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An Unsupervised Algorithm for Change Detection in Hyperspectral Remote Sensing Data Using Synthetically Fused Images and Derivative Spectral Profiles

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JOURNAL OF SENSORS 2017年第8-10期2017卷 9702612-9702612页

作者： Han, Youkyung Chang, Anjin Choi, Seokkeun Park, Honglyun Choi, Jaewan Kyungpook Natl Univ Sch Convergence & Fus Syst Engn Sangju 37224 South Korea Texas A&M Univ Corpus Christi Sch Engn & Comp Sci 6300 Ocean Dr Corpus Christi TX 78412 USA Chungbuk Natl Univ Sch Civil Engn 1 Chungdae Ro Cheongju 28644 Chungbuk South Korea

Multitemporal hyperspectral remote sensing data have the potential to detect altered areas on the earth's surface. However, dissimilar radiometric and geometric properties between the multitemporal data due to the acquisition time or position of the sensors should be resolved to enable hyperspectral imagery for detecting changes in natural and human-impacted areas. In addition, data noise in the hyperspectral imagery spectrum decreases the change-detection accuracy when general change-detection algorithms are applied to hyperspectral images. To address these problems, we present an unsupervised change-detection algorithm based on statistical analyses of spectral profiles;the profiles are generated from a synthetic image fusion method for multitemporal hyperspectral images. This method aims to minimize the noise between the spectra corresponding to the locations of identical positions by increasing the change-detection rate and decreasing the false-alarm rate without reducing the dimensionality of the original hyperspectral data. Using a quantitative comparison of an actual dataset acquired by airborne hyperspectral sensors, we demonstrate that the proposed method provides superb change-detection results relative to the state-of-the-art unsupervised change-detection algorithms.

关键词： computer algorithms Remote sensing Surface of the earth Hyperspectral imaging systems Detectors

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Advanced Image Enhancement Method for Distant Vessels and Structures in Capsule Endoscopy

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COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2017年第1期2017卷 1-13页

作者： Rukundo, Olivier Pedersen, Marius Hovde, Oistein Norwegian Univ Sci & Technol Dept Comp Sci Trondheim Norway Innlandet Hosp Trust Dept Gastroenterol N-2819 Gjovik Norway

This paper proposes an advanced method for contrast enhancement of capsule endoscopic images, with the main objective to obtain sufficient information about the vessels and structures in more distant (or darker) parts of capsule endoscopic images. The proposed method (PM) combines two algorithms for the enhancement of darker and brighter areas of capsule endoscopic images, respectively. The half-unit weighted-bilinear algorithm (HWB) proposed in our previous work is used to enhance darker areas according to the darker map content of its HSV's component V. Enhancement of brighter areas is achieved thanks to the novel threshold weighted-bilinear algorithm (TWB) developed to avoid overexposure and enlargement of specular highlight spots while preserving the hue, in such areas. The TWB performs enhancement operations following a gradual increment of the brightness of the brighter map content of its HSV's component V. In other words, the TWB decreases its averaged weights as the intensity content of the component.. increases. Extensive experimental demonstrations were conducted, and, based on evaluation of the reference and PM enhanced images, a gastroenterologist (O.H.) concluded that the PM enhanced images were the best ones based on the information about the vessels, contrast in the images, and the view or visibility of the structures in more distant parts of the capsule endoscopy images.

关键词： BLOOD-vessels CAPSULE endoscopy CONTRAST media (Diagnostic imaging) ENDOSCOPY computer algorithms

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A Combined One-Class SVM and Template-Matching Approach for User-Aided Human Fall Detection by Means of Floor Acoustic Features

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COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2017年第20170101期2017卷 1512670-1512670页

作者： Droghini, Diego Ferretti, Daniele Principi, Emanuele Squartini, Stefano Piazza, Francesco Univ Politecn Marche Dept Informat Engn Via Brecce Bianche I-60131 Ancona Italy

