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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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SAR Image Fusion Based on Mathematical Frame

SAR Image Fusion Based on Mathematical Frame

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Asian and Pacific Conference on Synthetic Aperture Radar (APSAR)

作者： Yang Liu GuiSheng Liao ShiDong Li GuoLi Nie Cao Zeng PeiJu Du National Laboratory of Radar Signal Processing XiDian University Xi'an China San Francisco State University San Francisco The United States of America International Cooperation Base of Integrated Electronic Information System of Ministry of Science and Technology XiDian University Xi'an China Radar Cognitive Detection Imaging and Target Recognition Overseas Expertises introduction Center for Discipline innovation XiDian University Xi'an China

ISBN: (数字)9781728129129

ISBN: (纸本)9781728129136

In this paper, we proposed a frame-based approach to synthetic aperture radar (SAR) images fusion. Specifically, the method consists two parts: image fusion preprocessing and fusion reconstruction. Firstly, we fuse a set of low-resolution (LR) SAR images to form an aligned coarse SAR image which still has image blur caused by the point spread function (PSF) by fusion preprocessing. Then Frame fundamental iterative regularization is used to reconstruct high-resolution (HR) SAR image. Both simulated and real SAR images are used to verify the validity of the method. The results show that details and definition of the LR image processed with the method are effectively improved.

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Advances in nonnegative matrix and tensor factorization

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Computational Intelligence and Neuroscience 2008年第1期2008卷 852187页

作者： Wang, W. Cichocki, A. Mørup, M. Smaragdis, P. Zdunek, R. Laboratory for Advanced Brain Signal Processing RIKEN Brain Science Institute Saitama 351-0198 Japan Department of Informatics and Mathematical Modeling Technical University of Denmark Building 321 2800 Lyngby Richard Petersens Plads Denmark Advanced Technology Labs. Adobe Systems Inc. Newton MA 02466 275 Grove Street United States Centre for Vision Speech and Signal Processing University of Surrey Guildford GU2 7XH United Kingdom Institute of Telecommunications Teleinformatics and Acoustics Wroclaw University of Technology Wybrzeze 50370 Wroclaw Wyspianskiego 27 Poland

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Deterministic realization of collective measurements via photonic quantum walks

Deterministic realization of collective measurements via pho...

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第十八届全国量子光学学术会议

作者：侯志博 Jun-Feng Tang Yuan Yuan Kang-Da Wu Guo-Yong Xiang Chuan-Feng Li Guang-Can Guo Jiangwei Shang Huangjun Zhu Jian Li 中科大 Key Laboratory of Quantum Information University of Science and Technology of ChinaCAS Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of China Naturwissenschaftlich-Technische Fakult?t Universit?t Siegen Beijing Key Laboratory of Nanophotonics and Ultrafine Optoelectronic Systems School of PhysicsBeijing Institute of Technology Institute for Theoretical Physics University of Cologne Department of Physics and Center for Field Theory and Particle Physics Fudan University State Key Laboratory of Surface Physics Fudan University Collaborative Innovation Center of Advanced Microstructures Institute of Signal Processing Transmission Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and TelecommunicationsMinistry of Education

Collective measurements on identically prepared quantum systems can extract more information than local measurements, thereby enhancing information-processing efficiency. Although this nonclassical phenomenon has been known for two decades, it has remained a challenging task to demonstrate the advantage of collective measurements in experiments. Here, we introduce a general recipe for performing deterministic collective measurements on two identically prepared qubits based on quantum walks. Using photonic quantum walks, we realize experimentally an optimized collective measurement with fidelity 0.9946 without post selection. As an application, we achieve the highest tomographic efficiency in qubit state tomography to date. Our work offers an effective recipe for beating the precision limit of local measurements in quantum state tomography and metrology. In addition, our study opens an avenue for harvesting the power of collective measurements in quantum information processing and for exploring the intriguing physics behind this power.

关键词： Deterministic realization of collective measurements via photonic quantum walks

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A co-evolutionary particle swarm optimization with dynamic topology for solving multi-objective optimization problems

Advances in Modelling and Analysis A

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Advances in Modelling and Analysis A 2016年第1期53卷 145-159页

作者： Wu, Daqing Tang, Lixiang Li, Haiyan Ouyang, LiJun Computer Science and Technology Institute University of South China HangyangHunan China Antai College of Economics and Management Shanghai Jiao Tong University Shanghai200240 China Zigong643000 China Key Laboratory of Guangxi High Schools for Complex System and Computational Intelligence Guangxi University for Nationalities Nanning530006 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University HefeiAnhui Province230039 China Department of Business Administration Hunan University of Finance and Economics Hunan410205 China

This paper proposes a multi-objective with dynamic topology particle swarm optimization (PSO) algorithm for solving multi-objective problems, named DTPSO. One of the main drawbacks of classical multi-objective particle swarm optimization algorithm is low diversity. To overcome this disadvantage, DTPSO uses two dynamic local best particles to lead the search particles with multiple populations to deal with multiple objectives, and maintains diversity of new found non-dominated solutions via partitioned the searching space into fixed number of cells. The proposed DTPSO is validated through comparisons with other two multi-objective algorithms using established benchmarks and metrics. Simulation results demonstrated that DTPSO shows competitive, if not better, performance as compared to the other algorithms. © 2016, AMSE Press. All rights reserved.

