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Orthogonal Polar V Transforms and application to shape retrieval

JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 2016年第Jan.期34卷 146-152页

作者： Chen, Wei Cai, Zhanchuan Jiangnan Univ Sch Digital Media Wuxi 214122 Peoples R China Macau Univ Sci & Technol Fac Informat Technol Taipa Peoples R China

The traditional orthogonal moments (e.g., Zernike moments) are formulated with polynomials as their basis that often face the problem of computation difficulty especially with the high-order moments. In this paper, we present a novel set of transforms namely the Polar V Transforms (PVTs). We can use the PVTs not only to generate the rotation-invariant features but also to capture global and local information of images. Since the PVTs basis functions can keep a low order of polynomials, we can significantly speed-up the runtime for computing the kernels. The experimental results have demonstrated that our proposed method outperforms the previous methods in runtimes and achieves very good results in shape retrieval compared to the previous methods especially when the images with high degree of perspective distortions. (C) 2015 Elsevier Inc. All rights reserved.

关键词： V-system Moments Orthogonal piecewise polynomial Rotation-invariant Multi-scale features low computational complexity Shape Perspective distortion

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A New SLM Scheme Based on Constellation Rotation for PAPR Reduction

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China Communications 2024年第11期21卷 267-277页

作者： Xie Yinghai Li Xianhuai Zhao Haibo Zhuhai Zhonghui Microelectronics CO. LTD.ZhuhaiGuangdong 519080China Willfar Information Technology CO. LTD.ChangshaHunan 410205China

A new selected mapping(SLM)scheme based on constellation rotation is proposed to reduce the peak-to-average power ratio(PAPR)of orthogonal frequency division multiplexing(OFDM)*** core idea is to generate abundant candidate signals by rotating different sub-signals of the original frequency signal with different *** new signal generation method can simplify the calculation process of candidate time signals into the linear addition of some intermediate signals,which are generated by the inverse fast Fourier transform(IFFT)operation of the original frequency *** feature can effectively reduce the computational complexity of candidate signal generation *** compared to the traditional SLM scheme,the number of complex multiplication and complex addition of new scheme can separately be decreased by about 99.99% and 91.7% with some specific ***,with the help of the constellation detection mechanism at the receiver,there is no need to carry any side information at the *** simulation results show that,with the same channel transmission performance,the PAPR reduction performance of new scheme can approach or even exceed the upper bound of the traditional SLM scheme,which uses all the vectors in Hadamard matrix as the phase sequences.

关键词： constellation rotation low computational complexity new selected mapping scheme peak-toaverage power ratio without side information transmission

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Enhanced pulse amplitude estimation for electronic warfare systems

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IET RADAR SONAR AND NAVIGATION 2019年第7期13卷 1123-1130页

作者： Lee, Yu-Ri Kim, Dong-Gyu Kim, Hyoung-Nam Pusan Natl Univ Dept Elect Engn Busan South Korea

In electronic warfare systems, the pulse amplitude (PA) of the received signals, which are emitted by enemies, has been used as one of the essential quantities for separating the mixed source signals. The PA is affected by time of arrival (TOA) and time of departure (TOD) estimation performance. Among methods of estimating TOA and TOD, there is a method of processing a signal in sample units in the time domain. This method has a disadvantage that it is completely affected by noise. This disadvantage can be overcome by using denoising techniques as in previous studies. However, conventional studies applying denoising are limited to the subject of signal detection, and there is no discussion on the problem of PA estimation due to the TOA and TOD estimation errors that occur after denoising. Therefore, we propose a power estimation-based PA estimation method using shrinked PW to be robust for TOA and TOD errors in sample units after wavelet packet denoising with high-order statistics. Simulation results show that the proposed PA estimation method has a smaller error at the same SNR when an unmodulated signal is received. Moreover, the proposed method can provide good performance even when a frequency modulated signal is received.

