The implementation of complex information processing systems requires dierent methods for validation on dierent levels of abstraction. Direct observation of a set of system parameters is necessary to detect possible implementation faults and for validation. On the uppermost level of abstraction, the observation of the behavior of a whole system is a building block of methods for the validation of an implementation. The goal of realization a technical system is to build a complex structure based on simpler components of well known behavior which interact among themselves. It depends on the coupling between those components, how complex the behavior of the resulting system becomes. The presented method of learn trajectories, introduced in the context of backpropagation neural networks, visualizes the behavior of multiple parameters for the systems point of view. This contribution illustrates the functionality and application of learn trajectories by dierent examples. Keywords: Learn..
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