SUMMARY In this paper we investigate the effects of different sampling operators on the performance of sparse reconstruction methods. The common paradigm in seismic data processing is to favor regular sampling. We will show, however, that regular sampling often hampers our data recovery efforts. Random sampling, on the other hand, can lead to algorithms where the reconstruction is almost perfec...

The new emerging theory of Compressive Sampling has demonstrated that by exploiting the structure of a signal, it is possible to sample a signal below the Nyquist rate and achieve perfect reconstruction. In this paper, we consider a special case of Compressive Sampling where the uncompressed signal is non-negative, and propose an extension of Non-negative Quadratic Programming—which utilises It...

a r t i c l e i n f o a b s t r a c t In this paper, we investigate level-crossing (LC) analog-to-digital converters (ADC)s in a competitive algorithm framework. In particular, we study how the level sets of an LC ADC should be selected in order to track the dynamical changes in the analog signal for effective sampling. We introduce a sequential LC sampling algorithm asymptotically achieving th...

Data compression capability of “Compressed sensing (sampling)” in signal discretization is numerically evaluated and found to be far from the theoretical upper bound defined by signal sparsity. It is shown that, for the cases when ordinary sampling with subsequent data compression is prohibitive, there is at least one more efficient, in terms of data compression capability, and more simple and ...

Sampling is the first step to convert an analogue optical signal into a digital electrical signal. The latter can be further processed and analysed by well-known electrical signal processing methods. Optical pulse sources like mode-locked lasers are commonly incorporated for all-optical sampling, but have several drawbacks. A novel approach for a simple all-optical sampling is to utilise the fr...

A problem of first-order bandpass sampling is that the indifferent disposition of the baseband spectrum may cause inconvenience in practical applications. To overcome it, we modify the first-order bandpass sampling theory according to the spectral arrangement of the sampled signal. We consider two situations on the arrangement of the shifted replicas of the bandpass signal spectrum: the normal ...

In Wireless Sensor Networks (WSN), the effective detection and reconstruction of the event signal is mainly based on the regulation of sampling and communication parameters used by the sensor nodes. The aim of this paper is to understand the effect of these parameters on the reconstruction performance of event signal in WSN. Theoretical analysis and results show that with proper selection of sa...

The application of a random sampling scheme in high-frequency digital lock-in amplifiers is proposed. This scheme allows reducing the sampling frequency with reduced aliasing effects. Analytical and numerical analyses that show the advantages and limitations of the proposed scheme are presented. Furthermore, experimental tests that validate the proposal are given. The maximum input-signal frequ...

A non-uniform additive pseudo-random sampling pattern (mainly proposed in the signal processing communities) can be used for performing an ‘alias-free signal sampling’ process. The carefully designed sampling scheme can mitigate the effects of aliasing and permit significant reductions in the average sampling frequency, leading to more efficient processor utilization. Despite the fact that the ...