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IEEE International Conference on Image Processing (ICIP 2006)

作者： Wei, Xiaohui Chu, Mei Yi Ahmad, Ishfaq Liang, Yongfang Univ Texas Dept Comp Sci & Engn Arlington TX 76019 USA

ISBN: (纸本)9781424404810

Exploitation of redundancies for superior coding efficiency is one of the major research issues in multi-view video coding (MVC). However, this incurs extra computation, counteracting the benefit gained from coding efficiency. This paper exploits inter-view correlations among video objects and background to lower the prediction complexity while achieving high coding efficiency in MVC. We propose an effective object-based scheme that utilizes video object information obtained from the coded base view. This information assists to predict disparity vectors and motion vectors in enhancement views (EVs) by employing object registration and warping. This leads to high compression and low-complexity coding scheme for EVs. The proposed scheme provides higher coding efficiency when compared to the segmentation-free scheme, while achieving lower computational complexity.

关键词： base view segmentation low computational complexity multi-view video coding object warping

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low complexity IA Design for the Multi-Cell MIMO Downlink Cellular Network 96

Low Complexity IA Design for the Multi-Cell MIMO Downlink Ce...

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IEEE 96th Vehicular Technology Conference (VTC-Fall)

作者： Liu, Weihua Fan, Junchuan Zhang, Yuanyuan Yu, Zeqi Cui, Yong Zhengzhou Univ Light Ind Sch Comp & Commun Engn Zhengzhou 450002 Peoples R China

ISBN: (纸本)9781665454681

Interference alignment (IA) is a promising technology to effectively eliminate interference and improve the wireless communication network capacity. However, the low complexity IA solution with high degrees of freedom (DoF) for the multi-cell multi-user cellular network is still an open problem that needs to be solved. To address this problem, in this paper, the two-stage IA scheme for the multi-cell multi-user multiple-input multiple-output (MIMO) interfering broadcast channel (IFBC) model is investigated. Since a multi-cell IFBC is a complex interfering channel model, it is simplified into several simple models. The complex MIMO IFBC model can be first transformed into a simple K-user MIMO interference channel model, by designing the first stage precoding matrix to eliminate inter-cell interference (ICI). Based on the designed first stage precoding matrix, the MIMO IFBC becomes several single-cell MIMO IFBCs, and the second stage precoding matrix can be designed to eliminate inter-user interference (IUI). The high system sum-rate performance and low computational complexity of the proposed IA design scheme are verified through a series of simulations.

关键词： Interference alignment (IA) degrees of freedom (DoF) low computational complexity multiple-input multiple-output interfering broadcast channel (MIMO IFBC)

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Power Harmonics Measurements Based on Modified Newton-Raphson Procedure 18

Power Harmonics Measurements Based on Modified Newton-Raphso...

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18th IEEE International Conference on Smart Technologies (IEEE EUROCON)

作者： Petrovic, Predrag B. Rozgic, Dimitrije Univ Kragujevac Fac Tech Sci Cacak Serbia

ISBN: (纸本)9781538693018

The paper proposes new algorithm for power harmonics parameters measurement based on modified Newton-Raphson method. The main modification is achieved through reconfiguration of the Jacobian matrix, and direct calculation of its characteristic coefficients without need to obtain inversion. The zero-crossing method is used to compute the frequency roughly for initial frequency estimation. With additional digital filtering, the parameters can be initialized properly and the updating steps can be supervised for fast convergence of Newton-Raphson iterations. With this combined approach, both high accuracy and good tracking speed can be achieved. It significantly reduces the computation complexity and makes the programming easier as well. The proposed algorithm has the quadratic convergence. Reliability and effectiveness of the proposed method was confirmed through simulation tests and results.

关键词： power harmonics Newton-Raphson method zero-crossing low computational complexity simulation

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Dynamic Resource Allocation for Heterogeneous Services in Cognitive Radio Networks with Imperfect Channel Sensing

Dynamic Resource Allocation for Heterogeneous Services in Co...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Xie, Renchao Yu, F. Richard Ji, Hong Beijing Univ Posts & Telecommun Sch Informat & Commun Engn Ottawa ON Canada Carleton Univ Sch Informat Technol Dept Syst & Comp Engn Ottawa ON Canada Beijing Univ Posts & Telecommun Minist Educ Key Lab Univ Wireless Commun Beijing 100876 Peoples R China

ISBN: (纸本)9781424492688

In cognitive radio networks (CRNs), perfect knowledge of a dynamic radio environment is hard to know due to hardware limitation, short sensing time and network connectivity issues in CRNs. In this paper, we study the dynamic resource allocation problem for heterogeneous services in CRNs with imperfect channel sensing. We formulate the optimization problem as a mixed integer programming problem under constraints. Then we solve the optimal joint power and channel allocation problem using discrete stochastic optimization method. The proposed algorithm has low computation complexity and fast convergence to approximate to the optimal solution under imperfect channel sensing. Another advantage of this method is that it can track the changing radio environment to allocate the resources dynamically. Simulation results are presented to demonstrate the effectiveness of the proposed scheme.

