Explore MATLAB source code curated for "高斯" with clean implementations, documentation, and examples.
Implementation and Performance Comparison of OFDM Symbol Synchronization Algorithms in Various Channel Environments including Gaussian and Multipath Channels
MATLAB implementation examples of diverse interpolation algorithms including: Lagrange interpolation, Aitken's interpolation method, Newton interpolation, Gaussian interpolation, Hermite interpolation, piecewise Hermite interpolation, spline interpolation, rational fraction interpolation, piecewise bilinear interpolation, bivariate three-point Lagrange interpolation, and piecewise bicubic Hermite interpolation with code implementation insights
Free MATLAB source code for adding different types of noise to images - Gaussian, salt and pepper, additive and multiplicative noise generation algorithms
This MATLAB program implements a comprehensive noise generator capable of producing Gaussian, salt-and-pepper, additive, and multiplicative noise types, and applying them to images for algorithm testing and analysis.
Essential kernel functions for SVM implementation, including four commonly used types: polynomial, linear, Gaussian (RBF), and sigmoid, with code implementation considerations
The primary frequency domain low-pass filters include Ideal, Butterworth, and Gaussian types, commonly implemented in digital signal processing for high-frequency attenuation.
This MATLAB program implements a versatile noise generator capable of creating Gaussian, salt-and-pepper, additive, and multiplicative noise types with customizable parameters for image processing applications.
ROC performance curve visualization for energy detection algorithm in Additive White Gaussian Noise (AWGN) channel with implementation insights.
Generating Gaussian white noise using MATLAB with visualization of time-domain waveform, autocorrelation function, and power spectrum density through complete signal processing workflow.
Application Background In analyzing filter bank-based OFDM systems, comprehensive time-frequency characterization of filter banks is essential, which requires specialized analysis programs. Common filters like Gaussian, IOTA, and EGF are frequently studied through comparative analysis with rectangular window functions in CP-OFDM systems. Key code implementations involve calculating time-frequency localization metrics and visualizing filter responses using MATLAB's signal processing toolbox. Key Technology From anti-ISI and anti-ICI perspectives, optimal energy concentration near time-frequency lattice points with minimal energy dispersion to adjacent lattices is desired. Time-Frequency Localization (TFL) serves as the primary metric for this characteristic. Algorithmically, TFL quantifies cross-correlation between filters through functions (instantaneous correlation/ambiguity/interference functions) and parameters (Heisenberg parameters/direction parameters). Python/Matlab implementations typically employ windowing techniques and Fourier transform operations for TFL computation.