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Digital Signal Processing (DSP) From Ground Up™ in C

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  • 5,934 Students
  • Updated 2/2023
4.3
(849 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
7 Hour(s) 47 Minute(s)
Language
English
Taught by
Israel Gbati, BHM Engineering Academy
Rating
4.3
(849 Ratings)

Course Overview

Digital Signal Processing  (DSP)  From Ground Up™ in  C

Practical DSP in C : FFT, Filter Design, Convolution, IIR, FIR, Hamming Window, Linear Systems, Chebyshev filters etc

With a programming based approach, this course is designed to give you a solid foundation in the most useful aspects of Digital Signal Processing (DSP) in an engaging and easy to follow way. The goal of this course is to present practical techniques while avoiding  obstacles of abstract mathematical theories. To achieve this goal, the DSP techniques are explained in plain language, not simply proven to be true through mathematical derivations.

Still keeping it simple, this course comes in different programming languages and hardware architectures so that students can put the techniques to practice using a programming language or hardware architecture  of their choice. This version of the course uses the C programming language.


By the end of this course you should be able develop the Convolution Kernel algorithm in C, develop the Discrete Fourier Transform (DFT) algorithm in C, develop the Inverse Discrete Fourier Transform (IDFT) algorithm in C, design and develop Finite Impulse Response (FIR) filters in C, design and develop Infinite Impulse Response (IIR) filters in C, develop Windowed-Sinc filters in C, build Modified Sallen-Key filters,  build Bessel, Chebyshev and Butterworth filters, develop the Fast Fourier Transform (FFT) algorithm in C , even give a lecture on DSP and so much more. Please take a look at the full course curriculum.

Course Content

  • 10 section(s)
  • 92 lecture(s)
  • Section 1 Set up
  • Section 2 Getting started with gnuplot
  • Section 3 Signal Statistics and Noise
  • Section 4 Quantization and The Sampling Theorem
  • Section 5 Linear Systems and Superposition
  • Section 6 Convolution
  • Section 7 Fourier Transsform
  • Section 8 Complex Numbers
  • Section 9 Complex Fourier Transform
  • Section 10 Fast Fourier Transform (FFT)

What You’ll Learn

  • Be able to develop the Convolution Kernel algorithm in C
  • Be able able to develop the Discrete Fourier Transform (DFT) algorithm in C
  • Be able to develop the Inverse Discrete Fourier Transform (IDFT) algorithm in C
  • Be able to develop the Fast Fourier Transform (FFT) algorithm in C
  • Be able to perform spectral analysis on ECG signals in C
  • Be able to design and develop Windowed-Sinc filters in C
  • Be able to design and develop Finite Impulse Response (FIR) filters in C
  • Be able to design and develop Infinite Impulse Response (IIR) filters in C
  • Be able to develop the FFT Convolution algorithm in C
  • Be able to develop the First Difference algorithm in C
  • Be able to develop the Running Sum algorithm in C
  • Be able to develop the Moving Average filter algorithm in C
  • Be able to develop the Recursive Moving Average filter algorithm in C
  • Be able to develop signal statistical algorithms in C
  • Be able to build passive Low-pass and High-pass filters
  • Be able to build Modified Sallen-Key filters
  • Be able to build Bessel, Chebyshev and Butterworth filters
  • Understand all about Linear Systems and their characteristics
  • Understand how to synthesize and decompose signals
  • Understand the relationship between the delta function and the Impulse response
  • Be able to plot signals with gnuplot
  • Be able to give a lecture on Digital Signal Processing (DSP)
  • Be able to suppress noise in signals


Reviews

  • A
    Aino Koskimies
    4.0

    Since the resources have the complete code, the students are not forced to write the code themselves. Otherwise the course has been clear and I've learned a few things.

  • M
    Martin Damev
    4.5

    The DFT and iDFT section are well explained and I enjoy coding these examples.

  • G
    Ghrms80 ji
    4.0

    DSP 전반적인 내용을 빠르게 배울 수 있었습니다. 수학과 관련된 부분은 코딩하는데 필요한 정도의 내용만 언급하고 흐름만 다룹니다. 일부 코드는 수정이 필요하지만, 어렵지 않게 변경할 수 있었습니다.

  • N
    Ningaraj Sannagowdara
    4.5

    Nicely brought the course to make a person understand the digital signal processing and also time domain and frequency domain.

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