Explore MATLAB source code curated for "信号频谱" with clean implementations, documentation, and examples.
This program implements both standard MUSIC algorithm and enhanced MUSIC method for signal spectral estimation, including detailed explanations of MUSIC principles and code implementation approaches for subspace decomposition and noise filtering.
1. Master spectral analysis methods for periodic signals using Fourier series and understand their physical significance. Learn implementation approaches for decomposing signals into frequency components using mathematical and programming techniques. 2. Deeply understand the concept of signal spectrum, analyze typical signal spectra, and master key properties of Fourier transform. Develop skills for implementing frequency domain transformations and spectral analysis algorithms.
Implementing the CLEAN Algorithm for Signal Spectrum Processing to Achieve Filtering Effects
Original algorithm implementation featuring six different power spectrum estimation techniques including FFT-based method, Periodogram, Welch's method, Short-Time Fourier Transform, parametric power spectrum estimation, and adaptive parametric approach. Each method includes corresponding visualization plots for comparative analysis, making this an excellent tool for learning signal processing and spectrum analysis. Available for download and study!
Implementation of Double-Sideband Suppressed-Carrier (DSB-SC) modulation and demodulation using MATLAB or similar software tools. The code generates and visualizes: (1) Original signal and its frequency spectrum; (2) Carrier signal waveform; (3) DSB-SC modulated signal and its spectrum; (4) Power spectral density of DSB-SC signal; (5) Coherently demodulated signal waveform. The implementation demonstrates key communication system concepts using signal processing functions like fft(), hilbert(), and modulation techniques.