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- W2046600760 abstract "Some finite energy, causal, real-valued signals are frequency analyzed using a fast Fourier transform (FFT). Computer generated additive white noise is combined with time-domain samples, and the analysis is repeated. It is shown that the combination of noise and aliasing can hide information when high frequency noise is folded over an interesting part of the frequency domain. Aliasing cannot be avoided in exploratory physics and engineering experiments and aliased noise can drown out real peaks in the signal frequency spectrum. Time-domain filtering techniques are discussed, but they cannot always recover these lost peaks. A new method is introduced in which the wavelet transform and its inverse are used to suppress high frequency noise prior to Fourier analysis. This method is useful in improving on experimental results when aliasing of high frequency noise presents a problem." @default.
- W2046600760 created "2016-06-24" @default.
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- W2046600760 date "1992-12-29" @default.
- W2046600760 modified "2023-09-23" @default.
- W2046600760 title "<title>Information-to-noise improvement in the frequency domain using the wavelet transform</title>" @default.
- W2046600760 doi "https://doi.org/10.1117/12.139008" @default.
- W2046600760 hasPublicationYear "1992" @default.
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