Superimposing Specified Noise onto Signal with Sampling Frequency Calibration

MATLAB 755B 251 views 0 downloads 1 credits
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Resource Overview

Superimposing specified noise onto a target signal using the standard NOISEX-92 noise database. The database contains various noise types including white noise, office noise, factory noise, vehicle noise, and tank noise. Signal processing applications often require noise superposition from the database, but sampling frequency mismatch between noise and clean signals necessitates calibration through resampling techniques before proper integration.

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In signal processing workflows, we frequently need to superimpose specified noise types onto target signals. The standard NOISEX-92 noise database provides a comprehensive collection of noise profiles, including white noise, office noise, factory noise, vehicle noise, and tank noise among others. However, the sampling frequency of noise samples typically differs from that of the clean signal, requiring sampling frequency calibration through resampling algorithms before proper superposition. Implementation typically involves using signal processing functions like resample() or interp1() in MATLAB to align sampling rates, followed by amplitude adjustment and additive mixing of the noise signal onto the target signal while maintaining appropriate signal-to-noise ratios.

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