The technology of DSP is so ingrained into every single industry that its applications are myriad. This technology finds itself being employed in applications like seismology, sonar, radar, image processing, security, biomedical engineering, robotics, aviation, nuclear science and so much more.
In this course, we will build upon the knowledge we have on continuous-time signals and systems. We will understand the different types of operations involved in digital signal processing. We will also understand various techniques that are used in the designing of digital filters.
You are expected to be familiar with advanced calculus and complex variable theory. You must have studied these topics in the First/Second year of your BE/BTech course. Knowledge of Fourier, Laplace and Z transforms on continuous-time signals is also expected.
This course is designed to provide you with the fundamental knowledge and working information of digital signal processing and digital filters. If you are someone who needs to work with basic digital signal processing or are an electronics or computers student, this course is perfect for you. The level of this course is marked at ‘Undergraduate’. This course will enable you to take higher-level digital signal processing courses.
Our courses are free and will always be.
- Digital Signal Processing – Introduction, Systems, Advantages and Applications.
- Elementary discrete time signals: Unit sample, unit step signal, unit ramp signal and exponential signal.
- Fourier signals and Fourier transform of signals.
- Convolution of signals.
- Correlation of signals.
- Z transform of digital signals.
- Types and properties of Z transform.R
- Relationship between Z transform and Laplace Transform.
- Relationship between Fourier transform and Z transform.
- Discrete Fourier Transform (DFT) – Linear transform and properties
- Circular convolution and Linear Convolution
- Fast Fourier Transform (FFT)
- Decimation in frequency (DIF) algorithm and Decimation in Time (DIT) algorithm.
- Computation of inverse DFT using FFT.
- Fast Convolution – Overlap-add and Overlap-save methods.
- Infinite Impulse Response Filter (IIR) – Butterworth, Chebyshev, and Elliptic.
- Finite Impulse Response Filter (FIR) – Design and Gibbs phenomenon.
- Design techniques for FIR filters – Fourier series, frequency sampling and window method.
- Finite Word Length Effect in Digital Filters – Quantization, product quantization error.