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Kernel Adaptive Filtering with Weibull M-transform Maximum Versoria Criterion

Kernel Adaptive Filtering with Weibull M-transform Maximum V...

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IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Chenchong Bi Yingsong Li Liping Li Nikola Zlatanov Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China Faculty of Computer and Engineering Sciences Innopolis University Innopolis Russia

ISBN: (数字)9798350384437

ISBN: (纸本)9798350384444

A kernel Weibull M-transform maximum-versoria-criterion (KWMMVC) algorithm is constructed, which is to use for nonlinear system identification. The KWMMVC algorithm ingeniously integrates the Weibull M-transform scheme into the maximum-versoria-criterion to formulate a novel cost function. The ability of KWMMVC algorithm to identify nonlinear channels under various impulse noise environments is tested in the kernel adaptive filters, and the results proved its superior performance.

关键词： Adaptive systems Noise Adaptive filters Filtering algorithms Information filters Cost function Information and communication technology

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A Novel Transformed Nested Array with Enhanced DOFs Based on Sum-Difference Coarray

A Novel Transformed Nested Array with Enhanced DOFs Based on...

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IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Wei Xin Yingsong Li Harbin Engineering University China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

Sum-difference driven coarray (SDCA) was paid great attention in array-signal-processing (ASP). By considering SDCA, the degrees of freedom (DOFs) for sparse arrays can be further improved. Here, a new transformed nested-array (TNA) is constructed, which reduces the element redundancy via rearranging the density of sub-arrays of the constructed new TNA. Compared to former TNAs, the constructed TNA gets higher DOFs and maximization signals, numerical simulation are given for getting its superior behaviors.

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Edge-Preserving Multi-Exposure Fusion with Guided Filtering for Structural Patch Decomposition 6

Edge-Preserving Multi-Exposure Fusion with Guided Filtering ...

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6th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2023

作者： Zhen, Yang Qi, Junwei Li, Yingsong College of Information and Communication Engineering Harbin Engineering University Harbin150001 China Ministry of Education Anhui University Key Laboratory of Intelligent Computing and Signal Processing Hefei China College of Computer Science and Technology Harbin Engineering University Harbin150001 China

ISBN: (纸本)9798350399059

Multi-exposure image fusion (MEF) is one of the effective ways to obtain high dynamic range (HDR) images. Multi-scale structural patch decomposition based MEF(MSPD) and edge-preserving structural patch decomposition (MESPD) have achieved state-of-the-art fusion quality. MESPD incorporates edge-preserving factors into MSPD to preserve details in a single-scale setting. However, we find that the edge-preserving factors put too much emphasis on the edge, resulting in artifacts on some edges and loss of details. To tackle this issue, guided filter is introduced into MSPD, which is directly used as an edge-preserving filter instead of mean filter to implicitly decompose images. In addition, we have designed a flexible adaptive weight, which can further maintain details of the light and dark areas. Likewise, we inherit MESPD and MSPD to extend our method to multi-scale framework. Extensive experimental results demonstrate our method can produce satisfactory results in both static and dynamic scenes with fewer artifacts and low computational cost. © 2023 IEEE.

关键词： Image fusion

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Inductive Network Representation based on Neighbor Aggregation 3

Inductive Network Representation based on Neighbor Aggregati...

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2022 3rd International Conference on Computer Information and Big Data Applications, CIBDA 2022

作者： Xie, Jingsheng Chen, Xi Zhang, Yanping Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Anhui Hefei China School of Computer Science and Technology Anhui University HefeiAH551 China

ISBN: (纸本)9783800758760

Network representation learning is to learn low dimensional vectors for nodes. It plays a critical role in network analysis. However, most existing network embedding methods focus on embedding the nodes that already exist in the network, and cannot be generalized to newly-added nodes without retraining the learning model. To deal with this problem, the most common idea is to directly aggregate neighbor embeddings as the representation of new nodes, but this may lead to ignoring the particularity of node neighbors themselves. To fill this gap, we present INRL-NA, an innovative method of Inductive Network Representation Learning based on Neighbor Aggregation, which uses the hierarchical information to selectively aggregate neighbor node embeddings, preserving both the structural information and feature information of network. First we build a hierarchical network, then train a refinement model on the hierarchical network, finally after a new node joins the network, we use the hierarchical information and feature information to selectively aggregate neighbor embeddings. The experimental results show that compared with direct aggregation of all neighbor representations, INRLNA has higher representation quality. © VDE VERLAG GMBH - Berlin - Offenbach.

关键词： Aggregates

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A Method to Verify Internal Parameters of Camera Calibration in World Coordinate System 6

A Method to Verify Internal Parameters of Camera Calibration...