The primary cause of injury-related death for the elders is represented by falls. The scientific community devoted them particular attention, since injuries can be limited by an early detection of the event. The solution proposed in this paper is based on a combined One-Class SVM (OCSVM) and template-matching classifier that discriminate human falls from nonfalls in a semisupervised framework. Acoustic signals are captured by means of a Floor Acoustic Sensor;then Mel-Frequency Cepstral Coefficients and Gaussian Mean Supervectors (GMSs) are extracted for the fall/nonfall discrimination. Here we propose a single-sensor two-stage user-aided approach: in the first stage, the OCSVM detects abnormal acoustic events. In the second, the template-matching classifier produces the final decision exploiting a set of template GMSs related to the events marked as false positives by the user. The performance of the algorithm has been evaluated on a corpus containing human falls and nonfall sounds. Compared to the OCSVM only approach, the proposed algorithm improves the performance by 10.14% in clean conditions and 4.84% in noisy conditions. Compared to Popescu and Mahnot (2009) the performance improvement is 19.96% in clean conditions and 8.08% in noisy conditions.

关键词： FALLS (Accidents) ACOUSTIC devices GAUSSIAN processes computer algorithms MEDICAL decision making TASK performance

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Adaptive Active Noise Suppression Using Multiple Model Switching Strategy

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SHOCK AND VIBRATION 2017年第1期2017卷 1-6页

作者： Huang, Quanzhen Chen, Suxia Huang, Mingming Guo, Zhuangzhi Henan Inst Engn Sch Elect Informat Engn Zhengzhou 451191 Peoples R China Henan Inst Engn Sch Comp Zhengzhou 451191 Peoples R China

Active noise suppression for applications where the system response varies with time is a difficult problem. The computation burden for the existing control algorithms with online identification is heavy and easy to cause control system instability. A new active noise control algorithm is proposed in this paper by employing multiple model switching strategy for secondary path varying. The computation is significantly reduced. Firstly, a noise control system modeling method is proposed for duct-like applications. Then a multiple model adaptive control algorithm is proposed with a new multiple model switching strategy based on filter-u least mean square (FULMS) algorithm. Finally, the proposed algorithm was implemented on Texas Instruments digital signal processor (DSP) TMS320F28335 and real time experiments were done to test the proposed algorithm and FULMS algorithm with online identification. Experimental verification tests show that the proposed algorithm is effective with good noise suppression performance.

关键词： ACTIVE noise control DIGITAL signal processing COMPUTATIONAL complexity LEAST squares computer algorithms

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Two-Dimensional DOA Estimation Using Arbitrary Arrays for Massive MIMO Systems

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INTERNATIONAL JOURNAL OF ANTENNAS AND PROPAGATION 2017年第12-17期2017卷 6794920-6794920页

作者： Lonkeng, Alban Doumtsop Zhuang, Jie Univ Elect Sci & Technol China Sch Commun & Informat Engn Chengdu 611731 Sichuan Peoples R China

With the quick advancement of wireless communication networks, the need for massive multiple-input-multiple-output (MIMO) to offer adequate network capacity has turned out to be apparent. As a portion of array signal processing, direction-of-arrival (DOA) estimation is of indispensable significance to acquire directional data of sources and to empower the 3D beamforming. In this paper, the performance of DOA estimation for massive MIMO systems is analyzed and compared using a low-complexity algorithm. To be exact, the 2D Fourier domain line search (FDLS) MUSIC algorithm is studied to mutually estimate elevation and azimuth angle, and arbitrary array geometry is utilized to represent massive MIMO systems. To avoid the computational burden in estimating the data covariance matrix and its eigenvalue decomposition (EVD) due to the large-scale sensors involved in massive MIMO systems, the reduced-dimension data matrix is applied on the signals received by the array. The performance is examined and contrasted with the 2D MUSIC algorithm for different types of antenna configuration. Finally, the array resolution is selected to investigate the performance of elevation and azimuth estimation. The effectiveness and advantage of the proposed technique have been proven by detailed simulations for different types of MIMO array configuration.

