Explore MATLAB source code curated for "相位" with clean implementations, documentation, and examples.
This MATLAB m-file solves the Schrödinger equation while incorporating bandwidth frequency and phase offset parameters, generating comprehensive 3D visualizations of the wave function evolution.
Modulation information in communication signals is embedded in variations of instantaneous amplitude, phase, and frequency, with different signals exhibiting unique spectral characteristics. By extracting statistical parameters from instantaneous amplitude, phase, frequency, and spectral features, various communication signals can be identified. Commonly, transformations are applied to instantaneous amplitude, phase, frequency, and power spectral density to derive discriminative feature parameters. In practice, this involves algorithms like Hilbert transform for instantaneous attributes calculation and Fourier analysis for spectral feature extraction.
Generating symmetric 16QAM, 64QAM, and 256QAM constellation diagrams to visualize signal amplitude and phase characteristics, including implementation approaches for plotting modulation schemes.
Design approach for Quadrature Mirror Filters starting from fundamental principles, with code-enabled observation and analysis of phase and magnitude characteristics through practical implementation.
Implementation of image processing in the frequency domain using Fourier transform techniques, comparing differences between image restoration from magnitude and phase components, with successful debugging and validation
A comprehensive program for partial discharge signal analysis, implementing algorithms to generate 3D spectrograms displaying discharge count, phase angle, and discharge magnitude relationships with signal processing techniques.
Hanning window FFT interpolation algorithm for calculating harmonic amplitude, frequency, and phase, requiring input parameters of sampling frequency and FFT length. This method improves spectral leakage reduction and provides accurate harmonic parameter estimation through windowing and interpolation techniques.
Using MATLAB to analyze frequency domain characteristics of 2D signals and investigating phase and amplitude distortion through practical code implementations
Extracting seven instantaneous information-based features from signals: maximum value of zero-centered normalized instantaneous amplitude power spectral density, standard deviation of zero-centered normalized instantaneous amplitude absolute value, standard deviation of absolute value of instantaneous phase nonlinear component in zero-centered non-weak signal segments, standard deviation of instantaneous phase nonlinear component in zero-centered non-weak signal segments, standard deviation of absolute value of zero-centered normalized instantaneous frequency in non-weak signal segments, maximum value of normalized instantaneous frequency power spectral density in a signal segment, and a novel feature parameter based on different projection characteristics of QPSK and 16QAM signals on the XI axis.