Types of Spectrum Analysis
Broadly Spectrum Analysis can be divided into two parts.
- Continuous Spectrum Analysis:
Analyzes continuous-time signals using techniques like Fourier transform. - Discrete Spectrum Analysis:
Analyzes discrete-time signals using techniques like discrete Fourier transform (DFT) and its fast implementation, the fast Fourier transform (FFT).
Spectrum Analysis in Python
Spectrum analysis is a powerful technique used in signal processing to analyze the frequency content of signals. It finds applications in various fields such as telecommunications, audio processing, and vibration analysis. In this article, we’ll explore the fundamentals of spectrum analysis and how it can be implemented in Python.
Table of Content
- What is Spectrum Analysis?
- Types of Spectrum Analysis
- Principles of Spectrum Analysis
- How to do Spectrum Analysis?
- 1. Fast Fourier Transform (FFT)
- 2. Power Spectral Density (PSD)
- Applications of Spectrum Analysis