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WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL STATISTICS 2010年第3期2卷 340-351页

作者： Yang, Wei Zurbenko, Igor Univ Penn DepT Biostat & Epidemiol Philadelphia PA 19104 USA SUNY Albany Dept Epidemiol & Biostat Albany NY 12222 USA

We reviewed the properties of the Kolmogorov-Zurbenko (KZ) filter and its extensions with applications in high resolution signal and image processing. The KZ filter is defined as an iteration of a moving average (MA) filter. The impulse response function of the KZ filter is a convolution of the rectangular window being used in a MA filter. Zero derivatives at the edges of the impulse response function make it a sharply declining function, providing high frequency resolution. The KZ Fourier transform (KZFT) is derived from the KZ filter by applying it to Fourier transform. Extensions of the KZ filter and the KZFT are demonstrated with examples. (C) 2010 John Wiley & Sons, Inc.

关键词： KZ Filter KZFT moving average spectrum estimation smoothing algorithm

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Exploring the latent segmentation space for the assessment of multiple change-point models

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COMPUTATIONAL STATISTICS 2013年第6期28卷 2641-2678页

作者： Guedon, Yann CIRAD UMR AGAP F-34095 Montpellier France Inria Virtual Plants F-34095 Montpellier France

This paper addresses the retrospective or off-line multiple change-point detection problem. Multiple change-point models are here viewed as latent structure models and the focus is on inference concerning the latent segmentation space. Methods for exploring the space of possible segmentations of a sequence for a fixed number of change points may be divided into two categories: (i) enumeration of segmentations, (ii) summary of the possible segmentations in change-point or segment profiles. Concerning the first category, a dynamic programming algorithm for computing the top most probable segmentations is derived. Concerning the second category, a forward-backward dynamic programming algorithm and a smoothing-type forward-backward algorithm for computing two types of change-point and segment profiles are derived. The proposed methods are mainly useful for exploring the segmentation space for successive numbers of change points and provide a set of assessment tools for multiple change-point models that can be applied both in a non-Bayesian and a Bayesian framework. We show using examples that the proposed methods may help to compare alternative multiple change-point models (e.g. Gaussian model with piecewise constant variances or global variance), predict supplementary change points, highlight overestimation of the number of change points and summarize the uncertainty concerning the position of change points.

关键词： Dynamic programming algorithm Latent structure model Multiple change-point detection Plant structure analysis smoothing algorithm

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Segmentation uncertainty in multiple change-point models

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STATISTICS AND COMPUTING 2015年第2期25卷 303-320页

作者： Guedon, Yann CIRAD UMR AGAP F-34095 Montpellier France Inria F-34095 Montpellier France

This paper addresses the retrospective or off-line multiple change-point detection problem. In this context, there is a need of efficient diagnostic tools that enable to localize the segmentation uncertainty along the observed sequence. Concerning the segmentation uncertainty, the focus was mainly on the change-point position uncertainty. We propose to state this problem in a new way, viewing multiple change-point models as latent structure models and using results from information theory. This led us to show that the segmentation uncertainty is not reflected in the posterior distributions of the change-point position because of the marginalization that is intrinsic in the computation of these posterior distributions. The entropy of the segmentation of a given observed sequence can be considered as the canonical measure of segmentation uncertainty. This segmentation entropy can be decomposed as conditional entropy profiles that enables to localize this canonical segmentation uncertainty along the sequence. One of the main outcomes of this work is to derive efficient algorithms to compute these conditional entropy profiles. The proposed approach benefits from all the properties of the Shannon-Khinchin axioms of entropy and therefore is the unique approach for localizing the canonical segmentation uncertainty along the sequence. We introduce the Kullback-Leibler divergence of the uniform distribution from the segmentation distribution for successive numbers of change points as a new tool for assessing the number of change points selected by different methods. The proposed approach is illustrated using four contrasted examples.

关键词： Entropy Kullback-Leibler divergence Latent structure model Multiple change-point detection smoothing algorithm

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BI-LEVEL PROGRAMMING APPROACH TO OPTIMAL STRATEGY FOR VENDOR-MANAGED INVENTORY PROBLEMS UNDER RANDOM DEMAND

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ANZIAM JOURNAL 2017年第2期59卷 247-270页

作者： Li, Yinxue Wan, Zhong Liu, Jingjing Cent S Univ Sch Math & Stat Changsha Hunan Peoples R China

We present an extension of vendor-managed inventory (VMI) problems by considering advertising and pricing policies. Unlike the results available in the literature, the demand is supposed to depend on the retail price and advertising investment policies of the manufacturer and retailers, and is a random variable. Thus, the constructed optimization model for VMI supply chain management is a stochastic bi-level programming problem, where the manufacturer is the upper level decision-maker and the retailers are the lower-level ones. By the expectation method, we first convert the stochastic model into a deterministic mathematical program with complementarity constraints (MPCC). Then, using the partially smoothing technique, the MPCC is transformed into a series of standard smooth optimization subproblems. An algorithm based on gradient information is developed to solve the original model. A sensitivity analysis has been employed to reveal the managerial implications of the constructed model and algorithm: (1) the market parameters of the model generate significant effects on the decision-making of the manufacturer and the retailers, (2) in the VMI mode, much attention should be paid to the holding and shortage costs in the decision-making.

关键词： game theory stochastic models smoothing algorithm optimization vendor-managed inventory problems

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A joint channel estimation and timing adjustment for adaptive MLSE

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IEICE TRANSACTIONS ON COMMUNICATIONS 1998年第11期E81B卷 2242-2244页

作者： Song, HK Cho, WD Korea Elect Technol Inst Fac Pyung Taek Si 451860 South Korea

Because of non-negligible ISI due to the Gaussian filter and delay spread in the GSM system, an equalizer is required. In this letter, a joint sliding window channel estimation and timing adjustment method is proposed fur maximum likelihood sequence equalizer. And also a smoothing algorithm is presented in order to improve the equalizer performance. This smoothing scheme utilizes a variant of LMS algorithm to tune the channel coefficient estimates. Simulation results show that the proposed scheme is adequate for channel estimation of the adaptive equalizer.

