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IEEE International Symposium on Information Theory

作者： Jayakrishnan Unnikrishnan Venugopal V. Veeravalli Sean Meyn Department of Electrical and Computer Engineering and Coordinated Science Laboratory University of Illinois Urbana-Champaign USA

We study the problem of robust quickest change detection where the pre-change and post-change distributions are not known exactly but belong to known uncertainty classes of distributions. Both Bayesian and minimax versions of the quickest change detection problem are considered. When the uncertainty classes satisfy some specific conditions, we identify least favorable distributions (LFD's) from the uncertainty classes, and show that the detection rule designed for the LFD's is optimal in a minimax sense. The condition is similar to that required for the existence of LFD's for the robust hypothesis testing problem studied by Huber.

关键词： Robustness Uncertainty Minimax techniques Intrusion detection Delay Bayesian methods Fault detection change detection algorithms System testing Quality control

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On the problem of detection and discrimination of double talk and change in the echo path

On the problem of detection and discrimination of double tal...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： C. Carlemalm F. Gustafsson B. Wahlberg S3-Automatic Control Royal Institute of Technology Stockholm Sweden Automatic Control Linköping University Linkoping Sweden

The problem of detection and discrimination of double talk and change in the echo path in a telephone channel is considered. The phenomenon echo path change requires fast adaptation of the channel model to be able to equalize the echo dynamics. On the other hand, the adaption rate should be reduced when double talk occurs. Thus, it is critical to quickly detect a change in the echo path while not confusing it with double talk, which gives a similar effect. The proposed likelihood based approach compares a global channel model with a local one over a sliding window, both estimated with the recursive least squares algorithm.

关键词： Telephony Automatic control Delay change detection algorithms Filters Recursive estimation Least squares approximation Signal processing algorithms detection algorithms Algorithm design and analysis

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change-Point detection in Time-Series Data based on Subspace Identification

Change-Point Detection in Time-Series Data based on Subspace...

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7th IEEE International Conference on Data Mining (ICDM 2007)

作者： Yoshinobu Kawahara Takehisa Yairi Kazuo Machida University of Tokyo Meguro Tokyo Japan

In this paper, we propose series of algorithms for detecting change points in time-series data based on subspace identification, meaning a geometric approach for estimating linear state-space models behind time-series data. Our algorithms are derived from the principle that the subspace spanned by the columns of an observability matrix and the one spanned by the subsequences of time-series data are approximately equivalent. In this paper, we derive an batch-type algorithm applicable to ordinary time-series data, i.e. consisting of only output series, and then introduce the online version of the algorithm and the extension to be available with input-output time-series data. We illustrate the effectiveness of our algorithms with comparative experiments using some artificial and real datasets.

关键词： Observability Fault detection change detection algorithms State estimation Stochastic systems Data mining Signal processing algorithms detection algorithms Signal analysis Time series analysis

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A compressed domain change detection algorithm for RTP streams in video surveillance applications

A compressed domain change detection algorithm for RTP strea...

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IEEE Workshop on Multimedia Signal Processing

作者： Marcus Laumer Peter Amon Andreas Hutter André Kaup Imaging and Visualization Siemens Corporate Technology Munich Germany Multimedia Communications and Signal Processing University of Erlangen-Nuremberg Erlangen Germany

This paper presents a novel change detection algorithm for the compressed domain. Many video surveillance systems in practical use transmit their video data over a network by using the Real-time Transport Protocol (RTP). Therefore, the presented algorithm concentrates on analyzing RTP streams to detect major changes within contained video content. The paper focuses on a reliable preselection for further analysis modules by decreasing the number of events to be investigated. The algorithm is designed to work on scenes with mainly static background, like in indoor video surveillance streams. The extracted stream elements are RTP timestamps and RTP packet sizes. Both values are directly accessible by efficient byte-reading operations without any further decoding of the video content. Hence, the proposed approach is codec-independent, while at the same time its very low complexity enables the use in extensive video surveillance systems. About 40,000 frames per second of a single RTP stream can be processed on an Intel ® Core™ 2 Duo CPU at 2 GHz and 2 GB RAM, without decreasing the efficiency of the algorithm.

关键词： Algorithm design and analysis Streaming media Transform coding Training change detection algorithms Visualization Feature extraction

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Clustering Algorithm of Remote Sensing Image change detection Based on Improved U-Net Network

Clustering Algorithm of Remote Sensing Image Change Detectio...

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Data Analytics, Computing and Artificial Intelligence (ICDACAI), International Conference on

作者： Song Peng School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (数字)9798331519032

ISBN: (纸本)9798331519049

Disaster assessment, urban planning and environmental monitoring urgently need to be combined with remote sensing image change detection to play a role. An improved U-Net network combined with clustering algorithm is proposed for remote sensing image change detection. In this paper, firstly, the U-Net network is improved to enhance its feature extraction ability. Next, this paper takes the improved U-Net output feature map as the input of clustering algorithm, and uses K-means clustering algorithm, density-based noisy application spatial clustering (DBSCAN) and Mean Shift clustering to process the change detection results. The final experimental results show that the improved U-Net network combined with K-means algorithm has achieved remarkable performance improvement in remote sensing image change detection, with the maximum OA of 98%, the maximum Kappa coefficient of 0.94 and the maximum BAI of 0.98.

