MATLAB Code Implementation for Signal-to-Noise Ratio (SNR)

Signal-to-Noise Ratio (SNR) is a fundamental concept widely used in signal processing and communication fields. It serves as a key metric for evaluating signal quality by comparing the energy of the signal against the intensity of the noise. The SNR calculation formula divides the signal energy by the noise power, yielding a numerical value where higher values indicate better signal quality. Through SNR analysis, we can better understand signal composition and characteristics, enabling more precise signal processing and communication system design. In MATLAB implementation, SNR calculation typically involves: 1. Signal power estimation using functions like mean(x.^2) for time-domain signals or bandpower() for frequency-domain analysis 2. Noise power calculation through methods such as var(noise) or measuring power in signal-free segments 3. SNR computation via 10*log10(signal_power/noise_power) for decibel scale Key functions include: fft() for frequency analysis, filter() for noise reduction, and snr() from Signal Processing Toolbox for direct measurement.