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Tarang-Tantra

तरङ्गतन्त्र — The System of Waves

Welcome to Tarang-Tantra, a comprehensive resource and toolkit dedicated to the science and art of Signal Processing. Our goal is to explore, understand, and implement a wide range of signal processing techniques that drive modern-day applications, from audio processing and image analysis to communications and beyond.

In Sanskrit, Tantra (तन्त्र) conveys multiple meanings that align well with concepts like technique, methodology, system, or even processing. Traditionally, Tantra refers to a structured set of practices, methods, or techniques, often applied systematically to achieve a particular outcome or understanding.

In the context of Tarang-Tantra:

  • Tarang means wave or signal.
  • Tantra here can imply a systematic technique or method, which fits perfectly with the concept of signal processing as a structured method for analyzing and interpreting signals. So, Tarang-Tantra effectively translates to Signal Processing or The System of Signal Techniques.

📜 Overview

This repository embodies a systematic approach to analyzing, transforming, and interpreting waves and signals.

This repository is designed for:

  • Students and researchers seeking foundational concepts and implementations.
  • Engineers and developers looking for practical algorithms and code.
  • Enthusiasts who want to dive into the science behind sound, vision, and communications.

✨ Key Features

  • Signal Analysis: Time-domain and frequency-domain analysis techniques.
  • Noise Reduction: Methods for signal denoising and enhancement.
  • Machine Learning in Signal Processing: Integrating machine learning models for predictive and classification tasks in signal contexts.

Why?

Tarang-Tantra is more than a repository; it’s a purposeful project inspired by the concept of Ikigai — the intersection of passion, mission, profession, and vocation in signal processing. The approach combines:

  • Diverse Domain Applications:

    • Sleep Analysis
    • Medical Diagnostics
    • Financial Forecasting
    • Sensor Data Interpretation
    • Music and Speech Processing

  • Mathematical Foundations:

    • Techniques like Wavelets and Fourier Transforms to analyze and interpret signals effectively.

  • Technical Approaches:

    • A spectrum of methods, from rule-based processing to advanced AI/ML techniques.
    • Support for time-series analysis, signal sequences, and pattern recognition.

  • Specific Knowledge (by Naval Ravikant):

    • Unique fusion of Yoga Nidra and AI-driven signal processing to explore wellness and mindfulness applications.

  • Future Goals:

    • Develop talks, training sessions, and micro-SaaS solutions.
    • Design wearable technology for continuous signal monitoring and interpretation.
    • Enable passive income opportunities by building products that generate ongoing value.

Tarang-Tantra is crafted to serve as a comprehensive toolkit, an educational resource, and a platform for innovative products, all at the intersection of modern signal processing and meaningful application.

🛠️ Getting Started

Prerequisites

To make the most of Tarang-Tantra, ensure you have:

  • Python 3.8+ installed
  • Essential libraries: numpy, scipy, matplotlib, librosa, and sklearn

Installation

Clone the repository and install the necessary dependencies:

git clone https://github.com/yourusername/Tarang-Tantra.git
cd Tarang-Tantra
pip install -r requirements.txt

📂 Repository Structure

  • /src: Core algorithms and implementations.
  • /examples: Jupyter notebooks and scripts demonstrating use cases.
  • /docs: Documentation for each module, including theoretical background.
  • /tests: Unit tests to ensure accuracy and robustness of code.

📘 Documentation

Comprehensive documentation is available in the /docs folder, including:

  • Theoretical Concepts: Detailed explanations of each signal processing technique.
  • Code Examples: Step-by-step tutorials on implementing and using algorithms.
  • Applications: Practical applications in fields like audio, image, and communication.

🚀 Usage

To get started with Tarang-Tantra, you can run any example notebook in the /examples folder:

python examples/basic_signal_analysis.py

Example: Basic Signal Filtering

Here’s a simple example of using Tarang-Tantra to filter a noisy signal:

import numpy as np
from src.filters import apply_lowpass_filter

# Generate a sample noisy signal
fs = 500  # Sampling frequency
t = np.linspace(0, 1, fs)
signal = np.sin(2 * np.pi * 50 * t) + 0.5 * np.random.randn(fs)

# Apply a lowpass filter
filtered_signal = apply_lowpass_filter(signal, cutoff=30, fs=fs)

📈 Roadmap

Planned enhancements include:

  • Motif identification: repeated patterns
  • Anomaly detection:
  • Matrix profile: stumpy, sax
  • Deep Learning Integration: Using neural networks for classification and regression tasks on signals.

Notes

Here at

References

Signal Processing

Matrix Profile, SAX, Stumpy

Sleep Analysis

Yoganidra

Companies

🤝 Contributing

Contributions are welcome! Feel free to submit issues, fork the repository, and make pull requests. Please refer to the CONTRIBUTING.md for more guidelines.

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

💬 Contact

For questions, discussions, or collaborations, feel free to reach out.

Embark on the journey through the Technique of Waves with Tarang-Tantra!