In this work, we developed a theoretical framework leading to misclassification of the final size epidemic data for the stochastic SIR (Susceptible-In</span></span><span style="font-family:Verdana;...In this work, we developed a theoretical framework leading to misclassification of the final size epidemic data for the stochastic SIR (Susceptible-In</span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">fective</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">-Removed), household epidemic model, with false negative and false positive misclassification probabilities. Maximum likelihood based algorithm is then employed for its inference. We then analyzed and compared the estimates of the two dimensional model with those of the three and four dimensional models associated with misclassified final size data over arrange of theoretical parameters, local and global infection rates and corresponding proportion infected in the permissible region, away from its boundaries and misclassification probabilities.</span></span></span><span><span><span style="font-family:""> </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">The adequacies of the three models to the final size data are examined. The four and three-dimensional models are found to outperform the two dimensional model on misclassified final size data.展开更多
A polynomial-rooting based fourth-order cumulant algorithm is presented for direction-of-arrival(DOA) estimation of second-order fully noncircular source signals, using a uniform linear array(ULA). This algorithm ...A polynomial-rooting based fourth-order cumulant algorithm is presented for direction-of-arrival(DOA) estimation of second-order fully noncircular source signals, using a uniform linear array(ULA). This algorithm inherits all merits of its spectralsearching counterpart except for the applicability to arbitrary array geometry, while reducing considerably the computation cost.Simulation results show that the proposed algorithm outperforms the previously developed closed-form second-order noncircular ESPRIT method, in terms of processing capacity and DOA estimation accuracy, especially in the presence of spatially colored noise.展开更多
This paper propose a computerized method of magnetic resonance imaging (MR/) of brain binarization for the uses of preprocessing of features extraction and brain ab- normality identification. One of the main problem...This paper propose a computerized method of magnetic resonance imaging (MR/) of brain binarization for the uses of preprocessing of features extraction and brain ab- normality identification. One of the main problems of MR/ binarization is that many pixels of brain part cannot be cor- rectly binarized due to extensive black background or large variation in contrast between background and foreground of MR/. We have proposed a binarization that uses mean, vari- ance, standard deviation and entropy to determine a thresh- old value followed by a non-gamut enhancement which can overcome the binarization problem of brain component. The proposed binarization technique is extensively tested with a variety of MR/and generates good binarization with im- proved accuracy and reduced error. A comparison is carried out among the obtained outcome with this innovative method with respect to other well-known methods.展开更多
Channel estimation and synchronization are crucial problems in coherent ultra wideband (UWB) receiver designs. A joint maximum-likelihood (ML) and minimum-mean-square-error (MMSE) channel esti- mation scheme was...Channel estimation and synchronization are crucial problems in coherent ultra wideband (UWB) receiver designs. A joint maximum-likelihood (ML) and minimum-mean-square-error (MMSE) channel esti- mation scheme was developed for more precise channel estimates based on the assumption of exponential multipath decay. The performance improvement was analyzed theoretically with a computer simulation using IEEE 802.15.3a ultra-wideband channel models. Theoretical and simulation results show that the scheme further improves the estimation performance of channel gains and multipath delays compared with the traditional ML channel estimator.展开更多
文摘In this work, we developed a theoretical framework leading to misclassification of the final size epidemic data for the stochastic SIR (Susceptible-In</span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">fective</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">-Removed), household epidemic model, with false negative and false positive misclassification probabilities. Maximum likelihood based algorithm is then employed for its inference. We then analyzed and compared the estimates of the two dimensional model with those of the three and four dimensional models associated with misclassified final size data over arrange of theoretical parameters, local and global infection rates and corresponding proportion infected in the permissible region, away from its boundaries and misclassification probabilities.</span></span></span><span><span><span style="font-family:""> </span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">The adequacies of the three models to the final size data are examined. The four and three-dimensional models are found to outperform the two dimensional model on misclassified final size data.
基金supported by the National Natural Science Foundation of China(617020986170209961331019)
文摘A polynomial-rooting based fourth-order cumulant algorithm is presented for direction-of-arrival(DOA) estimation of second-order fully noncircular source signals, using a uniform linear array(ULA). This algorithm inherits all merits of its spectralsearching counterpart except for the applicability to arbitrary array geometry, while reducing considerably the computation cost.Simulation results show that the proposed algorithm outperforms the previously developed closed-form second-order noncircular ESPRIT method, in terms of processing capacity and DOA estimation accuracy, especially in the presence of spatially colored noise.
文摘This paper propose a computerized method of magnetic resonance imaging (MR/) of brain binarization for the uses of preprocessing of features extraction and brain ab- normality identification. One of the main problems of MR/ binarization is that many pixels of brain part cannot be cor- rectly binarized due to extensive black background or large variation in contrast between background and foreground of MR/. We have proposed a binarization that uses mean, vari- ance, standard deviation and entropy to determine a thresh- old value followed by a non-gamut enhancement which can overcome the binarization problem of brain component. The proposed binarization technique is extensively tested with a variety of MR/and generates good binarization with im- proved accuracy and reduced error. A comparison is carried out among the obtained outcome with this innovative method with respect to other well-known methods.
基金Supported by the National Natural Science Foundation of China (No. 90204001)
文摘Channel estimation and synchronization are crucial problems in coherent ultra wideband (UWB) receiver designs. A joint maximum-likelihood (ML) and minimum-mean-square-error (MMSE) channel esti- mation scheme was developed for more precise channel estimates based on the assumption of exponential multipath decay. The performance improvement was analyzed theoretically with a computer simulation using IEEE 802.15.3a ultra-wideband channel models. Theoretical and simulation results show that the scheme further improves the estimation performance of channel gains and multipath delays compared with the traditional ML channel estimator.