Explore MATLAB source code curated for "现代信号处理" with clean implementations, documentation, and examples.
Graduate-level modern signal processing assignment involving MATLAB implementations of Kalman and Wiener filters, including filter design, state-space modeling, and practical signal analysis techniques.
This represents the most widely adopted signal analysis methodology in modern signal processing! Common implementations include Fast Fourier Transform (FFT) algorithms, wavelet transforms, and spectral estimation techniques using MATLAB's signal processing toolbox functions like fft(), wavelet families, and pwelch() for power spectral density estimation.
Modern Signal Processing with Higher-Order Statistics - Implementation of Third-Order Cumulant Calculation Algorithm
MATLAB project files for modern signal processing, designed to facilitate comprehensive learning of contemporary signal processing techniques with practical code implementation examples.
This MATLAB implementation demonstrates several common harmonic retrieval techniques used in modern signal processing. The accompanying documentation includes theoretical backgrounds and algorithm explanations (covering Pisarenko and ARMA methods), experimental procedures with detailed MATLAB code implementation, and analysis of results.
Kalman Filter and Wiener Filter - Implementation Approaches and Applications in Signal Processing