Sridhar Gollamudi Shirish Nagaraj Yih-Fang Huang Laboratory for Image and Signal Analysis Department of Electrical Engineering University of Notre Dame Notre Dame, IN 46556 E-mail: [email protected] Abstract | This paper presents the concept of SetMembership Filtering (SMF), an extension of SetMembership Identi cation (SMI) theory to the general ltering problem. A toolbox of adaptive solutions cal...

We conducted this study to explore functions of TF II A·/ß-like factor (ALF) during human spermatogenesis, and the relationship of its expression levels with male infertility. The RT-PCR and Western blot analyses illustrated that ALF was highly expressed in adult testis. Immunohistochemistry and immunoflurescence showed that ALF is located in the spermatid nuclei and in the annulus of spermatoz...

ABSTRACT: Hilbert-Huang Transform (HHT), proposed by N. E. Huang in 1998, is a novel algorithm for nonlinear and non-stationary signal processing. The key part of this method is decomposition the signal into finite number of Intrinsic Mode Functions (IMF) which will meet the requirements of Hilbert Transform. In this part, the algorithm uses natural cubic spline to connect all local maxima and ...

Detecting the interleaving relationship between sequences is a new research topic which begins to draw much attention. Recently, Huang et al. proposed the merged LCS model, which can be realized as finding the longest common subsequence between a target sequence and two merging sequences. Given the targe sequence T and two merging sequences A and B, Huang et al. gave an O(nmr)-time and O(mr)-sp...

R. Lopez , A. Colmenarez , T. S. Huang Beckman Institute University of Illinois Champaign-Urbana, IL 61801 Email: [email protected] , [email protected] , [email protected] ABSTRACT In the following paper we introduce an algorithm for automatic head tracking using a model-based approach. The input to the system is a 2D video sequence of a head-and-shoulders scene and the output is the traj...

Maximum and minimum computed across channels is used to monitor the Electroencephalogram signals for possible change of the eye state. Upon detection of a possible change, the last two seconds of the signal is passed through Multivariate Empirical Mode Decomposition and relevant features are extracted. The features are then fed into Logistic Regression and Artificial Neural Network classifiers ...

Towards developing a rigorous mathematical theory for Empirical Mode Decomposition (EMD), we provide an overview of the algorithm and introduce a corresponding operator, attempting a preliminary study. We prove that the EMD is nonlinear, we identify the major reason of its nonlinearity, and we introduce the related concept of consistency, which we show the EMD does not satisfy either. & 2012 Pu...