The focus of this paper is to consider the compressed sensing problem. It is stated that the compressed sensing theory, under certain conditions, helps relax the Nyquist sampling theory and takes smaller samples. One of the important tasks in this theory is to carefully design measurement matrix (sampling operator). Most existing methods in the literature attempt to optimize a randomly initiali...

As networks grow in complexity and scale, the importance of network performance monitoring and measurement also increases significantly. High data rates often lead to large amount of measurement results. Therefore, in order to prevent an exhaustion of the network resources and to reduce the measurement cost, a reduction of the collected data is required. A performance measurement method for est...

Three modifications are shown to improve resolution and reduce noise amplification in endoscopic imaging through multi-mode fiber using optimization-based reconstruction (OBR). First, random sampling patterns are replaced by sampling patterns designed to have more nearly equal singular values. Second, the OBR algorithm uses a point-spread function based on the estimated spatial frequency spectr...

Supporting sampling in the presence of joins is an important problem in data analysis. Pushing down the sampling operator through both sides of the join is inherently challenging due to data skew and correlation issues between output tuples. Joining simple random samples of base relations typically leads to results that are non-random. Current solutions to this problem perform biased sampling o...

OBJECTIVES There is a relationship between infant feeding method and maternal postpartum depression (PPD). This study was carried out in an Iranian population to compare the prevalence of PPD symptoms between breast feeding and non-breast feeding mothers for first time. METHODS Four health centers in Ahvas were selected by random sampling in 2009. At first 78 non-breast feeding mothers at two...

We propose the use of quasi-random sampling techniques for path planning in high-dimensional conng-uration spaces. Following similar trends from related numerical computation elds, we show several advantages ooered by these techniques in comparison to random sampling. Our ideas are evaluated in the context of the probabilistic roadmap (PRM) framework. Two quasi-random variants of PRM-based plan...

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...

In sampling theory, a wide variety of techniques is used to obtain efficient estimators for the population mean. The commonly used method to obtain the estimator for population mean is simple random sampling without replacement (SRSWOR) when there is no auxiliary variable available. There are methods that use the auxiliary information of the study characteristics. If there exists an auxiliary v...