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Articles 1 - 15 of 15
Full-Text Articles in Physical Sciences and Mathematics
Initial Values In Estimation Procedures For State Space Models (Ssms), Raed Alzghool, Yan-Xia Lin
Initial Values In Estimation Procedures For State Space Models (Ssms), Raed Alzghool, Yan-Xia Lin
Faculty of Informatics - Papers (Archive)
In this paper, we will focus on State Space Models(SSMs), especially the stochastic volatility model, and lookfor a standard approach for assigning initial values in theQuasi-Likelihood (QL) and Asymptotic Quasi-Likelhood (AQL)estimation procedures.
Age Estimation Based On Extended Non-Negative Matrix Factorization, Ce Zhan, Wanqing Li, Philip Ogunbona
Age Estimation Based On Extended Non-Negative Matrix Factorization, Ce Zhan, Wanqing Li, Philip Ogunbona
Faculty of Informatics - Papers (Archive)
Previous studies suggested that local appearance-based methods are more efficient than geometric-based and holistic methods for age estimation. This is mainly due to the fact that age information are usually encoded by the local features such as wrinkles and skin texture on the forehead or at the eye corners. However, the variations of theses features caused by other factors such as identity, expression, pose and lighting may be larger than that caused by aging. Thus, one of the key challenges of age estimation lies in constructing a feature space that could successfully recovers age information while ignoring other sources of …
Spectral Density Estimation Through A Regularized Inverse Problem, Chunfeng Huang, Tailen Hsing, Noel Cressie
Spectral Density Estimation Through A Regularized Inverse Problem, Chunfeng Huang, Tailen Hsing, Noel Cressie
Faculty of Informatics - Papers (Archive)
In the study of stationary stochastic processes on the real line, the covariance function and the spectral density function are parameters of considerable interest. They are equivalent ways of expressing the temporal dependence in the process. In this article, we consider the spectral density function and propose a new estimator that is not based on the periodogram; the estimator is derived through a regularized inverse problem. A further feature of the estimator is that the data are not required to be observed on a grid. When the regularization condition is based on the function's first derivative, we give the estimator …
An Estimation Method For Feedback Level Factor C Of A Self-Mixing Interferometry System, Yuanlong Fan, Yanguang Yu, Jiangtao Xi, Joe F. Chicharo
An Estimation Method For Feedback Level Factor C Of A Self-Mixing Interferometry System, Yuanlong Fan, Yanguang Yu, Jiangtao Xi, Joe F. Chicharo
Faculty of Informatics - Papers (Archive)
This paper presents a fast estimation method for feedback level factor C of a self-mixing interferometry (SMI) system. The reconstruction of a displacement waveform using a SMI signal needs to know a C value. However, it is difficult to maintain a constant C value during the reconstruction process. We study the features of the reconstructed displacement waveforms incorporating different pre-set C values and classify waveforms into two types. Bisection method is introduced in our method for fast estimating C value. The effectiveness of our proposed method has been verified by both simulation and experimental data.
Rotor Position And Speed Estimation Of A Variable Structure Direct-Torque-Controlled Ipm Synchronous Motor Drive At Very Low Speeds Including Standstill, Saad M. Sayeef, Gilbert Foo, Muhammad F. Rahman
Rotor Position And Speed Estimation Of A Variable Structure Direct-Torque-Controlled Ipm Synchronous Motor Drive At Very Low Speeds Including Standstill, Saad M. Sayeef, Gilbert Foo, Muhammad F. Rahman
Faculty of Informatics - Papers (Archive)
The performance of a speed sensorless variable structure direct-torque-controlled interior permanent magnet synchronous motor drive at very low speeds including standstill is investigated in this paper. The rotor position and speed are estimated using a high-frequency (HF) signal injection algorithm at low speeds and a sliding observer at medium to high speeds. The changeover between these two algorithms is performed using a weighting function which smoothly hands over the estimated rotor position information for stator flux and torque estimation purposes. Experiments were performed to test the effectiveness of the proposed HF signal injection algorithm, and results show that the sensorless …
Fast Digital Optical Flow Estimation Based On Emd, Mickael Quelin, Abdesselam Bouzerdoum, Son Lam Phung
Fast Digital Optical Flow Estimation Based On Emd, Mickael Quelin, Abdesselam Bouzerdoum, Son Lam Phung
Faculty of Informatics - Papers (Archive)
This paper presents an optical flow estimation technique based on the so called Elementary Motion Detector (EMD). The aim is to provide a fast but not necessarily very accurate system to be used for specific post processing purposes. This model uses a low complexity algorithm for detecting motion in four directions by identifying specific motion templates. By extending the motion templates to different scales of the input video, an Elementary Velocity Detector (EVD) is created. This one can save computation time by estimating different speeds in parallel. Information from the EVD outputs is then used to generate an estimate of …
Motion Estimation With Adaptive Regularization And Neighborhood Dependent Constraint, Muhammad Wasim Nawaz, Abdesselam Bouzerdoum, Son Lam Phung
Motion Estimation With Adaptive Regularization And Neighborhood Dependent Constraint, Muhammad Wasim Nawaz, Abdesselam Bouzerdoum, Son Lam Phung
Faculty of Informatics - Papers (Archive)
Modern variational motion estimation techniques use total variation regularization along with the L1 norm in constant brightness data term. An algorithm based on such homogeneous regularization is unable to preserve sharp edges and leads to increased estimation errors. A better solution is to modify regularizer along strong intensity variations and occluded areas. In addition, using neighborhood information with data constraint can better identify correspondence between image pairs than using only a pointwise data constraint. In this work, we present a novel motion estimation method that uses neighborhood dependent data constraint to better characterize local image structure. The method also uses …
Estimation In A Multiplicative Mixed Model Involving A Genetic Relationship Matrix, Alison M. Kelly, Brian R. Cullis, Arthur R. Gilmour, John A. Eccleston, Robin Thompson
Estimation In A Multiplicative Mixed Model Involving A Genetic Relationship Matrix, Alison M. Kelly, Brian R. Cullis, Arthur R. Gilmour, John A. Eccleston, Robin Thompson
Faculty of Informatics - Papers (Archive)
Genetic models partitioning additive and non-additive genetic effects for populations tested in replicated multi-environment trials (METs) in a plant breeding program have recently been presented in the literature. For these data, the variance model involves the direct product of a large numerator relationship matrix A, and a complex structure for the genotype by environment interaction effects, generally of a factor analytic (FA) form. With MET data, we expect a high correlation in genotype rankings between environments, leading to non-positive definite covariance matrices. Estimation methods for reduced rank models have been derived for the FA formulation with independent genotypes, and we …
Person-Level And Household-Level Regression Estimation In Household Surveys, David G. Steel, Robert Graham Clark
Person-Level And Household-Level Regression Estimation In Household Surveys, David G. Steel, Robert Graham Clark
Faculty of Informatics - Papers (Archive)
A common class of survey designs involves selecting all people within selected households. Generalized regressionestimators can be calculated at either the person or household level. Implementing the estimator at the household level has the convenience of equal estimation weights for people within households. In this article the two approaches are compared theoretically and empirically for the case of simple random sampling of households and selection of all persons in each selected household. We find that the household level approach is theoretically more efficient in large samples and any empirical inefficiency in small samples is limited.
