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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Shuyuan Zhu Bing Zeng Moncef Gabbouj Institute of Image Processing University of Electronic Science and Technology of China Chengdu China Department of Signal Processing Tampere University of Technology Tampere Finland

ISBN: (纸本)9781479934331

According to the compressed sensing (CS) theory, a signal that is sparse in a certain domain can be nearly exactly recovered from a few measurements where the sampling rate is lower than the Nyquist rate. This theory has been successfully applied to the image compression in the past few years as most image signals are highly sparse. In this paper, we apply an adaptive sampling mechanism to the reweighted block-based CS (BCS). The proposed adaptive sampling allocates the measurements to each image block according to the statistical information of the block so as to sample and recover the image more efficiently. Experimental results demonstrate that our adaptive reweighted method offers a very significant quality improvement compared with the traditional BCS schemes, including the non-reweighted and reweighted ones.

关键词： Resource management Compressed sensing image coding image reconstruction Sparse matrices Discrete cosine transforms

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Effect of channel aging on the sum rate of uplink massive MIMO systems

Effect of channel aging on the sum rate of uplink massive MI...

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IEEE International Symposium on Information Theory

作者： Chuili Kong Caijun Zhong Anastasios K. Papazafeiropoulos Michail Matthaiou Zhaoyang Zhang Institute of Information and Communication Engineering Zhejiang University Hangzhou China National Mobile Communications Research Laboratory Southeast University Nanjing China Communications and Signal Processing Group Imperial College London London U.K Department of Signals and Systems Chalmers University of Technology Gothenburg Sweden Electrical Engineering and Computer Science Queen's University Belfast Belfast U.K

ISBN: (纸本)9781467377058

This paper investigates the achievable sum-rate of uplink massive multiple-input multiple-output (MIMO) systems considering a practical channel impairment, namely, aged channel state information (CSI). Taking into account both maximum ratio combining (MRC) and zero-forcing (ZF) receivers at the base station, we present tight closed-form lower bounds on the sum-rate for both receivers, which provide efficient means to evaluate the sum-rate of the system. More importantly, we characterize the impact of channel aging on the power scaling law. Specifically, we show that the transmit power of each user can be scaled down by 1/√(M), which indicates that aged CSI does not affect the power scaling law; instead, it causes only a reduction on the sum rate by reducing the effective signal-to-interference-and-noise ratio (SINR).

关键词： Aging MIMO Receivers Uplink Channel estimation Antennas Training

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Reinforcement learning based predictive maintenance for a machine with multiple deteriorating yield levels

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Journal of Computational Information Systems 2014年第1期10卷 9-19页

作者： Wang, Xiao Wang, Hongwei Qi, Chao Sivakumar, Appa Iyer State Key Laboratory of Education Ministry for Image Processing and Intelligent Control Institute of Systems Engineering Huazhong University of Science and Technology Wuhan 430074 China School of Safety Engineering Shenyang Aerospace University Shenyang 110136 China Division of Systems and Engineering Management School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore Singapore

This paper proposes a predictive maintenance methodology for a machine in manufacturing with deteriorating quality states represented by multiple deteriorating yield levels. Imperfect minor maintenance and perfect major repair are considered. The underlying yield level cannot be directly obtained. Instead, product quality inspection information is used as the observed system state. The optimal maintenance policy associated with each possible observed system state is learnt by modeling the problem as hidden semi-Markov decision processes and solving it using policy iteration based Q-P learning. Then the future maintenance time can be estimated by re-simulating the system model using the learned maintenance policy. A set of experimental studies is conducted to testify the effectiveness of the proposed methodology and to investigate the impacts of involved system parameters. Copyright © 2014 Binary Information Press.

关键词： Markov processes

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Quantitative identification of yellow rust, powdery mildew and fertilizer-water stress in winter wheat using In-Situ hyperspectral data

Quantitative identification of yellow rust, powdery mildew a...

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作者： Guan, Qingsong Huang, Wenjiang Zhao, Jinling Liu, Liangyun Liang, Dong Huang, Linsheng Wang, Li Yang, Guijun Key Laboratory of Digital Earth Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei Anhui China Beijing Agriculture Information Technology Research Center Beijing China

