Introduction - If you have any usage issues, please Google them yourself
Power spectrum estimation is the use of a finite length data to estimate the power spectrum of the signal, widely used in various fields. Power spectrum estimation is divided into classic and modern spectral estimatio n. Commonly used methods of classical periodogram spectrum estimation method, the relevant law, the cycle graph Improvement Act, commonly used in modern spectral estimation methods have maximum entropy spectral estimation, AR model, MA model, ARMA model. Classical spectral estimation applied to signal a long sequence, its main drawback is the fluctuation power spectrum describing digital signature variance performance is poor, the frequency resolution is low, modern spectral estimation applied to signal short sequences designed to improve spectral estimation resolution, and The analysis applied to real seismic data spectrum.