Explore MATLAB source code curated for "SNR" with clean implementations, documentation, and examples.
MATLAB implementation for dynamic performance analysis of high-speed ADCs, featuring calculations for SNR, SINAD, ENOB, THD, and SFDR metrics with frequency-domain amplitude curve visualization.
A MATLAB source code implementation that performs SNR to Eb/N0 conversion with additional capabilities for Bit Error Rate (BER) and Symbol Error Rate (SER) calculations, including comprehensive plotting functionality for performance analysis.
Implementation of MUSIC algorithm in array signal processing with performance simulations under varying SNR, number of array elements, and snapshot counts. Original research with MATLAB code examples demonstrating covariance matrix estimation, eigenvalue decomposition, and spatial spectrum computation.
BER vs SNR plot analysis in Rayleigh fading channel using maximal ratio combining technique for MIMO systems, including code implementation considerations for signal combining algorithms
Overview of common beamforming criteria including SNR, MSE, and LCMV approaches for signal+interference+noise environments, featuring null placement in interference directions with implementation considerations.
Image Processing Features: Computing Mean Square Error (MSE), Signal-to-Noise Ratio (SNR), Peak Signal-to-Noise Ratio (PSNR), and Generating Quantized Images with Algorithm Explanations and Key Function Descriptions
Comparative analysis of Bit Error Rate versus Signal-to-Noise Ratio performance metrics for AWGN and Rayleigh fading channel models
A Graphical User Interface (GUI) for calculating Mean Square Error (MSE), Signal-to-Noise Ratio (SNR), and Peak Signal-to-Noise Ratio (PSNR) metrics with code-based implementation insights.
Wavelet denoising is an adaptive thresholding algorithm that achieves superior signal-to-noise ratio (SNR), making it one of the most effective denoising methods currently available. The implementation typically involves thresholding wavelet coefficients using methods like soft or hard thresholding.
FFT-based ADC dynamic performance testing methodology including SNR, ENOB, and other key parameters, implemented according to IEEE standard testing procedures. Supports data loading from files for comprehensive analysis with code implementation details.