  The characterization of multicomponent signals with a particular emphasis on
musical and communication signals is one of the problems studied in the
dissertation. In order to provide an efficient analysis of the multicomponent
signals, the possibility to separate signal components is observed. The
procedure for decomposition and classification of the signal components whose
energy and physical characteristics differ in the time-frequency domain is
proposed in this work. A special focus in the dissertation is on the
application of the compressive sensing approach in multicomponent signals. The
compressive sensing method becomes popular in the field of signal processing
until recently, and its application in various fields can increase the
acquisition and transmission speed, reduce the complexity of devices, and
reduce energy consumption. The procedure that applies the compressive sensing
in the classification of the wireless communication signals is proposed. The
algorithms for reconstruction of the compressive sensed signals are intensively
developing, and therefore special emphasis in the dissertation is devoted to
the hardware implementation of one of the algorithms for sparse signal
reconstruction.