关键词： Approximation algorithms Base stations Channel allocation Cognitive radio Heuristic algorithms Resource management Sensors channel allocation channel allocation problem cognitive radio cognitive radio networks computational complexity discrete stochastic optimization method dynamic radio environment dynamic resource allocation heterogeneous services imperfect channel sensing integer programming low computational complexity mixed integer programming problem network connectivity optimal joint power allocation problem optimization problem radio networks resource allocation stochastic programming

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Fast SVM classifier for large-scale classification problems

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INFORMATION SCIENCES 2023年 642卷

作者： Wang, Huajun Li, Genghui Wang, Zhenkun Changsha Univ Sci & Technol Dept Math & Stat Changsha Peoples R China Southern Univ Sci & Technol Sch Syst Design & Intelligent Mfg Shenzhen Peoples R China Southern Univ Sci & Technol Dept Comp Sci & Engn Shenzhen Peoples R China

Support vector machines (SVM), as one of effective and popular classification tools, have been widely applied in various fields. However, they may incur prohibitive computational costs when solving large-scale classification problems. To address this problem, we construct a new fast SVM with a truncated squared hinge loss (dubbed as L ��-SVM). We begin by developing an optimality theory of the nonconvex and nonsmooth L ��-SVM, which makes it convenient for us to investigate the support vectors and working set of L ��-SVM. Based on this, we propose a new and effective global convergence algorithm to address the L ��-SVM. This method is found to enjoy a tremendously low computational complexity, which makes sufficiently decreasing the demand for extremely large-scale computation possible. Numerical comparisons with eight other solvers show that our proposed algorithm achieves excellent performance on large-scale classification problems with regard to shorter computational times, more desirable accuracy levels, fewer support vectors and more robust to outliers.

关键词： Support vector machine Truncated squared hinge loss Support vectors Optimality theory Global convergence low computational complexity

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complexity-Reduced Super Resolution for Foveation-Based Driving Head Mounted Displays

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IEEE ACCESS 2021年 9卷 140042-140049页

作者： Nam, Hyoungsik Kang, Hangyeol Kyung Hee Univ Dept Informat Display Seoul 02447 South Korea

In this paper, we propose a foveation-based super resolution (SR) algorithm to create high resolution images from low resolution inputs for virtual reality head mounted displays. Because the proposed SR algorithm is integrated in the previous foveation-based driving technology to cover the small area around the foveation point that requires high rendering quality, the overall computational complexity is substantially reduced, compared to the whole area SR. The target display has 4 times as high resolution as the input image, therefore, the proposed SR algorithm generates 4 x as well as 2 x SR images at the same time. To support two SR output images, small area SR, and small number of weights, we employ cropping as well as progressive and recursive framework used in the previous MS-LapSRN. We reduce the number of neurons by placing the deconvolutional layer after convolutional layers, compared to the MS-LapSRN. PSNR and SSIM performances of the proposed SR for the 4 x scale are estimated as 31.152 dB and 0.935 for Set5, 26.656 dB and 0.858 for Set14, 27.138 dB and 0.830 for BSD100, and 25.078 dB and 0.836 for Urban100. For the target 8K display of 7;680 x 4 :320, the proposed FovSR-integrated driving technology achieves the substantial reductions by 76.7 % and 99.02 % on the number of lines from 7,680 to 1,788 and the number of neurons from 24,518,246,400 to 239,541,184, respectively.

