Explore MATLAB source code curated for "信噪比" with clean implementations, documentation, and examples.
Curve plots generated by multiple spatial spectrum estimation algorithms when incident signal angles are set at -22°, 6°, and 18° under different signal-to-noise ratio scenarios, with implementation approaches including MUSIC, Capon beamforming, and ESPRIT methods.
Performing spectral analysis on ADC sampled signals to compute critical parameters including Signal-to-Noise Ratio (SNR) and Effective Number of Bits (ENOB), with MATLAB/Python code implementation references
Classic grayscale images used for SNR, PSNR, and MSE measurements, featuring standard implementation approaches for image quality assessment algorithms
This project provides a MATLAB-based simulation of Reed-Solomon (RS) codes, including comprehensive error correction performance analysis and visualization of Bit Error Rate (BER) versus Signal-to-Noise Ratio (SNR) characteristics.
Implementation of FFT-based non-coherent accumulation pseudo-code acquisition with detection probability calculation across various signal-to-noise ratio conditions, featuring signal processing workflow and performance analysis algorithms.
Using MATLAB to generate and visualize linear frequency modulation signals in time-domain, performing spectral analysis, and investigating the impact of sampling frequency and signal-to-noise ratio on frequency spectrum characteristics.
Implementation of QPSK modulation simulation with BER (Bit Error Rate) vs SNR (Signal-to-Noise Ratio) curve plotting using MATLAB's communication toolbox functions
Three complex sinusoidal signals with SNR values of SNR1=30dB, SNR2=30dB, and SNR3=27dB were analyzed using an MVDR method based on singular value decomposition (SVD). The simulation employed 1000 signal samples and a 4-tap FIR filter to estimate the power spectral density function. The implementation involves covariance matrix construction, eigenvalue decomposition, and adaptive weight calculation for spectral estimation.
MATLAB implementation of Jafarkhani's differential space-time block code comparing SER and BER performance across varying SNR ratios using 2-transmit 1-receive configuration in Rayleigh fading channel
The Log Spectral Amplitude Minimum Mean Square Error (LSA-MMSE) speech enhancement algorithm incorporates voice activity detection (VAD) to further improve signal-to-noise ratio (SNR) and delivers excellent noise suppression performance. This algorithm is particularly effective for various types of stationary noise environments.