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NONUNIFORM ARRAY-PROCESSING VIA THE POLYNOMIAL APPROACH

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 1989年第1期25卷 48-55页

作者： WEISS, AJ WILLSKY, AS LEVY, BC MIT INFORMAT & DECIS SYST LABCAMBRIDGEMA 02139 UNIV CALIF DAVIS DEPT ELECT ENGN & COMP SCIDAVISCA 95616

A polynomial approach for maximum-likelihood (ML) estimation of superimposed signals in time-series problems and array processing was recently proposed. This technique was applied successfully to linear uniform arrays and to uniformly sampled complex exponential signals. However, uniformly spaced arrays are not optimal for minimum variance estimation of bearing, range or position, and uniform sampling of signals is not always possible in practice. The authors make use of the expectation-maximization algorithm to apply the polynomial approach to sublattice arrays and to missing samples in time-series problems.

关键词： expectation-maximisation algorithm Uniform Array Array processing Nonuniform signals Polynomial uniform sampling Signal timing sampling time

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Human-level face verification with intra-personal factor analysis and deep face representation

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IET BIOMETRICS 2018年第5期7卷 467-473页

作者： Munasinghe, Sarasi Fookes, Clinton Sridharan, Sridha Queensland Univ Technol Image & Video Res Lab 2 George StGPO Box 2434 Brisbane Qld 4001 Australia

The last two decades have seen an escalating interest in methods for large-scale unconstrained face recognition. While the promise of computer vision systems to efficiently and accurately verify and identify faces in naturally occurring circumstances still remains elusive, recent advances in deep learning are taking us closer to human-level recognition. In this study, the authors propose a new paradigm which employs deep features in a feature extractor and intra-personal factor analysis as a recogniser. The proposed new strategy represents the face changes of a person using identity specific components and the intra-personal variation through reinterpretation of a Bayesian generative factor analysis model. The authors employ the expectation-maximisation algorithm to calculate model parameters which cannot be observed directly. Recognition outcomes achieved through benchmarking on large-scale wild databases, Labeled Faces in the Wild (LFW) and Youtube Face (YTF), clearly prove that the proposed approach provides remarkable face verification performance improvement over state-of-the-art approaches.

关键词： image representation computer vision face recognition learning (artificial intelligence) expectation-maximisation algorithm feature extraction Bayes methods deep face representation large-scale unconstrained face recognition computer vision systems deep learning human-level recognition deep features feature extractor intra-personal variation recognition outcomes remarkable face verification performance improvement human-level face verification intrapersonal factor analysis Labeled face recognition Youtube face recognition

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INVESTIGATION OF CARBON BLACK AND SILICA SURFACE STRUCTURE BY STATIC GAS ADSORPTION WITH VARIOUS GASES

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RUBBER CHEMISTRY AND TECHNOLOGY 2018年第2期91卷 509-519页

作者： Plagge, J. Klueppel, M. Deutsch Inst Kautschuktechnol EV Eupener Str 33 D-30519 Hannover Germany

The surface of various carbon black and silica grades is characterized via static gas adsorption using different gases. From decomposition of the adsorption isotherm into distinct energetic contributions, the adsorption energy distribution as well as the surface area are obtained. The decomposition is done by an iterative expectation maximization algorithm specifically designed for this problem. It is found that the adsorption isotherms of the various gases differ significantly in the low-pressure regime, leading to characteristic energy distributions with distinct maxima. As expected, the mean adsorption energy generally increases with the cross section of the gases, and systematic deviations are found reflecting the polar and dispersive interaction characteristics of silica and carbon black, respectively. The surface fractal dimension of two different carbon black grades is estimated using the yardstick method. The obtained values 2.6 and 2.7 agree with previous findings that the carbon black surface morphology is very rough. The adsorption of CO2 on both carbon blacks delivers unexpectedly low values of the monolayer coverage or specific surface area, indicating that mainly high energetic sites of the surface are covered. In consequence, compared with N-2, a relatively high value of the mean adsorption energy is found. For both investigated silicas, the mean adsorption energy scales with the quadrupole moments of CO2 and N-2, which is indicative of a large polar contribution to interaction energy.

关键词： Cross section Carbon Dioxide surface structure Gases expectation-maximisation algorithm surface area Adsorption isotherms energy distribution Quadrupole moment Gas adsorption Adsorption energy

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Bayesian image reconstruction in SPECT using higher order mechanical models as priors

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IEEE TRANSACTIONS ON MEDICAL IMAGING 1995年第4期14卷 669-680页

作者： Lee, SJ Rangarajan, A Gindi, G SUNY STONY BROOK DEPT ELECT ENGN STONY BROOK NY 11794 USA YALE UNIV DEPT COMP SCI NEW HAVEN CT 06520 USA SUNY STONY BROOK DEPT RADIOL STONY BROOK NY 11794 USA