关键词： time-of-arrival estimation signal detection amplitude estimation image denoising signal denoising computational complexity blind source separation wavelet transforms electronic warfare enhanced pulse amplitude estimation electronic warfare systems received signals essential quantities mixed source signals pulse width PW arrival TOA TOD estimation performance sample units time domain low computational complexity denoising techniques EW systems signal detection TOD estimation errors power estimation-based PA estimation method wavelet packet denoising unmodulated signal frequency-modulated signal

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Deep Learning Driven Non-Orthogonal Precoding for Millimeter Wave Communications

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IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS 2020年第2期10卷 164-176页

作者： Liu, Junkai Chen, Jienan Luo, Siyu Li, Shuai Fu, Shengli Univ Elect Sci & Technol China Natl Key Lab Sci & Technol Commun Chengdu 611731 Peoples R China Univ North Texas Dept Elect Engn Denton TX 76201 USA

Hybrid beamforming (HB) based millimeter wave (mm-Wave) transmission is a promising technology for providing low latency and high data rate transmission. However, due to the high path loss, the performance of mmWave-based HB is significantly impacted by channel degradation, especially when the number of the available transmission path is less than the transmission streams. Driven by deep learning (DL) based beamforming, we propose a non-orthogonal precoding based HB scheme for the deterioration of channel transmission. Instead of directly applying the neural network as the beamforming function, we present the insight and theoretical analysis of the beamforming strategy in the DL based HB. By studying the beamforming behavior, we designed and formulated deep learning driven hybrid beamforming method. Compared with the existing DL-based hybrid beamforming, the neural network in the proposed method acts as a general neural codebook, which avoids network training even channel changed. In the overloaded channel condition, the proposed deep learning driven non-orthogonal precoding can solve the problem of channel degradation, which improves the robustness for hybrid beamforming. Simulation results show that the proposed method can achieve significant performance improvement over existing ones in overloaded transmission conditions. We also designed and implemented our scheme over the FPGA platform, which shows a much lower hardware cost than other existing schemes.

关键词： Array signal processing Radio frequency MIMO communication Neural networks Deep learning NOMA Training Hybrid beamforming MIMO systems overloaded transmission deep learning driven non-orthogonal precoding low computational complexity

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A low complexity Reconfigurable DCT Architecture to Trade off Image Quality for Power Consumption

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JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY 2008年第3期53卷 399-410页

作者： Park, Jongsun Roy, Kaushik Korea Univ Sch Elect Engn Seoul 136701 South Korea Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA

In this paper we present a low complexity discrete cosine transform (DCT) architecture based on computation re-use in vector-scalar product. 1-D DCT operation is expressed as additions of vector-scalar products and basic common computations are identified and shared to reduce computational complexity in 1-D DCT operation. Compared to general distributed arithmetic based DCT architecture, the proposed DCT shows 38% of area and 18% of power savings with little performance degradation. We also propose an efficient method to trade off image quality for computational complexity. The approach is based on the modification of DCT bases in bit-wise manner and different computational complexity/image quality trade-off levels are suggested. Finally, based on the above approaches, we propose a low complexity DCT architecture, which can dynamically reconfigure from one trade-off level to another. The reconfigurable DCT architecture can achieve power savings ranging from 28% to 56% for 3 different trade-off levels.

关键词： low power VLSI design Discrete cosine transform low computational complexity

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Adaptive Extremum Seeking Control Based LCL Filter Resonant Frequency Online Estimation

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IEEE TRANSACTIONS ON POWER ELECTRONICS 2022年第1期37卷 59-64页

作者： Wu, Yuheng Mahmud, Mohammad Hazzaz Moorthy, Radha Sree Krishna Chinthavali, Madhu Zhao, Yue Univ Arkansas Power Elect Syst Lab Arkansas Fayetteville AR 72701 USA Oak Ridge Natl Lab Elect Energy Syst Integrat Grp Knoxville TN 37932 USA

