Filtering out disturbances from transmitted or recovered measurement signals is one of the most important tasks of analog and digital signal processing for many decades. Removing of specific disturbances, having form of separate pulses (impulsive disturbances), requires specific algorithms because of very wide spectra of such pulses. The use of median procedures, especially of weighted medians, is particularly effective in such filtering procedures. According to the applied algorithm, signal samples, which include disturbances, are eliminated and replaced by some values resulting from neighbouring nondisturbed samples. The optimum weights of median filter depend on signal shape of deterministic signals. An analysis of frequency responses of medians is given in the contribution.

Weight filtration is one of the methods for weakening the effect of noise exerted on dis-crete signals. The wider is the weight window, the higher is the filtration quality. However, weight fil-tration produces an undesirable side effect, namely a certain number of samples relative to the input is lost. This may be attributed to the concept of weight filtration itself. The number of lost samples is the greater, the wider is the weight window. So, the desire to get a well-filtered signal comes into conflict with the number of samples being lost by virtue of filtration. In the paper an approach is suggested that enables the sample losses occurring during the weight filtration to be reduced.

Voltage to frequency converter (VFC) is an oscillator whose frequency is linearly proportional to control voltage. In this paper, the New Synchronous Voltage to Frequency Converter (NSVFC) or "sigma delta" (Σ-Δ) voltage to frequency converter is described. This NSVFC works similarly as conventional synchronous voltage to frequency converter (SVFC), but it has a better frequency spectral property then other SVFC and therefore it is possible to used as fractional frequency divider and also building block in fractional phase locked loop (PLL). An experimental NSVFC was constructed and simulated to verify operation of the converter. Analysis and prototype of NSVFC is described.

The main product of the DFT algorithms is the amplitude frequency spectrum while the phase frequency spectrum calculation is mainly unwanted. However, this part becomes relevant in the cases, in which the spectral lines have to be considered as vectors. Since the data record, from which the frequency spectrum is calculated, is usually acquired by non-coherent sampling, a problem of the correct phase determination appears. Time windows minimise the leakage in the amplitude frequency spectrum; their effect on the phase frequency spectrum is unclear. Moreover, the phase of each frequency depends on its initial phase and it varies in every data record, which is often undesired. One possibility of how to exactly express the phases of higher harmonic components is described in this paper.

If the RMS value is gained by digital processing of sequence of signal samples, both uncertainty and bias of the measured value depend on the algorithm used. Since in practice signal sampling is usually non-coherent, leakage occurs in signal DFT spectrum and definition of the RMS of periodic signals in time domain is violated. The paper compares three different DSP algorithms of RMS measurement by non-coherent sampling from the point of view of measurement bias and uncertainty for various leakage levels and data window used. Results of simulations and example of measurement are evaluated for monofrequency signals. For non-coherent signal sampling a new and effective approach to RMS value measurement in time domain, a new method of finding exact signal frequency (different from those of DFT grid) based on two DFT phase spectra computation, and a method of automatic RMS value bias correction in frequency domain are presented. The reported results can easily be extended to multifrequency signals.