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Practical implementations of wireless transmitters suffer from a large number of impairments such as quantization noise, sampling offset, phase noise, I/Q imbalance... which can be classified into systematic and non-systematic effects.
The influence, on the moving load identification, of practical aspects such as measurement noise, sampling frequency, a small number of measured response modes, a small number of measuring points, road surface roughness and non-uniform velocity or braking of vehicle is studied in simulations and experiment.
Therefore, it is important to understand how different levels of noise, sampling frequency, and time series length influence various estimates of entropy.
The purpose of this study was to examine how noise, sampling frequency and time series length influence various measures of entropy when applied to human center of pressure (CoP) data, as well as in synthetic signals with known properties.
Fold change, unusual ratio, univariate testing with correction for multiple experiments, ANOVA and noise sampling methods are reviewed and compared.
All the 100x100 measurements are disturbed by noise sampling from a standard normal distribution.
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Tidally induced ocean-depth variations lead to a loss of coherence between the noise sampled by the hydrophones [17].
and are additive noise samples.
sequence of complex noise samples.
with the filtered noise samples Ψk,m.
Similarly noise samples can be defined.
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