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https://github.com/mdlmab/fouriertransform

Fourier transform in MATLAB and Python, and its applications in digital signal processing and image processing.
https://github.com/mdlmab/fouriertransform

digitalprocessing fouriertransform imageprocessing matlab python3

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Fourier transform in MATLAB and Python, and its applications in digital signal processing and image processing.

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README

          

# **Fourier Transform Learning Journey** 📊

Welcome to my **Deep Learning** repository! 🐒

This repository serves as a documentation of my personal journey in mastering the **Fourier Transform**, a foundational mathematical tool widely used in engineering, data science, and signal processing.
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## **Overview** 🌟

The **Fourier Transform** is a powerful technique that allows us to analyze signals in the frequency domain, revealing how complex signals can be decomposed into simpler sinusoidal components. It has a wide range of applications in fields such as:

- **Signal Processing**: Filtering, compression, and noise reduction.
- **Data Analysis**: Spectral analysis of time series data.
- **Image Processing**: Compression techniques (e.g., JPEG) and feature extraction.
- **Control Systems**: Stability and frequency response analysis.
- **Audio and Speech**: Equalization, synthesis, and noise cancellation.

This repository contains structured **notes, tools, and experiments** that I develop as I progress in my studies.

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## **What You'll Find in This Repository** 📁

1. **Learning Notes**: Summaries and explanations of key Fourier Transform concepts.
2. **Practical Tools**: Scripts and utilities for performing Fourier analysis (Matlab/Python-based).
3. **Experiments**: Step-by-step projects that demonstrate the use of Fourier Transform in real-world problems.

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## **Goals of the Repository** 🎯

- To **document my learning process** as I explore the theory and applications of the Fourier Transform.
- To create a **reference hub** for anyone interested in signal and frequency analysis.
- To share **practical implementations** and insights gained through experimentation and personal projects.

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## **Current Status** 🚧

I have started my learning journey with resources like a course on **Udemy**. The focus is currently on building a solid theoretical foundation and gradually moving into practical applications using tools like **Python** and libraries such as:

- **NumPy**: For numerical analysis.
- **Matplotlib**: For visualizing signals and frequency components.
- **SciPy**: For advanced signal processing tasks.

## 🐒🍌🐒🍌🐒🍌🐒🍌🐒🍌🐒🍌