This repository contains code and resources for various digital signal processing (DSP) techniques and implementations. The code is organized into different folders, each representing a specific DSP concept or technique.

• Overview
• Folder Structure
• Usage
• Dependencies
• Contributing

This repository serves as a lab reference for understanding and implementing core digital signal processing concepts, including convolution, discrete Fourier transform (DFT), finite impulse response (FIR) filtering, and verification of the sampling theorem. Each folder contains code examples, scripts, and individual README files with theoretical explanations to aid understanding of the application and implementation of DSP techniques.

• DSP-Kit: Contains various DSP helper functions and utilities.
• FIR-Filter: Implements FIR filtering techniques, including added window functions.
• basic-test-signals: Scripts and examples for generating and analyzing basic test signals used in DSP.
• circular-convolution-using-linear: Demonstrates how to perform circular convolution using linear convolution methods.
• circular-convolution: Contains examples of circular convolution.
• dft: Implements discrete Fourier transform (DFT) and its properties.
• idft_code: Contains code for inverse discrete Fourier transform (IDFT).
• linear-convolution-using-circular: Demonstrates how to perform linear convolution using circular convolution methods.
• linear-convolution: Contains examples of linear convolution.
• overlap-add-save: Demonstrates the overlap-add and overlap-save methods for convolution.
• properties_of_dft: Explores and demonstrates the properties of DFT.
• verification-of-sampling-theorem: Contains code to verify the sampling theorem.

1. Clone this repository:

   git clone https://github.com/your-username/Digital-Signal-Processing-Laboratory.git

2. Navigate to the desired folder and refer to the individual README files for theoretical explanations and usage instructions for each DSP concept.

This repository uses MATLAB for all DSP code implementations. Make sure you have MATLAB installed on your system to run the scripts.

Contributions are welcome! Please open an issue to discuss any major changes or additions before submitting a pull request.

1. Fork the repository.
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes.
4. Commit your changes (git commit -m 'Add feature').
5. Push to the branch (git push origin feature-branch).
6. Open a pull request.