While the ML-EM algorithm for reconstruction for emission tomography is unstable due to the ill-posed nature of the problem. Bayesian reconstruction methods overcome this instability by introducing prior information, often in the form of a spatial smoothness regularizer. More elaborate forms of smoothness constraints may be used to extend the role of the prior beyond that of a stabilizer in order to capture actual spatial information about the object. Previously proposed forms of such prior distributions were based on the assumption of a piecewise constant source distribution. Here, we propose an extension to a piecewise linear model-the weak plate-which is more expressive than the piecewise constant model. The weak plate prior not only preserves edges but also allows for piecewise ramplike regions in the reconstruction. Indeed, for our application in SPECT, such ramplike regions are observed in ground-truth source distributions in the form of primate autoradiographs of rCBF radionuclides. To incorporate the weak plate prior in a MAP approach, we model the prior as a Gibbs distribution and use a GEM formulation for the optimization. We compare quantitative performance of the ML-EM algorithm, a GEM algorithm with a prior favoring piecewise constant regions, and a GEM algorithm with our weak plate prior. Pointwise and regional bias and variance of ensemble image reconstructions are used as indications of image quality. Our results show that the weak plate and membrane priors exhibit improved bias and variance relative to ML-EM techniques.

关键词： emission tomography Piecewise expectation-maximisation algorithm image reconstruction Generalized EM algorithm MECHANICAL MODEL single photon emission computed tomography

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Fully automated scheme for computer-aided detection and breast cancer diagnosis using digitised mammograms

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IET IMAGE PROCESSING 2020年第3期14卷 495-505页

作者： Eltrass, Ahmed S. Salama, Mohamed S. Alexandria Univ Dept Elect Engn Fac Engn Alexandria Egypt

Breast cancer becomes a significant public health problem in the world. During the early detection of breast cancer, it is a very challenging task to classify accurately the benign-malignant patterns in digital mammograms. This study proposes a new fully automated computer-aided diagnosis (CAD) system for breast cancer diagnosis with high-accuracy and low-computational requirements. The expectation-maximisation algorithm is investigated to extract automatically the region of interests (ROIs) within mammograms. The standard shape, statistical, and textural features of ROIs are extracted and combined with multi-resolution and multi-orientation features derived from a new feature extraction technique based on wavelet-based contourlet transform. A hybrid feature selection approach based on combining the support vector machine recursive feature elimination with correlation bias reduction algorithm is proposed. Also, the authors investigate a new similarity-based learning algorithm, called Q, for benign-malignant classification. The proposed CAD system is applied to real clinical mammograms, and the experimental results demonstrate the superior performance of the proposed CAD system over other existing CAD systems in terms of accuracy 98.16%, sensitivity 98.63%, specificity 97.80%, and computational time 2.2 s. This reveals the effectiveness of the proposed CAD system in improving the accuracy of breast cancer diagnosis in real-time systems.

关键词： medical image processing image texture support vector machines learning (artificial intelligence) wavelet transforms mammography image classification cancer feature extraction object detection expectation-maximisation algorithm image resolution statistical analysis feature selection correlation methods computer-aided detection breast cancer diagnosis public health problem benign-malignant patterns digital mammograms fully automated computer-aided diagnosis system low-computational requirements textural features multiorientation features feature extraction technique hybrid feature selection approach support vector machine recursive feature elimination CAD system breast cance early detection expectation-maximisation algorithm region of interest extraction ROIs multiresolution features wavelet-based contourlet transform correlation bias reduction algorithm Q similarity-based learning algorithm benign-malignant classification real-time systems real clinical mammograms time 2 2 s

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The EM algorithm for the extended finite mixture of the factor analyzers model

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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2008年第8期52卷 3939-3953页

作者： Zhou, Xingcai Liu, Xinsheng Nanjing Univ Aeronaut & Astronaut Acad Frontier Sci Inst Nano Sci Nanjing 210016 Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Sci Nanjing 210016 Peoples R China Tongling Univ Dept Elementary Educ Tongling 244000 Anhui Peoples R China

This paper is devoted to extending common factors and categorical variables in the model of a finite mixture of factor analyzers based on the multivariate generalized linear model and the principle of maximum random utility in the probabilistic choice theory. The EM algorithm and Newton-Raphson algorithm are used to estimate model parameters, and then the algorithm is illustrated with a simulation study and a real example. (c) 2008 Elsevier B.V. All rights reserved.

关键词： model parameters Finite Newton-Raphson method Analysers expectation-maximisation algorithm maximum principle

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Three-dimensional channel modelling using spherical statistics for multiple-input multiple-output systems

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IET COMMUNICATIONS 2009年第1期3卷 48-56页

作者： Mammasis, K. Stewart, R. W. Pfann, E. Freeland, G. Univ Strathclyde Dept Elect & Elect Engn Glasgow G1 1XW Lanark Scotland Steepest Ascent Ltd Glasgow G4 0UW Lanark Scotland

Recently, the third generation partnership standards bodies (3GPP/3GPP2) have defined a two-dimensional channel model for multiple-input multiple-output (MIMO) systems, where the propagating plane waves are assumed to arrive only from the azimuthal direction and therefore not include the elevation domain. As a result of this assumption, the derived angle-of-arrival (AoA) distribution is characterised only by the azimuth direction of these waves. The AoA distribution of multipaths is implemented with a novel three-dimensional approach. The von Mises-Fisher (VMF) probability density function is used to describe their distribution within the propagation environment in both azimuth and co-latitude. More specifically, the proposed model uses a mixture of VMF distributions. A mixture can be composed of any number of clusters and this is clutter specific. The parameters of the individual cluster of scatterers within the mixture are derived and an estimation of those parameters is achieved using the spherical K-means algorithm and also the expectation maximisation algorithm. Statistical tests are provided to measure the goodness of fit of the proposed model. The results indicate that the proposed model fits well with MIMO experimental data obtained from a measurement campaign in Germany.

