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All Projects → hukenovs → dsp-theory

hukenovs / dsp-theory

Licence: GPL-3.0 license
Theory of digital signal processing (DSP): signals, filtration (IIR, FIR, CIC, MAF), transforms (FFT, DFT, Hilbert, Z-transform) etc.

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lecturestutorialfpgadspnumpyfast-fourier-transformscipyconvolutionfftdigital-signal-processinglessonsfirnumpy-tutorialfinite-impulse-response

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Digital signal processing

Digital signal processing

Этот проект - базовые лекции по цифровой обработке сигналов (ЦОС) в виде тетрадок Jupyter Notebook. Это мои заметки по теоретическим аспектам и практическому применению задач ЦОС.

Материалы представлены с использованием библиотек на языке Python (numpy , scipy, matplotlib, seaborn etc). Основная информация взята из моих лекций, которые я, будучи аспирантом, читал студентам Московского Энергетического Института ("НИУ МЭИ"). Частично информация из этих лекций была использована на обучающих семинарах в Центре Современной Электроники, где я выступал в качестве докладчика. Кроме того, в эти лекции входит перевод различных статей, компиляция материалов из достоверных источников и литературы по тематике цифровой обработки сигналов, а также официальная документация по прикладным пакетам и встроенным функциям библиотек scipy и numpy языка Python.

Main information

Title Digital signal processing
Author Alexander Kapitanov
Language Python
Contact
Release 10 Jul 2019
License GNU GPL 3.0

List of lectures (Russian)

Install

  • Install anaconda (miniconda)
  • Create and activate virtual environment
  • Install python packages
  • Run jupyter notebooks via Jupyter server or JetBrains DataSpell
# Create conda environment and install needed packages
conda create -n "dsp_venv" python=3.9 -y
conda activate dsp_venv
pip install -r reqirements.txt
# Run jupyter notebook server and follow link from console
jupyter notebook

Requirements

numpy==1.21.2
scipy==1.7.1
matplotlib==3.4.3
seaborn==0.11.2
jupyter==1.0.0

Habr link

Release:

  • 2019/07/10.

License:

  • GNU GPL 3.0.
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