Sharif Digital Repository

This paper addresses the problem of frame detection in orthogonal frequency-division multiplexing (OFDM) systems. Using fourth-order statistics, a novel approach is presented for detection of a preamble composed of two identical parts in the time domain. First, it is demonstrated that sufficient statistics for detection of a periodic preamble do not exist, and conventional methods are not optimal. Next, looking at the detection of a preamble from the viewpoints of hypothesis testing and classification, a new method is presented based on the idea that fourth-order statistics can increase class separability (between-class distance) and consequently improve detection performance. It is proven... 

Recently, a new data collection was initiated within the RedDots project in order to evaluate text-dependent and text-prompted speaker recognition technology on data from a wider speaker population and with more realistic noise, channel and phonetic variability. This paper analyses our systems built for RedDots challenge-the effort to collect and compare the initial results on this new evaluation data set obtained at different sites. We use our recently introduced HMM based i-vector approach, where, instead of the traditional GMM, a set of phone specific HMMs is used to collect the sufficient statistics for i-vector extraction. Our systems are trained in a completely phraseindependent way on...