关键词： channel estimation sliding window algorithm smoothing algorithm

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A new algorithm for numerical solution of 3D elastoplastic contact problems with orthotropic friction law

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COMPUTATIONAL MECHANICS 2004年第1期34卷 1-14页

作者： Zhang, HW He, SY Li, XS Wriggers, P Dalian Univ Technol State Key Lab Struct Anal Ind Equipment Dept Engn Mech Dalian 116024 Peoples R China Univ Hannover Inst Baumech & Numer Mech D-30167 Hannover Germany

3D elastoplastic frictional contact problems with orthotropic friction law belong to the unspecified boundary problems with nonlinearities in both material and geometric forms. One of the difficulties in solving the problem lies in the determination of the tangential slip states at the contact points. A great amount of computational efforts is needed so as to obtain high accuracy numerical results. Based on a combination of the well known mathematical programming method and iterative method, a finite element model is put forward in this paper. The problems are finally reduced to linear complementarity problems. A specially designed smoothing algorithm based on NCP-function is then applied for solving the problems. Numerical results are given to demonstrate the validity of the model and the algorithm proposed.

关键词： 3D contact problem orthotropic friction law elastoplasticity mathematical programming method iterative method linear complementarity problem smoothing algorithm

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Particle filters

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BERNOULLI 2013年第4期19卷 1391-1403页

作者： Kuensch, Hans R. ETH D Math Seminar Stat CH-8092 Zurich Switzerland

This is a short review of Monte Carlo methods for approximating filter distributions in state space models. The basic algorithm and different strategies to reduce imbalance of the weights are discussed. Finally, methods for more difficult problems like smoothing and parameter estimation and applications outside the state space model context are presented.

关键词： Ensemble Kalman filter importance sampling and resampling sequential Monte Carlo smoothing algorithm state space models

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Trends in sub-daily precipitation in Tasmania using regional dynamically downscaled climate projections

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JOURNAL OF HYDROLOGY-REGIONAL STUDIES 2017年 10卷 18-34页

作者： Brown, Katherine Kamruzzaman, Mohammad Beecham, Simon Univ South Australia Sch Nat & Built Environm CWMR Mawson Lakes SA 5095 Australia

Study region: Island state of Tasmania, Australia. Study focus: This study detected monotonic and step trends in maximum sub-daily precipitation for durations ranging from 3 to 24 h over the period 19612100. It also looked at whether or not there is agreement between six dynamically downscaled global circulation models (GCMs) in terms of the extent and magnitude of monotonic and step trends in the dataset. This was done using a split-apply-combine approach for data manipulation. The study included trend evaluation, application of a smoothing algorithm, and the application of non-parametric and parametric statistical tests on low pass filtered series. New hydrological insights: Monotonic and step trends in maximum sub-daily precipitation occurring in each month were identified across the state. Decreasing trends were found to become more evident in the Central Plateau region. There was reasonable agreement between GCMs on the sign and the magnitude of the precipitation changes, with the exception of the Central Plateau region of Tasmania, where the GCMs disagreed as to the spatial extent of the decreasing in trends. The duration and intensity (percentile) of maximum sub-daily precipitation were found to influence trends in sub-daily precipitation. Evidence of spatial patterns in monotonic and step trends for the data between the baseline period (19611990) and future climates (20102039, 20402069, and 20702099) have been evaluated. (C) 2016 The Author(s). Published by Elsevier B.V.

关键词： Dynamical downscaling Global climate model Precipitation trends smoothing algorithm Low pass filtered series

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Estimating hidden semi-Markov chains from discrete sequences

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JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS 2003年第3期12卷 604-639页

作者： Guédon, Y Univ Montpellier 2 INRA CNRS CIRADUnite Mixte Rech F-34398 Montpellier 5 France

This article addresses the estimation of hidden semi-Markov chains from nonstationary discrete sequences. Hidden semi-Markov chains are particularly useful to model the succession of homogeneous zones or segments along sequences. A discrete hidden semi-Markov chain is composed of a nonobservable state process, which is a semi-Markov chain, and a discrete output process. Hidden semi-Markov chains generalize hidden Markov chains and enable the modeling of various durational structures. From an algorithmic point of view, a new forward-backward algorithm is proposed whose complexity is similar to that of the Viterbi algorithm in terms of sequence length (quadratic in the worst case in time and linear in space). This opens the way to the maximum likelihood estimation of hidden semi-Markov chains from long sequences. This statistical modeling approach is illustrated by the analysis of branching and flowering patterns in plants.

关键词： censoring EM algorithm forward-backward algorithm nonparametric maximum likelihood plant structure analysis smoothing algorithm Viterbi algorithm

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Vector Quantization of images based on Peanoscanning

Vector Quantization of images based on Peanoscanning

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International Symposium on Multispectral Image Processing and Pattern Recognition

作者： Feng, YC Su, J Cao, ZS Huazhong Univ Sci & Technol Coll Comp Sci Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)0819430064

VQ(Vector Quantization) reduce the bit rate by exploting the correlation in the data. To improve the performance of a compression algorithm based on VQ, this paper introduced a more efficient scanning method, i.e. Peanoscanning, which maintains better correlation in two dimensional data than that of raster scan, and then a hierarchical VQ based on the characteristics of image data is presented, at last we reduced the blocking effect by a smoothing algorithm.

关键词： Peanoscanning hierarchical Vector Quantization smoothing algorithm

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