The LCL filter has been widely used in the grid-tied inverter systems. However, the resonance of the LCL filter can reduce the system stability margin and the control performance. Moreover, the grid impedance variations can lead to the drift of the resonant frequency, which can further worsen the system robustness. Thus, it is important to know the actual resonant frequency of the LCL filter. In this letter, an adaptive extremum seeking control (AESC) based estimation scheme is proposed to estimate the resonant frequency of the LCL filter online. By injecting a high-frequency (HF) signal into the inverter output voltage, the AESC scheme can identify the extremum of the LCL filter amplitude response, i.e., resonant peak. The amplitude of injection signal is adaptive based on the inverter HF response, which can address the tradeoff between the dynamic response and inverter output current quality. Most importantly, compare to other method, the proposed scheme has very low computational complexity, which minimizes the burden to the normal inverter controller operation. Stability analysis is given in this letter, and experimental studies are conducted to validate the effectiveness of the proposed scheme.

关键词： Resonant frequency Inverters Impedance low-pass filters Estimation Delays Frequency estimation Adaptive extremum seeking control (AESC) low computational complexity resonant frequency estimation

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Globality constrained adaptive graph regularized non-negative matrix factorization for data representation

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IET IMAGE PROCESSING 2022年第10期16卷 2577-2592页

作者： Sun, Yanfeng Wang, Jie Guo, Jipeng Hu, Yongli Yin, Baocai Beijing Univ Technol Beijing Key Lab Multimedia & Intelligent Software 100 Pingleyuan Beijing Peoples R China

Benefiting from the good physical interpretations and low computational complexity, non-negative matrix factorization (NMF) has attracted wide attentions in data representation learning tasks. Some graph-based NMF approaches make the learned representation encode the topological structure by the local graph Laplacian regularizer, which improves the discriminant ability of data representation. However, the performance of graph-based NMF methods depend heavily on the quality of the predefined graph and the complexity of models is high. Here, a globality constrained adaptive graph regularized non-negative matrix factorization for data representation (GCAG-NMF) model is proposed, which not only uses the self-representation characteristics of data to learn an adaptive graph to describe the sample relationship more accurately, but also proposes a graph factorization technique to reduce the complexity of the model and improve the discriminative ability of data representation. Then, an iterative optimizing strategy with low complexity and strict convergence guarantee is developed to optimize the objective function. Experimental results on some databases demonstrate the effectiveness of the proposed model.

关键词： discriminative ability graph factorization technique iterative optimizing strategy learned representation data representation model optimisation low computational complexity GCAG-NMF globality constrained adaptive graph regularized non-negative matrix factorization discriminant ability data representation learning tasks predefined graph data structures graph theory adaptive graph graph-based NMF methods matrix decomposition objective function iterative methods graph-based NMF approaches nonnegative matrix factorization local graph Laplacian regularizer

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Multipath Extraction Based UL/DL Channel Estimation for FDD Massive MIMO-OFDM Systems

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IEEE ACCESS 2021年 9卷 75349-75361页

作者： Ji, Wei Zhang, Feng Qiu, Ling Univ Sci & Technol China Chinese Acad Sci Sch Informat Sci & Technol Key Lab Wireless Opt Commun Hefei 230026 Peoples R China