关键词： Multiobjective optimization

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Tensor-based Gaussian processes regression using a probabilistic kernel with information divergence

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International Journal of Simulation: Systems, science and technology 2015年第5期16卷 13.1-13.7页

作者： Tang, Lingbing Peng, Pin Zhao, Qibin Gui, Lihua Qing, Luochang Mobile E-business Collaborative Innovation Center of Hunan Province Hunan University of Commerce ChangshaHunan410205 China Key Laboratory of Hunan Province for Mobile Business Intelligence ChangshaHunan410205 China Lab.for Advanced Brain Signal Processing Brain Science Institute RIKEN 2-1 Hirosawa WakoshiSaitama Japan Graduate School of Engineering Saitama Institute of Technology Japan School of Finance and Banking Hunan University of Commerce ChangshaHunan410205 China

We present a Gaussian processes regression for tensor-valued inputs, which is based on a coherent treatment of a prior for the latent function with a covariance function defined on a tensor representation of multivariate data. Such a rigorous account of the underlying data dependencies within the model is also the basis for a new and powerful framework for structural data analysis. This is achieved under the assumption of generative models, and by introducing a family of probabilistic kernels with tensor arguments. By equipping these product kernels with the Jensen-Shannon divergence measure for tensorial data, the proposed model can be considered as both a generative and discriminative model. Further, a fully Bayesian treatment is used to estimate the hyperparameters and infer the predictive distributions. Experimental results on a real world application of decoding 3D movement trajectory based on electrocorticography (ECoG) signals recorded from a monkey brain demonstrate the effectiveness and performance advantage of the proposed framework. © 2015, UK Simulation Society. All rights reserved.

关键词： Tensors

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On Error Performance and Concatenated Coding of Polar Codes in AWGN Channels

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IOP Conference Series: Materials science and Engineering 2020年第7期768卷

作者： Jing Jin Rui Deng Tiansheng Liu Liping Li Key Laboratory of Intelligent Computing and Signal Processing (Ministry of Education) Anhui University Hefei China Department of Electronic Engineering and Information Science University of Science and Technology Hefei China

In additive white Gaussian noise (AWGN) channels, construction of polar codes is needed for every operating signal-to-noise ratio (SNR). Recently, the proposal of the design-SNR reduces the computation effort in constructing polar codes. In this paper, we prove that although the BER performance of the design-SNR construction is not affected, the packet-error-rate (PER) performance is degraded compared with the point-by-point construction. Therefore, a concatenation scheme is proposed to improve the degraded PER performance. Results show the validity of the proposed concatenation scheme when employing the design-SNR construction.

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Band Sampling of Hyperspectral Anomaly Detection in Effective Anomaly Space

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IEEE Transactions on Geoscience and Remote Sensing 2024年 62卷 1-29页

作者： Chang, Chein-I Lin, Chien-Yu Hu, Peter Fuming Information and Technology College Dalian116026 China University of Maryland Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering BaltimoreMD21250 United States National Cheng Kung University Department of Electrical Engineering Tainan70101 Taiwan University of Maryland School of Medicine R Adams Cowley Shock Trauma Center Shock Trauma Anesthesia Organized Research Center Department of Anesthesia BaltimoreMD21201 United States

This article investigates four issues, background (BKG) suppression (BS), anomaly detectability, noise effect, and interband correlation reduction (IBCR), which have significant impacts on its performance. Despite that a recently developed effective anomaly space (EAS) was designed to use data sphering (DS) to remove the second-order data statistics characterized by BKG, enhance anomaly detectability, and reduce noise effect, it does not address the IBCR issue. To cope with this issue, this article introduces band sampling (BSam) into EAS to reduce IBCR and further suppress BKG more effectively. By implementing EAS in conjunction with BSam (EAS-BSam), these four issues can be resolved altogether for any arbitrary anomaly detector. It first modifies iterative spectral-spatial hyperspectral anomaly detection (ISSHAD) to develop a new variant of ISSHAD, called iterative spectral-spatial maximal map (ISSMax), and then generalizes ISSMax to EAS-ISSMax, which further enhances anomaly detectability and noise removal. Finally, EAS-BSam is implemented to reduce IBCR. As a result, combining EAS, BSam, and ISSMax yields four versions: EAS-BSam, EAS-ISSMax, BSam-SSMAX, and EAS-BSam-SSMax. Such integration presents a great challenge because all these four versions are derived from different aspects, iterative spectral-spatial feedback process, compressive sensing, and low-rank and sparse matrix decomposition. Experiments demonstrate that EAS-BSam and EAS-BSam-SSMax show their superiority to ISSHAD and many current existing hyperspectral anomaly detection (HAD) methods. © 1980-2012 IEEE.

