Time-frequency distributions (TFDs) are powerful tools for analysis of nonstationary signals, which allow us to observe signal energy distribution as a function of both time and frequency simultaneously. However, TFDs are often corrupted by artifacts, a mathematical byproduct of TFD quadratic nature. A method for artefact suppression is compressive sensing (CS) of signal ambiguity function (AF) in such a way to discard corrupted samples, and leaving only a small subset of artifact-free signal samples. However, in order to obtain a high-resolution TFD, one needs to solve a linear unconstrained optimization problem. In this paper, we analyse noise effect on TFD reconstruction based on various ℓ₁ norm algorithms for different sizes of CSAF regions of interest.

Signals with time-varying frequency content are generally best represented in the time frequency (TF) domain, with the components instantaneous frequency laws being their key nonstationary features. There are a number of methods for TF distribution calculation (TFD), however, most of them add unwanted artifacts, making the TFD interpretation more difficult. In this paper, we use a compressive sensing approach to suppress or completely eliminate those artifacts. Furthermore, a basis pursuit algorithm is employed for signal reconstruction in order to reduce resolution loss, which is a mayor obstacle of existing TFD design methods.

In this paper noise analysis of three different filter designs is performed. Voltage noise spectral density and RMS noise voltage in simply designed active RC, noise optimized active RC and switched capacitor (SC) filter design are calculated for fifth order Chebyshev low pass filter, with a cut-off frequency f _c =3.4kHz, and pass-band ripple α _max =-0.5dB. All three designs are realized as a cascade of two second order sections and one first order section. All filter analysis has been performed using MATLAB and SPICE program tools. Through the analysis it is shown that SC based filter has significantly lower noise when compared with active RC based filter.