Ultra-Wideband Mb-Ofdm Channel Estimation With Complementary Codes, Darryn Lowe, Xiaojing Huang
Ultra-Wideband Mb-Ofdm Channel Estimation With Complementary Codes, Darryn Lowe, Xiaojing Huang
Faculty of Informatics - Papers (Archive)
In this paper, we design complementary codesets that significantly improve the quality of channel estimation in orthogonal frequency division multiplexing (OFDM) communication systems, with a focus on the recent MB-OFDM ultra-wideband (UWB) standard. The proposed time-domain OFDM channel estimation technique incurs only a nominal increase in computational complexity and is able to be readily retrofitted into the existing MB-OFDM standard. The underlying complementary codesets, found via an evolutionary algorithm, combine with the existing preamble synchronization sequences to yield asymptotically ideal auto-correlation functions (ACFs). We show how improvements exceeding 1 dB can be achieved in end-to-end packet error rate relative to …
Adaptive Low-Complexity Mmse Channel Estimation For Ofdm, Darryn Lowe, Xiaojing Huang
Adaptive Low-Complexity Mmse Channel Estimation For Ofdm, Darryn Lowe, Xiaojing Huang
Faculty of Informatics - Papers (Archive)
In this paper we present extremely low-complexity adaptive infinite impulse response (IIR) filters that approximate minimum mean square error (MMSE) channel estimation in orthogonal frequency-division multiplexing (OFDM) systems. We show how the packet error rate (PER) can be significantly improved over conventional zero-forcing (ZF) estimation without incurring a significant increase in computational complexity. All quantitative results are provided in the context of multi-band OFDM (MB-OFDM) ultra-wideband (UWB) with standard IEEE channel models.
In Process Surface Roughness Estimation In Grinding, Li Xue, Fazel Naghdy, Christopher David Cook
In Process Surface Roughness Estimation In Grinding, Li Xue, Fazel Naghdy, Christopher David Cook
Faculty of Informatics - Papers (Archive)
An intelligent sensor system for on-line estimation of surface roughness in the grinding process is developed. The system consists of a statistical signal processing algorithm and a neuro-fuzzy model of surface roughness. The model is established using a set of experimental data. The sensor signals of acoustic emission CAE), normal force and tangential force generated in grinding zone are acquired online in real time. The surface roughness of the ground workpiece is measured offline and used as the target output of the model. A first order Sugeno-type neuro-fuzzy inference system is employed to optimize the model by minimizing a sum …
The Estimation Of Continuous Pq Disturbance Levels In Distribution Systems, Victor J. Gosbell, D A. Robinson
The Estimation Of Continuous Pq Disturbance Levels In Distribution Systems, Victor J. Gosbell, D A. Robinson
Faculty of Informatics - Papers (Archive)
A simple method is given for estimating the continuous PQ disturbance level at a site. It is based on determining a "Voltage Distortion Increment" (VDI) for each segment of the network and then adding the VDIs from a given site back to an upstream site where levels are taken to be zero. The VDI is conveniently expressible in the form of S(MVA) times length (km), where "length" correspond to the physical length in the case of MV overhead lines and an equivalent length for other components. The method is verified by a comparison with field survey data. The voltage distortion …
Sensorless Force Estimation For Robots With Friction, John L. Simpson, Christopher David Cook, Zheng Li
Sensorless Force Estimation For Robots With Friction, John L. Simpson, Christopher David Cook, Zheng Li
Faculty of Informatics - Papers (Archive)
No abstract provided.
Small-Area Estimation: An Appraisal - Comment, Noel A. Cressie, Mark S. Kaiser
Small-Area Estimation: An Appraisal - Comment, Noel A. Cressie, Mark S. Kaiser
Faculty of Informatics - Papers (Archive)
Malay Ghosh and Jon Rao have presented us with a well written exposition of the topic of small area estimation. The past literature has been de-cidedly influenced by linear modeling, and we see that clearly in their paper. There has also been a tendency to judge the performance of the estimation methods by concentrating on a single, arbitrary small area. In our comment, we shall discuss what opportunities there might be to expand the class of statistical models for small area data and to consider multivariate aspects of small area estimation.