关键词： MIMO systems Signal processing Beamforming Wireless communication systems Computational complexity computer algorithms Decomposition (Mathematics)

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An Improved Multiobjective Particle Swarm Optimization Algorithm Using Minimum Distance of Point to Line

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SHOCK AND VIBRATION 2017年第1期2017卷 1-16页

作者： Fan, Zhengwu Wang, Tie Cheng, Zhi Li, Guoxing Gu, Fengshou Taiyuan Univ Technol Dept Vehicle Engn Taiyuan Shanxi Peoples R China Taiyuan Univ Sci Technol Dept Mech Engn Taiyuan Shanxi Peoples R China Univ Huddersfield Ctr Efficiency & Performance Engn Huddersfield HD1 3DH W Yorkshire England

In a multiobjective particle swarm optimization algorithm, selection of the global best particle for each particle of the population from a set of Pareto optimal solutions has a significant impact on the convergence and diversity of solutions, especially when optimizing problems with a large number of objectives. In this paper, a new method is introduced for selecting the global best particle, which is minimum distance of point to line multiobjective particle swarmoptimization (MDPL-MOPSO). Using the basic concept of minimum distance of point to line and objective, the global best particle among archive members can be selected. Different test functions were used to test and compare MDPL- MOPSO with CD-MOPSO. The result shows that the convergence and diversity of MDPL- MOPSO are relatively better than CD-MOPSO. Finally, the proposed multiobjective particle swarm optimization algorithm is used for the Pareto optimal design of a five-degree-of-freedom vehicle vibration model, which resulted in numerous effective trade-offs among conflicting objectives, including seat acceleration, front tire velocity, rear tire velocity, relative displacement between sprung mass and front tire, and relative displacement between sprung mass and rear tire. The superiority of this work is demonstrated by comparing the obtained results with the literature.

关键词： PARTICLE swarm optimization computer algorithms MATHEMATICAL optimization DEGREES of freedom ANALYSIS of variance

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Fast Constrained Spectral Clustering and Cluster Ensemble with Random Projection

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COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE 2017年第1期2017卷 2658707-2658707页

作者： Liu, Wenfen Ye, Mao Wei, Jianghong Hu, Xuexian Guilin Univ Elect Technol Sch Comp Sci & Informat Secur Guangxi Key Lab Cryptogp & Informat Secur Guilin 541004 Peoples R China Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China State Key Lab Math Engn & Adv Comp Zhengzhou 450002 Henan Peoples R China Natl Univ Def Technol Nanjing 210012 Jiangsu Peoples R China

Constrained spectral clustering (CSC) method can greatly improve the clustering accuracy with the incorporation of constraint information into spectral clustering and thus has been paid academic attention widely. In this paper, we propose a fast CSC algorithm via encoding landmark-based graph construction into a new CSC model and applying random sampling to decrease the data size after spectral embedding. Compared with the original model, the new algorithm has the similar results with the increase of its model size asymptotically;compared with the most efficient CSC algorithm known, the new algorithm runs faster and has a wider range of suitable data sets. Meanwhile, a scalable semisupervised cluster ensemble algorithm is also proposed via the combination of our fast CSC algorithm and dimensionality reduction with random projection in the process of spectral ensemble clustering. We demonstrate by presenting theoretical analysis and empirical results that the new cluster ensemble algorithm has advantages in terms of efficiency and effectiveness. Furthermore, the approximate preservation of random projection in clustering accuracy proved in the stage of consensus clustering is also suitable for the weighted kappa-means clustering and thus gives the theoretical guarantee to this special kind of kappa-means clustering where each point has its corresponding weight.

关键词： RANDOM projection method ENSEMBLES (Mathematics) SAMPLING (Statistics) computer algorithms SET theory

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Molecular system identification for enzyme directed evolution and design

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JOURNAL OF CHEMICAL PHYSICS 2017年第12期147卷 124106-124106页

作者： Guan, Xiangying Chakrabarti, Raj Chakrabarti Adv Technol Div Fundamental Res Mt Laurel NJ 08054 USA

