The extremely high sampling rate is a challenge for ultra-wideband (UWB) communication. In this paper, we study the compressed sensing (CS) based impulse radio UWB (IR-UWB) signal detection and propose an IR-UWB signal detection algorithm based on compressive sampling matching pursuit (CoSaMP). The proposed algorithm relies on the fact that UWB received signal is sparse in the time domain. The ...

In software defined radio systems, placing the analog-todigital converter (ADC) near the antenna part in the block diagram of the receiver is desired to improve the flexibility of the system. The radio frequency (RF) sampling method, in which the received signal is sampled at the RF stage, realizes such structure. The undersampling is a potential method to sample the RF signal using the existin...

Analyzing physical phenomena using a computer inevitably requires to bridge between the continuous nature of the physical phenomena and the discrete nature of computers. This bridging is known as sampling. The continuous signal is sampled such that it is represented by a discrete set of samples. The sampling scheme used to discretize the signal is often irregular. This may be due to either the ...

Time-warped signal spaces have received recent attention in the research literature. Among the topics of particular interest are sampling of time-warped signals and signal analysis using warped analysis functions, including wavelets. This correspondence introduces a reproducing kernel (RK) structure for time-warped signal spaces that unifies multiple perspectives on sampling in such spaces.

An analogue to digital (AD) converter is described which may be used to transform a multichannel analyser into an analogue signal averager suitable for analysis of analogue signals in the frequency range from DC to typically 40 kHz and signal amplitudes in the millivolt to volt range. The AD converter operates on a triggered basis and is capable of sampling an analogue signal at a maximum rate ...

Fourier sampling algorithms exploit the spectral sparsity of a signal to reconstruct it quickly from a small number of samples. In these algorithms, the sampling rate is subNyquist and the time to reconstruct the dominate frequencies depends on the type of algorithm—some scale with the number of tones found and others with the length of the signal. The Ann Arbor Fast Fourier Transform (AAFFT) s...

An ubiquitous challenge in modern data and signal acquisition arises from the evergrowing size of the object under study. Hardware and power limitations often preclude sampling with the desired rate and precision, which motivates the exploitation of signal and/or channel structures in order to enable reduced-rate sampling while preserving information integrity. This thesis is devoted to underst...

A method to improve l1 performance of the CS (Compressive Sampling) for signals with known spectral energy density is proposed. Instead of random sampling, the proposed method selects the location of samples to follow the distribution of the spectral energy. Samples collected from three different measurement methods; the uniform sampling, random sampling, and energy equipartition sampling, are ...

The conventional approach to sampling signals or images follows the celebrated Shannon sampling theorem: the sampling rate must be at least twice the maximum frequency present in the signal (the so-called Nyquist rate). In fact, this principle underlies nearly all signal acquisition protocols used in consumer audio and visual electronics, medical imaging devices, radio receivers, and so on. In ...

The need of direct measure and monitoring of ultra-fast signal in the time domain is rapidly increasing, being of interest in a large number of applications such as ultra-fast communication, biophotonics, sensing, large systems synchronization, dynamic characterization and testing of new materials. In particular in the telecommunication field optical sampling can been exploited for high bit rat...