关键词： Iterative methods

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Iterative Gaussian-Laplacian Pyramid Network for Hyperspectral Image Classification

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IEEE Transactions on Geoscience and Remote Sensing 2024年 62卷 1-22页

作者： Chang, Chein-I Liang, Chia-Chen Hu, Peter Fuming Information and Technology College Dalian116026 China University of Maryland Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering BaltimoreMD21250 United States National Cheng Kung University Department of Electrical Engineering Tainan70101 Taiwan University of Maryland School of Medicine R Adams Cowley Shock Trauma Center Shock Trauma Anesthesia Organized Research Center Department of Anesthesia BaltimoreMD21201 United States

Gaussian pyramid (GP) is a commonly used image coding technique that encodes an image as a pyramid that is stacked by a set of images with Gaussian window-reduced sizes and multiple spatial resolutions. Associated with GP, a Laplacian pyramid (LP) can be also constructed to represent differential images between images in two consecutive layers of GP. Such resulting Gaussian-Laplacian pyramid (GLP) performs data compression in a lossless and lossy manner. A convolutional neural network (CNN) consists of a series of layers concatenated in a feedforward manner where each layer has a convolutional sublayer (CL) and a pooling sublayer (PL). Interestingly, each layer implemented by CL and PL in a CNN can be realized by a single layer in GP in the sense that CL and PL can be carried out by a low-pass Gaussian filter operated as a Gaussian kernel in a single layer of GP. This article develops a new approach to hyperspectral image classification (HSIC), called the GLP network (GLPN), which uses not only GP to realize CNN but also LP to capture differential information between two consecutive layers that CNN cannot. Furthermore, by incorporating an iterative process into GLPN, we can derive an iterative GLPN (IGLPN) that can be considered a companion of a recently developed iterative random training sampling CNN (IRTS-CNN) by replacing CNN with GLPN. Since GLPN can realize CNN in a better way, it is expected that IGLPN will perform better than IRTS-CNN and also significantly reduce computational efficiency compared to IRTS-CNN. © 1980-2012 IEEE.

关键词： Iterative methods

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A Ginzburg-Landau Approach to Field Theories for Single, Isolated Zero-Dimensional Superconductors

SSRN

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SSRN 2022年

作者： Roger Magloire, Keumo Tsiaze Tsague Fotio, Carlos Fotue, Alain Jerve Lukong Fai, Cornelius Talla, Pierre Kisito El Moussaouy, Abdelaziz Mommadi, Omar Kenfack Sadem, Christain Laboratory of Condensed Matter-Electronics and Signal Processing Department of Physics Faculty of Science University of Dschang P.O. Box 479 Dschang Cameroon University of Abomey-Calavi 072 P O Box 50 Cotonou Benin Laboratory of Mechanics Materials and Structures Faculty of Science University of Yaoundé I P.O. Box 812 Yaoundé Cameroon OAPM Group Laboratory of Mechanics Waves Energy and Environment Department of Physics Faculty of Sciences University Mohamed I Oujda60000 Morocco Laboratory of Innovation in Science Technology and Education Regional Centre for the Professions of Education and Training Oujda60000 Morocco Department of Physics Faculty of Science University of Dschang P. O. Box 67 Dschang Cameroon

The letter presents a Ginzburg-Landau theory of fluctuations in superconductors in the zero-dimensional (0D) limit. The central descriptive tool is a complex order parameter interpreted as a self-consistent field describing the centre-of-mass motion of electrons pairs and highlighting a resistance between Cooper pairs. We describe the temperature and size dependences of superconductivity in single, isolated 0D superconductors taking into account an intrinsic energy parameter related to confined geometries. It is shown that all the superconducting effects arise only from the existence of fluctuation-induced superconductivity. The results obtained show that the electronic structure of 0D superconductors goes through several phases with qualitatively different properties. The dimensional dependence of thermodynamic quantities is particularly highlighted and thermodynamic properties of 0D fields are discussed and compared in relation to those of bulk fields. Individual grains of $^{127}\mathrm{Al}$ and $^{207}\mathrm{Pb}$ as well as granular superconductors are provided in support of the analysis © 2022, The Authors. All rights reserved.

关键词： Thermodynamic properties

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