Techniques for developing low-complexity, robust Digital Signal Processing (DSP) algorithms with low-power consumption have become increasingly important. This thesis explores a framework, discrete-time randomized sampling, which allows the design of algorithms that meet some desired complexity, robustness or power constraints. Three distinct sampling schemes are presented based on randomized s...

This paper deals with estimation of probabilities of rare events in static simulation models using a fast adaptive two-stage procedure based on importance sampling and Kullback-Liebler’s cross-entropy (CE). More specifically, at the first stage we estimate the optimal parameter vector in the importance sampling distribution using CE, and at the second stage we estimate the desired rare event pr...

the current study aims to identify and examine the effect of market orientation, management innovation and technological innovation on organizational performance. the current research was conducted using descriptive- correlational methodology. the population of the current research included pharmaceutical companies throughout the country. using simplerandom sampling method and cochran formula, ...

the main purpose of this study was to identify and analyze the mechanisms of small and medium enterprises (smes) development in qazvin province. the study is an applied quantitative research. the data was collected using a descriptive-survey method. the statistical population of the study consisted of managers in charge of smes in qazvin province.  93 people were selected as the sample by using...

Sampling is a powerful and popular way to tackle problems for which exact inference is computationally intractable. We propose a novel sampling scheme based on Low Density Parity Check (LDPC) codes which works for any distribution over a finite alphabet. Compared to existing methods such as Markov Chain Monte Carlo (MCMC) Methods, the proposed scheme offers a different trade-off among various f...