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

Practical DSP in Python : Over 70 examples, FFT,Filter Design, IIR,FIR, Window Filters,Convolution,Linear Systems etc

Created by: Israel Gbati
Embedded Firmware Engineer

Created by: BHM Engineering Academy
21st Century Engineering Academy

What Will I Learn?

• Develop the Convolution Kernel algorithm in Python
• Design and develop 17 different window filters in Python
• Develop the Discrete Fourier Transform (DFT) algorithm in Python
• Design and develop Type I Chebyshev filters in Python
• Design and develop Type II Chebyshev filters in Python
• Develop the Inverse Discrete Fourier Transform (IDFT) algorithm in Pyhton
• Develop the Fast Fourier Transform (FFT) algorithm in Python
• Perform spectral analysis on ECG signals in Python
• Design and develop Windowed-Sinc filters in Python
• Design and develop Finite Impulse Response (FIR) filters in Python
• Design and develop Infinite Impulse Response (IIR) filters in Python
• Develop the First Difference algorithm in Python
• Develop the Running Sum algorithm in Python
• Develop the Moving Average filter algorithm in Python
• Develop the Recursive Moving Average filter algorithm in Python
• Design and develop Butterworth filters in Python
• Design and develop Match filters in Python
• Design and develop Bessel filters in Python
• Simulate Linear Time Invariant (LTI) Systems in Python
• Perform linear and cubic interpolation in Python

Requirements

• You will need just a good working computer for this course

Target audience

• People working in the field of signal processing
• University students taking classes in signal processing
• Python developers who wish to expand their skills
• People who want to understand signal processing practically and apply it to their respective fields.