  This paper presents a short evaluation about the integration of information
derived from wavelet non-linear-time-invariant (non-LTI) projection properties
using Support Vector Machines (SVM). These properties may give additional
information for a classifier trying to detect known patterns hidden by noise.
In the experiments we present a simple electromagnetic pulsed signal
recognition scheme, where some improvement is achieved with respect to previous
work. SVMs are used as a tool for information integration, exploiting some
unique properties not easily found in neural networks.