关键词： Accuracy change detection algorithms Urban planning Clustering algorithms Feature extraction Robustness Sensors Indexes Remote sensing Research and development

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PRACTICAL ITERATIVE RECONSTRUCTION METHODS FOR QUANTITATIVE CARDIAC SPECT IMAGE-RECONSTRUCTION

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IEEE TRANSACTIONS ON NUCLEAR SCIENCE 1994年第1期41卷 325-330页

作者： TSUI, BMW ZHAO, X University of North Carolina Chapel Hill Chapel Hill NC USA

We proposed a practical iterative reconstruction method for cardiac SPECT imaging. The method consisted of four major parts. First, the first order Chang reconstructed image with attenuation compensation for the chest region was obtained as the initial estimate. The iterative weighted least square-conjugate gradient (WLS-CG) reconstruction algorithm, known for its fast convergence rate, was then applied. A projector/backprojector which modeled the nonuniform attenuation and the spatially variant collimator-detector response was used with the WLS-CG algorithm to provide accurate compensation for the effects of attenuation and collimator-detector response. Finally a smoothing filter was used to suppress noise amplification between iterations. The method was evaluated relative to conventional reconstruction methods in terms of quantitative accuracy, image noise and ventricular wall thickness. We conclude that the practical iterative reconstruction method has great potential for clinical use in providing cardiac SPECT images with high quantitative accuracy and low image noise within a few iterations.

关键词： Iterative methods Reconstruction algorithms Image reconstruction Attenuation Iterative algorithms Collimators Convergence Biomedical imaging change detection algorithms Smoothing methods

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Switching Signal Estimator Design for a Class of Elementary Systems

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2016年第5期61卷 1362-1367页

作者： Menini, Laura Possieri, Corrado Tornambe, Antonio Univ Roma Tor Vergata Dipartimento Ingn Civile & Ingn Informat I-00133 Rome Italy

The goal of this technical note is to design a switching signal estimator for a class of elementary continuous-time switching or switched systems. First, the elementary system is recast into a polynomial form and, secondly, some tools borrowed from Algebraic Geometry are used to express the switching signal as a function of the time derivatives of the output and of the input.

关键词： change detection algorithms hybrid systems nonlinear dynamical systems observers

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change detection in Image Time-Series Affected by Directional Reflectance and Phenological Variability: Application to Forest Disturbance Monitoring

Change Detection in Image Time-Series Affected by Directiona...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Eric Nielsen Mark Finco Everett Hinkley U.S. Forest Service Remote Sensing Applications Center. emnielsen@fs.fed.us U.S. Forest Service Remote Sensing Applications Center

Rapid identification of vegetation change over extensive areas requires the use of high temporal resolution data from wide-swath sensors, but analysis of such data is difficult due to the effects of vegetation directional reflectance and phenological variability. The magnitude of these effects can be large relative to the often subtle reflectance changes associated with natural forest disturbance, especially at coarse spatial resolutions. To address these challenges we propose a novel change detection methodology. We first apply a median-based compositing technique to a multi-year surface reflectance data record to create a reliable baseline phenological time-series. We then apply an algorithm - Dynamic Class Delta Resistant-Z Analysis - to reduce the magnitude of the change signal deriving from extraneous sources, allowing the use of composite images containing pixels collected under substantial variability in sensor and solar geometry. We apply these methods to generate an evolving disturbance product at an approximately weekly timestep and 250-meter spatial resolution for recent years in the U.S. Pacific Northwest. Comparison of results with other methodologies indicate the technique provides advantages that should substantially enhance the ability to reliably and rapidly detect natural forest disturbance.

关键词： Reflectivity Monitoring Spatial resolution Vegetation mapping Data analysis change detection algorithms Heuristic algorithms Image analysis Signal analysis Algorithm design and analysis

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A Kernel change detection Algorithm in Remote Sense Imagery

A Kernel Change Detection Algorithm in Remote Sense Imagery

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Guorui Ma Haigang Sui Pingxiang Li Qianqing Qin Wuhan University Wuhan Hubei CN

This paper proposes a novel kernel change detection algorithm (KCD). The input vectors from two images of different times are mapped into a potential much higher dimensional feature space via a nonlinear mapping, which will usually increase the linear margin of change and no-change regions. Then a simple linear distance measure between two high dimensional feature vectors is defined in features space, which corresponds to the complicated nonlinear distance measure in input space. Furthermore the distance measure's dot product is expressed in the combination of kernel functions and large numbers of dot product processed in input space by combined kernel tactic, which avoids the computational load. Finally this paper takes the soft margin single-class support vector machine (SVM) to select the optimal hyper-plane with maximum margin. Preliminary results show the kernel change detection algorithm (KCD) has excellent performance in accuracy.

关键词： Kernel detection algorithms Remote sensing Extraterrestrial measurements Support vector machines Learning systems Layout change detection algorithms Pixel Object detection

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SAR image restoration and change detection based on game theory

SAR image restoration and change detection based on game the...

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International Conference on Intelligent Computing and Internet of Things (ICIT)

作者： Chujian Bi Qiushi Zhang Rui Bao Haoxiang Wang Dept. of Electrical and Computer Engineering University of Minnesota Minneapolis USA Northwestern Polytechnical University Xi'an China Dept. of Science and Applied Math National University of Singapore Singapore Dept. of Electrical and Computer Engineering Cornell University New York USA

ISBN: (纸本)9781479975358

In this paper, a novel unsupervised change detection algorithm based on game theory is proposed for synthetic aperture radar(SAR) images. With the introduction of Nash-game theory, we find the balance of segmentation accuracy and overall restoration performance. Restoration of images plays a denoising role due to the complex movement while obtaining a SAR image. The Segmentation procedure transfers the difference map into change map. To make the algorithm less time-consuming, we analyze the state-of-the-art methods for generating the change map and finally select the minus map as the preferred one. The experiment based on the proposed methodology proves the accuracy and robustness of our algorithm compared with several well-known change detection techniques on both noise-free and noisy satellite images. Further optimization methods are discussed in the end.

关键词： Game theory Image restoration Image segmentation change detection algorithms Synthetic aperture radar Optimization Algorithm design and analysis

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