关键词： Image resolution Neurons Head Training Rendering (computer graphics) computational complexity Licenses Super resolution low computational complexity virtual reality head mounted display foveation-based driving

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Probability-weighted tensor robust PCA with CP decomposition for hyperspectral image restoration

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SIGNAL PROCESSING 2023年 209卷

作者： Zhang, Aiyi Liu, Fulai Du, Ruiyan Northeastern Univ Sch Comp Sci & Engn Shenyang 110819 Liaoning Peoples R China Northeastern Univ Qinhuangdao Inst Engn Optimizat Smart Antenna Qinhuangdao 066004 Hebei Peoples R China

This paper presents a novel probability-weighted tensor robust principal component analysis (TRPCA) method based on CANDECOMP/PARAFAC decomposition (CPD) for hyperspectral image (HSI) restoration with low computational complexity from the coexistence of dense noise and sparse outliers. In the pro-posed method, via the CPD property, the tensor nuclear norm (TNN) optimization object is replaced as the CPD factor matrix of HSI with lower dimensions without losing low-rank property, so as to the com-putational complexity could be reduced during optimizing TNN in TRPCA model. To demonstrate the dif-ferent effects of noise and outliers on HSI restoration, two weighted sets are defined with probability by the prior knowledge of the occurrence of outliers, which are used to analyze the probability whether the HSI is corrupted by dense noise or outliers. Via the probability theory, information entropy is employed to measure the uncertainty of noise and outlier occurrence in received data, so that to demonstrate their difference impacts on HSI restoration to improve the recovery accuracy. Theoretical analysis and simula-tion results show that the proposed method has lower computational complexity and better restoration performance compared with other related methods. (c) 2023 Elsevier B.V. All rights reserved.

关键词： HSI restoration Robust principal component analysis CP decomposition low computational complexity Probability weighted

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Superposition Signal Input Decoding for Lattice Reduction-Aided MIMO Receivers

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IEICE TRANSACTIONS ON COMMUNICATIONS 2023年第2期E106B卷 184-192页

作者： Denno, Satoshi Kashihara, Koki Hou, Yafei Okayama Univ Grad Sch Nat Sci & Technol Okayama 7008530 Japan

This paper proposes a novel approach to low complexity soft input decoding for lattice reduction-aided MIMO receivers. The pro-posed approach feeds a soft input decoder with soft signals made from hard decision signals generated by using a lattice reduction-aided linear detec-tor. The soft signal is a weighted-sum of some candidate vectors that are near by the hard decision signal coming out from the lattice reduction-aided linear detector. This paper proposes a technique to adjust the weight adapt to the channel for the higher transmission performance. Furthermore, we propose to introduce a coefficient that is used for the weights in order to enhance the transmission performance. The transmission performance is evaluated in a 4 x 4 MIMO channel. When a linear MMSE filter or a serial interference canceller is used as the linear detector, the proposed technique achieves about 1.0 dB better transmission performance at the BER of 10-5 than the decoder fed with the hard decision signals. In addition, the low computational complexity of the proposed technique is quantitatively eval-uated.

关键词： soft decision weighted sum lattice reduction linear detectors low computational complexity

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Fast Sparse Bayesian Learning Method for Scanning Radar Super-Resolution Imaging

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IEEE ACCESS 2024年 12卷 166393-166401页

作者： Yu, Ze AVIC Chengdu Aircraft Design & Res Inst Chengdu 610073 Peoples R China

The high azimuth resolution and low computational complexity are significant for scanning radar super-resolution imaging. In this paper, we propose a fast sparse Bayesian learning method with truncated singular value (FSBL-T) to quickly improve the azimuth resolution. Firstly, we truncate the small singular value of the convolution matrix to rewrite the echo signal. Secondly, we introduce the Gaussian-Gamma distribution to model the echo noise and sparse target. Then, the expectation maximization method is utilized to estimate the imaging parameters. To reduce the computational load, we introduce Kailath Variant conversion to reduce the size of the inverse matrix. Finally, the simulations illustrate that the FSBL-T method can effectively enhance the azimuth resolution without reducing the imaging accuracy.

关键词： Radar imaging Azimuth Radar Imaging Bayes methods Sparse matrices Noise Superresolution Convolution computational complexity Scanning radar super-resolution imaging sparse Bayesian learning low computational complexity truncated singular value

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Fast Parameter Estimation for Polyphase P Codes Modulated Radar Signals

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2017年第10期E100A卷 2162-2166页

作者： Zhang, Qi Wang, Pei Zhu, Jun Tang, Bin Univ Elect Sci & Technol China West Hitech Zone Qingshuihe Campus 2006Xiyuan Ave Chengdu 611731 Sichuan Peoples R China

A fast parameter estimation method with a coarse estimation and a fine estimation for polyphase P coded signals is proposed. For a received signal with N sampling points, the proposed method has an improved performance when the signal-to-noise ratio (SNR) is larger than 2 dB and a lower computational complexity O (N log(s) N) compared with the latest time-frequency rate estimation method whose computational complexity is O (N-2).

关键词： radar signals polyphase P codes parameter estimation low computational complexity

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