Abstract
Using model and real signals, the possibility and appropriateness of low-frequency component (trend) filtering using singular spectrum analysis (SSA) based on principal component analysis is considered. The real signals are represented by human breathing curves obtained after processing of UWB (ultrawideband) impulse signals using the principal component analysis. It has been shown experimentally that the use of the SSA makes it possible to suppress an interfering trend down to 18 dB.
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