Signal Spectrum Estimation Using Various Methods

This original algorithm program implements six distinct methods for signal power spectrum estimation: FFT-based approach, Periodogram method, Welch's technique, Short-Time Fourier Transform (STFT), parametric power spectrum estimation, and adaptive parametric method. Each estimation method is accompanied by corresponding visualization plots, enabling clear comparison of their respective advantages and limitations. The implementation demonstrates key signal processing concepts through practical code examples, including windowing functions for Welch's method, overlap-add processing for STFT, and autoregressive modeling for parametric approaches. This serves as a powerful educational tool for studying signal processing fundamentals and spectrum analysis techniques. Welcome to download and learn!

The program provides multiple algorithmic implementations for signal power spectrum estimation. These include FFT-based spectral analysis, Periodogram with rectangular windowing, Welch's method with configurable segment overlap, STFT with time-frequency resolution control, parametric estimation using Yule-Walker equations, and adaptive parametric methods with real-time coefficient adjustment. Each algorithm generates comparative plots showing spectral resolution, variance characteristics, and computational efficiency. The code structure features modular design with separate functions for each method, allowing easy modification of parameters like FFT length, window types, and model orders. An ideal resource for understanding spectrum estimation trade-offs and algorithm implementation details in digital signal processing. Available for download and learning!