The rational design of chemical catalysts requires methods for the measurement of free energy differences in the catalytic mechanism for any given catalyst Hamiltonian. The scope of experimental learning algorithms that can be applied to catalyst design would also be expanded by the availability of such methods. Methods for catalyst characterization typically either estimate apparent kinetic parameters that do not necessarily correspond to free energy differences in the catalytic mechanism or measure individual free energy differences that are not sufficient for establishing the relationship between the potential energy surface and catalytic activity. Moreover, in order to enhance the duty cycle of catalyst design, statistically efficient methods for the estimation of the complete set of free energy differences relevant to the catalytic activity based on high-throughput measurements are preferred. In this paper, we present a theoretical and algorithmic system identification framework for the optimal estimation of free energy differences in solution phase catalysts, with a focus on one- and two-substrate enzymes. This framework, which can be automated using programmable logic, prescribes a choice of feasible experimental measurements and manipulated input variables that identify the complete set of free energy differences relevant to the catalytic activity and minimize the uncertainty in these free energy estimates for each successive Hamiltonian design. The framework also employs decision-theoretic logic to determine when model reduction can be applied to improve the duty cycle of high-throughput catalyst design. Automation of the algorithm using fluidic control systems is proposed, and applications of the framework to the problem of enzyme design are discussed. Published by AIP Publishing.

关键词： FREE energy (Thermodynamics) ENZYMES EVOLUTIONARY theories computer algorithms POTENTIAL energy PROGRAMMABLE logic devices

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Validation of the Decomposition Method for Fast MIMO Over-the-Air Measurements

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INTERNATIONAL JOURNAL OF ANTENNAS AND PROPAGATION 2017年第4-18期2017卷 18-18页

作者： Auinger, Bernhard Zemen, Thomas Gadringer, Michael Tankielun, Adam Gagern, Christoph Boesch, Wolfgang Graz Univ Technol Graz Austria Austrian Inst Technol Vienna Austria Rohde & Schwarz Munich Germany

Over-the-air (OTA) throughput tests of wireless Multiple-Input Multiple-Output (MIMO) devices are an important tool for network operators and manufacturers. The user equipment (UE) is placed in an anechoic chamber and a random fading process is emulated by a base-station emulator (BSE). The antenna characteristic of the UE is taken into account by sampling the sphere around the UE with the BSE test antenna at a large number of positions. For low- variance throughput results, long measurement intervals over many fading realizations are required, leading to long and expensive measurement periods in an anechoic chamber. To speed up the OTA test, we analyze the Decomposition Method (DM). The DM splits the throughput measurement into two parts: (1) a receiver algorithm performance tests taking the fading process into account and (2) an antenna performance test without fading process emulation. Both results are combined into a single throughput estimate. The DM allows for a measurement time reduction of more than one order of magnitude. We provide an analytic and numerical analysis as well as measurements. Our detailed results show the validity of the DM in all practical settings.

关键词： MIMO systems Anechoic chambers computer algorithms Decomposition method (Mathematics) Numerical analysis

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Pedestrian Stride Length Estimation from IMU Measurements and ANN Based Algorithm

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JOURNAL OF SENSORS 2017年第2-9期2017卷 6091261-6091261页

作者： Xing, Haifeng Li, Jinglong Hou, Bo Zhang, Yongjian Guo, Meifeng Tsinghua Univ Dept Precis Instruments Engn Res Ctr Nav Technol Beijing 100084 Peoples R China

Pedestrian dead reckoning (PDR) can be used for continuous position estimation when satellite or other radio signals are not available, and the accuracy of the stride length measurement is important. Current stride length estimation algorithms, including linear and nonlinear models, consider a few variable factors, and some rely on high precision and high cost equipment. This paper puts forward a stride length estimation algorithm based on a back propagation artificial neural network (BP-ANN), using a consumer-grade inertial measurement unit (IMU);it then discusses various factors in the algorithm. The experimental results indicate that the error of the proposed algorithm in estimating the stride length is approximately 2%, which is smaller than that of the frequency and nonlinear models. Compared with the latter two models, the proposed algorithm does not need to determine individual parameters in advance if the trained neural net is effective. It can, thus, be concluded that this algorithm shows superior performance in estimating pedestrian stride length.

关键词： Neural networks (computer science) Length measurement Back propagation (Artificial intelligence) computer algorithms Nonlinear models (Statistics)

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