As the progressive effects of global warming, the yield loss caused by diseases and pests are increasing in winter wheat. It is necessary to distinguish different diseases for guiding variable rate spraying in wheat. Nevertheless, it is very difficult to quantitatively identify different diseases and fertilizer-water stress by specific sensitive bands selected from multi spectral data over a large area. Conversely, hyper spectral data contain more information, and provide the potential for quantitative identification of different stresses. This study focused on identification and distinction of yellow rust, powdery mildew and fertilizer-water stress by canopy spectral reflectance. Fifteen commonly used vegetation indices were selected, and independent t-test was done to get sensitivity index for each stress. Finally, a combination index was optimally selected to distinguish the three stresses. The results showed that the integrative index (NDVI-PhRI) combining normalized difference vegetation index (NDVI) and physiological reflectance index (PhRI) could be used to identify powdery mildew and yellow rust (PM-YR). A 2-dimensional spatial coordinate was established based on the NDVI and PhRI derived from hyper spectral data, then the different stress data were displayed in the spatial coordinate and the classification boundary could be used to identify the powdery mildew and yellow rust stress. Similarly, yellow rust and fertilizer-water stress (YR-n0w0) can be distinguished by the combination index (MSR-PhRI) derived from modified simple ratio (MSR) and physiological reflectance index (PhRI);and the combination index (NRI-RVSI) derived from nitrogen reflectance index (NRI) and red-edge vegetation stress index (RVSI) was accurate to identify powdery mildew and fertilizer-water stress (PM-n0w0). For the PM-YR, YR-n0w0 and PM-n0w0 models, their verification accuracies were 83.3%, 88%, 88.75%, and the kappa accuracies were 63.41%, 74.79%, 71.43%, respectively. It indicate

关键词： Physiology

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Texture Classification Using Joint Statistical Representation in Space-frequency Domain with Local Quantized Patterns

Texture Classification Using Joint Statistical Representatio...

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IEEE International Symposium on Circuits and Systems

作者： Tiecheng Song Hongliang Li Bing Zeng Moncef Gabbouj Institute of Image Processing University of Electronic Science and Technology of China Chengdu 611731 China Department of Signal Processing Tampere University of Technology P.O. Box 553 FIN-33101 Tampere Finland

ISBN: (纸本)9781479934331

Despite its success in texture analysis, Local Binary Pattern (LBP) is operated in the original image space, and it fails to capture deeper pixel interactions to provide a more discriminative description. In this paper, we propose to explore the joint statistical representation in the space-frequency domain with local quantized patterns for texture classification. The proposed method consists of two channels. In each channel, the multi-resolution spatial filters are employed to generate multi-scale spatial maps and the local Fourier transform is subsequently applied to extract local frequency features (spectral maps). The global thresholding is adopted to quantize the spatial and spectral maps into different levels, which are then jointly encoded to built a space-frequency co-occurrence histogram. Finally, the two-channel feature histograms are combined to represent the texture. Experiments on the Outex texture database demonstrate the robustness of our method to image rotation and illumination changes, and our method outperforms the state of the art in terms of the classification accuracy.

关键词： original LBP classification LBP gene LBP textures texture state of the art image rotation local frequency ORIGINAL original image 2-channel Space Frequency-domain analysis texture analysis Taxonomy histograms

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Fuzzy networks: What happens when fuzzy people are connected through social networks

Fuzzy networks: What happens when fuzzy people are connected...

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IEEE Symposium on Foundations of Computational Intelligence, FOCI

作者： Li-Xin Wang Jerry M. Mendel Department of Automation Science and Technology Xian Jiaotong University Xian China Signal and Image Processing Institute University of Southern California Los Angeles CA USA

A fuzzy node is a fuzzy set whose membership function contains some uncertain parameters. Two fuzzy nodes are connected if the uncertain parameter of one node is provided by the fuzzy set from the other node. A fuzzy network is a connection of a number of fuzzy nodes. We define Gaussian Fuzzy Networks and study a number of basic connections in details, including basic center, basic standard deviation (sdv), basic center-sdv, chain-in-center, chain-in-sdv, self-feedback and some other connections. We derive the membership functions resulting from these connections that reveal how the fuzziness is propagated through the networks, and we explain what the mathematical results mean with respect to human behaviors.

关键词： Fuzzy sets Standards Uncertainty Bayes methods Social network services Network theory (graphs) Pragmatics

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Extracting commuting patterns in railway networks through matrix decompositions 13

Extracting commuting patterns in railway networks through ma...

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2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014

作者： Jere, Shashank Dauwels, Justin Asif, Muhammad Tayyab Vie, Nikola Mitro Cichocki, Andrzej Jaillet, Patrick School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Laboratory for Advanced Brain Signal Processing RIKEN Brain Science Institute Japan Laboratory for Information and Decision Systems MIT CambridgeMA United States Center for Future Urban Mobility Singapore-MIT Alliance for Research and Technology Singapore Singapore

ISBN: (纸本)9781479951994

With the rise in the population of the world's cities, understanding the dynamics of commuters' transportation patterns has become crucial in the planning and management of urban facilities and services. In this study, we analyze how commuter patterns change during different time instances such as between weekdays and weekends. To this end, we propose two data mining techniques, namely Common Orthogonal Basis Extraction (COBE), and Joint and Individual Variation Explained (JIVE) for Integrated Analysis of Multiple Data Types and apply them to smart card data available for passengers in Singapore. We also discuss the issues of model selection and interpretability of these methods. The joint and individual patterns can help transportation companies optimize their resources in light of changes in commuter mobility behavior. © 2014 IEEE.

