%A P R Patnaik
%O Copyright of this artiocle belongs to Elsevier Science.
%J Process Biochemistry
%T Further enhancement of fed-batch streptokinase yield in the presence of inflow noise by coupled neural networks
%X Noise carried by the feed stream is a common feature of large-scale bioreactor operations. This noise may be modelled by a set of time-dependent Gaussian distributions. Recent studies have shown that neither unfiltered nor completely filtered noise is desirable. The best performance requires optimally filtered noise. A previous publication in this journal showed that streptokinase (SK) activity in a fed-batch fermentation can be improved substantially through controlled static filtering. Later work with ?-galactosidase showed that dynamic filtering by means of a neuralnetwork was superior, especially when it was coupled to a neural filter. That concept has been applied to SK. Coupling of two neuralnetworks increased the peak SK activity (in g/l) by 42% over that for a noise-free feed whereas the improvement with a static filter was 22%
%N 2
%K Streptokinase fermentation; Inflownoise; Neural filtering; Neural control
%P 145-151
%V 37
%D 2001
%I Elsevier Science
%R doi:10.1016/S0032-9592(01)00190-X
%L open869