Bandpass sampling algorithm is effectively adopted to obtain the digital signal with significantly reduced sampling rate for a single radio frequency(RF) signal. In order to apply the concept to multiple RF signals, we propose bandpass sampling algorithms with the normal and the inverse placements since we are interested in uniform order of the spectrum in digital domain after bandpass sampling...

This paper provides an overview of the effects of timing jitter in audio sampling analog-to-digital converters (ADCs), i.e. PCM (conventional or Nyquist sampling) ADCs and sigma-delta (Σ∆) ADCs. Jitter in a digital audio is often defined as shortterm fluctuations of the sampling instants of a digital signal from their ideal positions in time. The influence of the jitter increases particularly w...

The Shannon/Nyquist sampling theorem specifies that for lossless capture of a signal, one must sample at least two times faster than the largest frequency content of the signal. In many applications, the Nyquist rate is so high that too many samples result, making compression a necessity prior to storage or transmission. But if the signal has a sparse representation in some domain, the novel id...

In many practical applications of digital signal processing sampling rate conversion is a problem. The process of converting a signal from a given rate to a different rate is called Sampling Rate Conversion. Sampling rate conversion process may be based on an integer or a rational factor. In this paper, the process of rational sampling rate conversion is discussed in detail. Along with this, a ...

This paper describes Data-Weighted-Averaging (DWA) algorithms for multibit complex bandpass ∆ΣAD modulators with arbitrary signal bands. In most of bandpass ∆ΣAD modulators, their sampling frequency is chosen as four times of the center frequency of their signal band in order to simplify the following digital filter design. But with this relationship, their performance would be limited by the t...

A new sampling theorem on the sphere has been developed recently, reducing the number of samples required to represent a band-limited signal by a factor of two for equiangular sampling schemes. For signals sparse in a spatially localised measure, such as in a wavelet basis, overcomplete dictionary, or in the magnitude of their gradient, for example, a reduction in the number of samples required...

This paper describes a power spectrum analyzer whose bandwidth is not limited by the mean sampling time. The procedure is based on the estimation of the spectral components of the autocorrelation function of the input signal through the simultaneous random sampling of the given input signal and its randomly “delayed copy.” The samples are therefore randomly taken in a double-dimension space, ti...

Propagation of radio occultation (RO) signals through the lower troposphere results in high phase acceleration and low signal to noise ratio signal. The excess Doppler estimation accuracy in lower troposphere is very important in receiving RO signals which can be estimated by sliding window spectral analysis. To do this, various frequency estimation methods such as MUSIC and ESPRIT can be adopt...

Many communication systems are bandwidthexpanding : the transmitted signal occupies a bandwidth larger than the symbol rate. The sampling theorems of Kotelnikov, Shannon, Nyquist et al. [1] shows that in order to represent a bandlimited signal, it is necessary to sample at what is popularly referred to as the Shannon or Nyquist rate. However, in many systems, the required sampling rate is very ...

Compressive sampling (CS) is aimed at acquiring a signal or image from data which is deemed insufficient by Nyquist/Shannon sampling theorem. Its main idea is to recover a signal from limited measurements by exploring the prior knowledge that the signal is sparse or compressible in some domain. In this paper, we propose a CS approach using a new total-variation measure TVL1, or equivalently TV ...