关键词： channel model Scattering expectation-maximisation algorithm Plane waves Sphericity azimuth output system goodness of fit multiple input multiple output systems

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Multi-phase initial ranging process for OFDMA systems: improved dynamic threshold-based multi-user detection approach

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IET COMMUNICATIONS 2020年第13期14卷 2130-2140页

作者： Naveen, Kolihalli Narasaiah Ramesha, Kenchappa Dr Ambedkar Inst Technol Dept Elect & Commun Engn Bengaluru Karnataka India Dr Ambedkar Inst Technol Dept Elect & Instrumentat Engn Bengaluru Karnataka India

Initial ranging (IR) is a process of performing power adjustment, timing offset estimation, and synchronisation between the base station (BS) and all users. It plays a vital role in mobile WiMAX standard, which establishes a communication link between BS and ranging subscriber stations (RSSs). Since RSS is located far away from the BS and uplink signal is corrupted by noise, the IR process becomes inferior. Thus, the authors propose an improved dynamic threshold-based IR method comprising three phases: (i) code detection phase, (ii) filtering phase, and (iii) parameter estimation phase. In the first two phases, the received signal is pre-processed to eliminate noise and unselected codes from the codeset by employing adaptive filter and weight-based code detection method. Then, the noise-free signal is considered for the final phase, which improves accuracy. The iterative expectation maximisation algorithm is involved in the estimation of channel coefficient and timing offset. All possible active paths are detected by setting a dynamic threshold value for each channel by the enhanced dynamic threshold method. For all active channels, round trip delay, and power level are estimated by considering particular channel coefficient and timing offset. Extensive simulation of proposed work shows considerable improvements in performance.

关键词： multiuser detection frequency division multiple access adaptive filters expectation-maximisation algorithm OFDM modulation parameter estimation phase coding signal denoising channel estimation OFDMA systems base station mobile WiMAX standard ranging subscriber stations filtering phase parameter estimation phase received signal noise-free signal weight-based code detection method enhanced dynamic threshold method channel coefficient unselected code detection phase multiphase initial ranging process RSS timing offset estimation synchronisation communication link iterative expectation maximisation algorithm dynamic threshold-based IR method dynamic threshold-based multiuser detection approach

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Population pharmacokinetic/pharmacodynamic mixture models via maximum a posteriori estimation

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COMPUTATIONAL STATISTICS & DATA ANALYSIS 2009年第12期53卷 3907-3915页

作者： Wang, Xiaoning Schumitzky, Alan D'Argenio, David Z. Univ So Calif Dept Biomed Engn Los Angeles CA 90089 USA Univ So Calif Dept Math Los Angeles CA 90089 USA Bristol Myers Squibb Co Clin Discovery Strateg Modeling & Simulat Grp Princeton NJ 08543 USA

Pharmacokinetic/pharmacodynamic phenotypes are identified using nonlinear random effect models with finite mixture structures. A maximum a posteriori probability estimation approach is presented using an EM algorithm with importance sampling. Parameters for the conjugate prior densities can be based on prior studies or set to represent vague knowledge about the model parameters. A detailed simulation study illustrates the feasibility of the approach and evaluates its performance, including selecting the number of mixture components and proper subject classification. (C) 2009 Elsevier B.V. All rights reserved.

关键词： EM algorithm BAYESIAN-APPROACH LIKELIHOOD expectation-maximisation algorithm Conjugate prior model parameters Bayes methods random effect Maximum a posteriori estimation importance sampling

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IDENTIFICATION AND RESTORATION OF NOISY BLURRED IMAGES USING THE expectation-MAXIMIZATION algorithm

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IEEE TRANSACTIONS ON ACOUSTICS SPEECH AND SIGNAL PROCESSING 1990年第7期38卷 1180-1191页

作者： LAGENDIJK, RL BIEMOND, J BOEKEE, DE DELFT UNIV TECHNOL DEPT ELECT ENGNINFORMAT THEORY LAB2600 GA DELFTNETHERLANDS

A maximum-likelihood approach to the blur identification problem is presented. The expectation-maximization algorithm is proposed to optimize the nonlinear likelihood function in an efficient way. In order to improve the performance of the identification algorithm, low-order parametric image and blur models are incorporated into the identification method. The resulting iterative technique simultaneously identifies and restores noisy blurred images.

关键词： fuzzy identification expectation-maximisation algorithm Likelihood Functions restoration Authentication

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