Digital Signal Processing Course (DSP) – Learn from scratch

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Introduction to Digital Signal Processing (DSP)

What is digital signal processing (DSP)? – A complete overview

January 10, 2020

An introduction to Digital Signal Processing that includes everything you need to know about the DSP, its merits and demerits, and its applications.

simple explanation of the signal transforms (Laplace, Fourier and Z)

A simple explanation of the signal transforms (Laplace, Fourier and Z)

January 12, 2020

Can’t understand Fourier or Laplace or Z signal transforms? This is the easiest way to understand what they are, how they relate with each other and what’s their purpose.

Aliasing in DSP

What is aliasing in DSP and how to prevent it?

January 1, 2020

Aliasing is a very common undesirable effect in the processing of digital signals. In this post, we discuss what it is, its implications and how to avoid it.

Convolution - Derivation, types and properties

Convolution – Derivation, types and properties

December 4, 2019

Convolution is an important operation in digital signal processing. In this post, we will introduce it, derive an equation and see its types and properties.

Difference between linear and circular convolution

What is the difference between linear convolution and circular convolution?

December 1, 2019

There are two types of convolution. Linear convolution and circular convolution. Turns out, the difference between them isn’t quite stark.

Discrete Time Fourier Transform (DTFT) vs Discrete Fourier Transform (DFT)

Discrete Time Fourier Transform (DTFT) vs Discrete Fourier Transform (DFT)

December 4, 2019

The Discrete Fourier Transform is a subset of the Discrete Time Fourier Transform. But there are some subtle differences between the two. Let’s check em out

Twiddle factor of DFT

Twiddle factors in DSP for calculating DFT, FFT and IDFT

December 30, 2019

An easy to understand summary of twiddle factors, their usage in calculating DFT and IDFT in DSP and their cyclic properties.

properties of discrete fourier transform (dft)

Properties of DFT (Summary and Proofs)

March 30, 2020

All of these properties of the discrete Fourier transform (DFT) are applicable for discrete-time signals that have a DFT. Meaning these properties of DFT apply to any generic signal x(n) for which an X(k) exists. (x(n) X(k)) where . Proofs of the properties of the discrete Fourier transform  


Computing Inverse DFT (IDFT) using DIF FFT algorithm – IFFT

January 10, 2020

For the faster calculation of inverse DFT (IDFT) we can use Decimation in Frequency (DIF) Fast Fourier Transform (FFT) with the butterfly diagram.

properties of z transform

Properties of Z-transform (Summary and Proofs)

March 29, 2020

There are some properties of the z-transform that can be used to simplify calculations. Let’s take a quick look at them & go on to prove them mathematically

Relation of Z-transform with Fourier and Laplace transforms

Relation of Z-transform with Fourier and Laplace transforms – DSP

December 31, 2019

The relationship between the z transform and laplace and fourier transforms is important for the designing of a digital filter. Let’s derive it.

IIR filters

What is an Infinite Impulse Response Filter (IIR)?

One of the two main digital filter types, the Infinite Impulse Response (IIR) filter is a major part of any DSP curriculum. Let’s take an in-depth look into what it is.

IIR filter design - approximation of derivates method

Approximation of derivatives method to design IIR filters

January 1, 2020

The backward difference method (aka approximation of derivates method) is one of the main ways to get a digital IIR filter from an analog filter.

FIR vs IIR filters

Difference between Infinite Impulse Response (IIR) & Finite Impulse Response (FIR) filters

December 22, 2019

IIR vs FIR is an evergreen distinction in DSP. Both these filter types have their advantages and disadvantages & you’ll need to know them to make a choice.

filter approximation - Chebyshev, butterworth, elliptic

Filter Approximation and its types – Butterworth, Elliptic, and Chebyshev

March 2, 2020

We can’t really get our hands on an ideal filter. However, we can get close to the parameters of an ideal filter. These three methods: Butterworth, Elliptic, and Chebyshev offer us three filters that come close to some of the parameters of an ideal filter. Check them out. They are pretty important in Digital Signal Processing.


Fourier series method to design FIR filters

March 18, 2020

We can use the concepts of Fourier series to design FIR filters by applying the methods to the frequency response of the filters we desire. Though it is short and easy to understand, this method comes with the back draw of Gibb’s phenomena.

Quantization of filter coefficients in digital filter design

Quantization of filter coefficients in digital filter design

December 21, 2019

The practical designing of filters requires the coefficients of the filter’s transfer equation to be quantized. Let’s see how the quantization is acheived.

Quantization in DSP – Truncation and Rounding

January 9, 2020

Rounding and Truncation are two easy methods to quantize a filter coefficient in digital signal processing. Let’s see a simple explanation of the two.

Limit Cycle Oscillation in recursive systems

Limit Cycle Oscillation in recursive systems

January 1, 2020

Limit cycle oscillations are an unwanted implication of finite-word length effects in an IIR filter. These arise due to inherent system quantizations.

DSP mcqs quiz and interview questions

Digital Signal Processing Quiz | MCQs | Interview Questions

March 20, 2020

This DSP quiz is crafted to test your skills in the fundamental concepts of digital signal processing taught in this course. Upon clearing this quiz, you will gain access to the final certification quiz. Please ensure that you are signed in before attempting the quiz.