Statistical analysis system (SAS) is the most comprehensive statistical analysis software package in the world. It offers data analysis for almost all experiments under various statistical models. Each analysis is performed using a particular subroutine, called a procedure (PROC). For example, PROC ANOVA performs analysis of variances. PROC QTL is a user-defined SAS procedure for mapping quanti...

The Hierarchical mixture of experts(HME) architecture is a powerful tree structured architecture for supervised learning. In this paper, an eecient one-pass algorithm to solve the M-step of the EM iterations while training the HME network to perform classiication tasks, is rst described. This substantially reduces the training time compared to using the IRLS method to solve the M-step. Further,...

A framework of M-estimation based fuzzy C–means clustering (MFCM) algorithm is proposed with iterative reweighted least squares (IRLS) algorithm, and penalty constraint and kernelization extensions of MFCM algorithms are also developed. Introducing penalty information to the object functions of MFCM algorithms, the spatially constrained fuzzy c-means (SFCM) is extended to penalty constraints MF...

ادغام داده‌ها بین حسگرهای مختلف می‌تواند موجب استخراج اطلاعات با دقت و کیفیت بالاتر گردد بهبود تشخیص تهدیدهای هسته‌ای را به همراه داشته باشد. در این تحقیق، ردیابی چشمه متحرک استفاده از تلفیق داده­های سیستم آشکارساز پرتوی دوربین نظارتی مورد مطالعه قرار گرفت است. بدین منظور الگوریتمی جهت ایجاد همبستگی تصاویر دریافتی توسط شمارش طراحی شده است تا مسیر حرکت جسمی که بیش­ترین ثبت آشکارسازی دارد عنوان ا...

Dropout and other feature noising schemes have shown promising results in controlling over-fitting by artificially corrupting the training data. Though extensive theoretical and empirical studies have been performed for generalized linear models, little work has been done for support vector machines (SVMs), one of the most successful approaches for supervised learning. This paper presents dropo...

This paper presents a new approach to total variation (TV) based image deconvolution/deblurring, which is adaptive in the sense that it doesn’t require the user to specify the value of the regularization parameter. We follow the Bayesian approach of integrating out this parameter, which is achieved by using an approximation of the partition function of the probabilistic prior interpretation of ...

A compact isotope ratio laser spectrometry (IRLS) instrument was developed for simultaneous measurements of the D/H, 18O/16O and 17O/16O isotope ratios in water by laser absorption spectroscopy at 2.73 μm. Special attention is paid to the spectral data processing and implementation of a Kalman adaptive filtering to improve the measurement precision. Reduction of up to 3-fold in standard deviati...

When GPS signal measurements have outliers, using least squares (LS) estimation is likely to give poor position estimates. One of the typical approaches to handle this problem is to use robust estimation techniques. We study the computational issues of Huber’s M-estimation applied to relative GPS positioning. First for code-based relative positioning, we use simulation results to show that Newt...

Real-time reconstruction in multi-contrast magnetic resonance imaging (MC-MRI) is very challenging due to the slow scanning and reconstruction process. In this study, we propose a novel algorithm to accelerate the MC-MRI reconstruction in the framework of compressed sensing. The problem is formulated as the minimization of the least square data fitting with joint total variation (JTV) regulariz...

When GPS signal measurements have outliers, using least squares (LS) estimation will likely give poor position estimates. One of typical approaches to handling this problem is to use robust estimation techniques. In this paper, we study the computational issues of Huber’s M-estimation applied to relative positioning. First for code based relative positioning, we use simulation results to show N...