In this paper, we propose a multipath extraction based uplink/downlink channel estimation scheme for wideband massive multiple-input multiple-output (MIMO) systems, where orthogonal frequency division multiplexing (OFDM) is adopted and the beam squint effect is considered. Firstly, we investigate the spatial- and frequency-wideband effects and obtain the relationship between angle-delay information and coordinates of on-grid paths. Secondly, according to the spatial- and frequency-wideband effects, we design a pilot pattern in uplink training to ensure that exact paths can be acquired from limited potential paths. Combined with pilot pattern design, a modified density-based spatial clustering of applications with noise (M-DBSCAN) approach is proposed to acquire the on-grid potential paths. Potential paths are used for initialization in uplink channel extraction. Due to the fact that coordinates of only a few potential paths are close to those of true paths, the uplink multipath extraction problem can be regarded as an off-grid sparse signal reconstruction problem. To deal with this issue, an off-grid sparsity adaptive matching pursuit (OSAMP) based compressive sensing method with low computational complexity is proposed. In OSAMP, angle-delay information as well as path gains of exact paths are accurately estimated, which are further used for accomplishing the uplink channel reconstruction. Angle-delay reciprocity between uplink and downlink channels is exploited, and downlink channel estimation is accomplished with the help of uplink multipath extraction. Downlink pilots are only used for downlink path gain estimation, therefore, the downlink training overhead will be significantly reduced. Simulation results are provided to demonstrate the effectiveness of our proposed low computational complexity channel estimation method.

关键词： Massive MIMO wideband channel estimation beam squint low computational complexity angle-delay reciprocity

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Mobile beacon control algorithm that ensures observability in single range navigation

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IFAC-PapersOnLine 2016年第23期49卷 48-53页

作者： Mandi, Filip Mikovi, Nikola Palomeras, Narcís Carreras, Marc Vallicrosa, Guillem University of Zagreb Faculty of Electrical Engineering and Computing LABUST - Laboratory for Underwater Systems and Technologies Unska 3 Zagreb Croatia Computer Vision and Robotics Institute Universitat de Girona Parc Cientfic i Tecnolgic UdG Girona17003 Spain

Mobile beacon vehicles are used as navigational aid for autonomous underwater vehicles when performing navigation using single range measurements. They remove the constraints imposed on the underwater vehicle trajectory by executing trajectory that provides persistent range measurements. In this paper, control algorithm for beacon vehicle which ensures observability of the underwater vehicle's navigation filter is presented. It is characterized by small communication overhead, low computational complexity and it is deployable on both fully actuated and underactuated vehicles. The algorithm was tested in real-life environment and the acquired experimental results show that despite the presence of uncertainties and communication delays, the algorithm accomplishes its task. © 2016

关键词： Marine navigation Autonomous underwater vehicles Kalman filters Navigation Observability Autonomous Vehicles Communication delays Communication overheads low computational complexity Marine systems Navigation filters Underactuated vehicles Underwater vehicles

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Signed Orthogonal Regressor Algorithm for Digital Predistortion of Power Amplifiers

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IEEE MICROWAVE AND WIRELESS COMPONENTS LETTERS 2021年第7期31卷 869-872页

作者： Li, Hongmin Qiao, Wen Liu, Qiao Li, Gang Zhang, Yikang Wang, Guangjian Liu, Falin Univ Sci & Technol China Dept Elect Engn & Informat Sci Hefei 230027 Peoples R China Huawei Technol Co Ltd Wireless Technol Lab Chengdu 611731 Peoples R China

Digital predistortion (DPD) of broadband power amplifiers (PAs) requires a large number of parameters to compensate for the severe nonlinear distortion, which may cause considerable computational complexity in the DPD parameter identification process. To solve this problem, we proposed a novel signed orthogonal regressor algorithm (SORA) to simplify the identification of DPD parameters. Based on the signed regressor algorithm and principal component analysis (PCA), the proposed algorithm can eliminate most of the multiplication operations in the identification process and greatly reduce the computational complexity. Furthermore, the proposed SORA is modified to be able to estimate each parameter independently. Experimental results show that compared with the conventional PCA-based method, the proposed two methods can realize comparable linearization performance with significantly lower computational complexity.

关键词： Principal component analysis Covariance matrices Wireless communication Mathematical model Microwave theory and techniques Correlation computational complexity Digital predistortion (DPD) low computational complexity power amplifier (PA) principal component analysis (PCA) signed orthogonal regressor algorithm (SORA)

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