Inferring mixed-culture growth from total biomass data in a wavelet approach
Rosu Barbus, Haret-Codratian
It is shown that the presence of mixed-culture growth in batch fermentation pro-cesses can be very accurately inferred from total biomass data by means of the wavelet analysis for singularity detection. This is accomplished by considering sim-ple phenomenological models for the mixed growth and the more complicated case of mixed growth on a mixture of substrates. The main quantity provided by the wavelet analysis is the H¨older exponent of the singularity that we determine for our illustrative examples. The numerical results point to the possibility that H¨older exponents can be used to characterize the nature of the mixed-culture growth in batch fermentation processes with potential industrial applications. Moreover, the analysis of the same data aﬀected by the common additive Gaussian noise still lead to the wavelet detection of the singularities although the H¨older exponent is no longer a useful parameter.
Fecha de publicación2006
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