关键词： Smart cards

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Predicting traffic speed in urban transportation subnetworks for multiple horizons 13

Predicting traffic speed in urban transportation subnetworks...

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2014 13th International Conference on Control Automation Robotics and Vision, ICARCV 2014

作者： Dauwels, Justin Aslam, Aamer Asif, Muhammad Tayyab Zhao, Xinyue Vie, Nikola Mitro Cichocki, Andrzej Jaillet, Patrick School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Laboratory for Advanced Brain Signal Processing Brain Science Institute RIKEN Saitama Japan Laboratory for Information and Decision Systems MIT CambridgeMA United States Center for Future Urban Mobility Singapore-MIT Alliance for Research and Technology Singapore Singapore

ISBN: (纸本)9781479951994

Traffic forecasting is increasingly taking on an important role in many intelligent transportation systems (ITS) applications. However, prediction is typically performed for individual road segments and prediction horizons. In this study, we focus on the problem of collective prediction for multiple road segments and prediction-horizons. To this end, we develop various matrix and tensor based models by applying partial least squares (PLS), higher order partial least squares (HO-PLS) and N-way partial least squares (N-PLS). These models can simultaneously forecast traffic conditions for multiple road segments and prediction-horizons. Moreover, they can also perform the task of feature selection efficiently. We analyze the performance of these models by performing multi-horizon prediction for an urban subnetwork in Singapore. © 2014 IEEE.

关键词： Forecasting

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Multiple description coding with randomly and uniformly offset quantizers

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IEEE Transactions on image processing 2014年第2期23卷 582-595页

作者： Meng, Lili Liang, Jie Samarawickrama, Upul Zhao, Yao Bai, Huihui Kaup, Andre Institute of Information Science Beijing Jiaotong University Beijing 100044 China School of Information Science and Engineering Shandong Normal University Jinan 730050 China School of Engineering Science Simon Fraser University Burnaby BC V5A 1S6 Canada Microsoft Corporation Redmond WA 98052 United States State Key Laboratory of Rail Traffic Control and Safety Beijing 100044 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing 100011 China Department of Multimedia Communications and Signal Processing University of Erlangen-Nuremberg Erlangen 91058 Germany

In this paper, two multiple description coding schemes are developed, based on prediction-induced randomly offset quantizers and unequal-deadzone-induced near-uniformly offset quantizers, respectively. In both schemes, each description encodes one source subset with a small quantization stepsize, and other subsets are predictively coded with a large quantization stepsize. In the first method, due to predictive coding, the quantization bins that a coefficient belongs to in different descriptions are randomly overlapped. The optimal reconstruction is obtained by finding the intersection of all received bins. In the second method, joint dequantization is also used, but near-uniform offsets are created among different low-rate quantizers by quantizing the predictions and by employing unequal deadzones. By generalizing the recently developed random quantization theory, the closed-form expression of the expected distortion is obtained for the first method, and a lower bound is obtained for the second method. The schemes are then applied to lapped transform-based multiple description image coding. The closed-form expressions enable the optimization of the lapped transform. An iterative algorithm is also developed to facilitate the optimization. Theoretical analyzes and image coding results show that both schemes achieve better performance than other methods in this category. © 1992-2012 IEEE.

关键词： image coding

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Multiuser Massive MIMO Uplink Performance with Mutual Coupling Effects

Multiuser Massive MIMO Uplink Performance with Mutual Coupli...

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IEEE Global Communications Conference

作者： Ran Zi Xiaohu Ge Haichao Wang Jing Zhang Cheng-Xiang Wang Dept. Electronics & Information Engineering Huazhong University of Science & Technology Joint Research Institute for Signal and Image Processing School of Engineering & Physical Sciences Heriot-Watt University

ISBN: (纸本)9781479935130

A multiuser massive MIMO system with mutual coupling is investigated in finite-dimensional channel scenarios. The uplink ergodic achievable rate is analytically derived for a multiuser massive MIMO system equipped with a rectangular planar uniform antenna array at the base station (BS). Numerical results show that the mutual coupling effect reduces the uplink achievable rate of multiuser massive MIMO systems when the antenna distance decreases. But when the size of the antenna array is fixed, the uplink achievable rate increases with the growing of antenna number.

关键词： Massive MIMO Mutual coupling Multiuser MIMO Finite-dimensional channel

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