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6th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2023

作者： Xing, Zheng Wang, Qingchun Li, Yingsong Qi, Junwei College of Information and Communication Engineering Harbin Engineering University Harbin150001 China Shanghai Yanding Information Technology Co. Ltd. Shanghai201210 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (纸本)9798350399059

Aiming at the problem that reprojection error (RE) cannot reflect the camera calibration accuracy intuitively, this paper proposes a method to verify the camera calibration results in world coordinate system. Firstly, the checkerboard calibration target is photographed with the camera under test, and the internal parameters and distortion parameters of the camera are calculated by using the pinhole model and the Kannala-Brandt (KB) fisheye model, respectively. Then, the same camera is used to shoot two targets in the field of view (FOV), and the pixel coordinates of the two target points are detected from the image. Thirdly, the inverse projection model is used to calculate the distance between the two objects and the angle between the camera and the two objects, and the real distance and angle are compared. The experimental results show that the average distance errors of the pinhole model and the KB fisheye model are 0.34% and 0.35%, respectively, and the angle errors are 0.40% and 0.12%, respectively, which proves that the verification method can effectively characterize the calibration accuracy of the camera. © 2023 IEEE.

关键词： Calibration

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A miniaturized double-sided UWB-MIMO antenna with four-notched band

A miniaturized double-sided UWB-MIMO antenna with four-notch...

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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Qitao Chen Yufa Sun Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University HeFei China

A $\boldsymbol{40}\times\boldsymbol{40}\times \boldsymbol{1.6}\mathbf{mm}^{3}$ ultra-wideband MIMO antenna is proposed in this paper. The antenna realizes four-notched band characteristics by embedding different types of slits in the radiating element. The antenna has good UWB performance, with four-band rejection to avoid interference caused by four narrow frequency bands WiMAX(3.3-3.8GHz), WLAN(S.1-S.8GHz), INSAT(6.7-7.3GHz) and ITV 8GHz (8.13-8.38GHz). It achieves better than - 15dB of isolation, and impedance bandwidth from 3.06-15.5GHz.

关键词： Antenna measurements Bandwidth Interference Size measurement Ultra wideband antennas Impedance Antennas

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SES: Bridging the Gap Between Explainability and Prediction of Graph Neural Networks

SES: Bridging the Gap Between Explainability and Prediction ...

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International Conference on Data Engineering

作者： Zhenhua Huang Kunhao Li Shaojie Wang Zhaohong Jia Wentao Zhu Sharad Mehrotra Anhui University Hefei China Key Lab of Intelligent Computing and Signal Processing of Ministry of Education Hefei China Amazon Research Seattle USA University of California Irvine Irvine USA

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

Despite the Graph Neural Networks' (GNNs) pro-ficiency in analyzing graph data, achieving high-accuracy and interpretable predictions remains challenging. Existing GNN interpreters typically provide post-hoc explanations disjointed from GNNs' predictions, resulting in misrepresentations. Self-explainable GNNs offer built-in explanations during the training process. However, they cannot exploit the explanatory outcomes to augment prediction performance, and they fail to provide high-quality explanations of node features and require additional processes to generate explainable subgraphs, which is costly. To address the aforementioned limitations, we propose a self-explained and self-supervised graph neural network (SES) to bridge the gap between explainability and prediction. SES comprises two processes: explainable training and enhanced predictive learning. During explainable training, SES employs a global mask generator co-trained with a graph encoder and directly produces crucial structure and feature masks, reducing time consumption and providing node feature and subgraph explanations. In the enhanced predictive learning phase, mask-based positive-negative pairs are constructed utilizing the ex-planations to compute a triplet loss and enhance the node representations by contrastive learning. Extensive experiments demonstrate the superiority of SES on multiple datasets and tasks. SES outperforms baselines on real-world node classification datasets by notable margins of up to 2.59% and achieves state-of-the-art (SOTA) performance in explanation tasks on synthetic datasets with improvements of up to 3.0%. Moreover, SES delivers more coherent explanations on real-world datasets, has a fourfold increase in Fidelity+ score for explanation quality, and demonstrates faster training and expla-nation generating times. To our knowledge, SES is a pioneering GNN to achieve SOTA performance on both explanation and prediction tasks.

关键词： Training Bridges Accuracy Reliability engineering Data engineering Graph neural networks Generators

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Optimization Strategies for Hydrogen Mixing Scheduling in Natural Gas Networks in Integrated Energy Systems

Optimization Strategies for Hydrogen Mixing Scheduling in Na...

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IEEE International Conference on Power and Power and Renewable Energy (ICPRE)

作者： Zixun Zhang Xiaohan Fang Yuan Fan Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electrical Engineering and Automation Anhui University Hefei China

Developing a clean and efficient Integrated Energy System (IES) is critical to optimizing the use of renewable energy sources and harnessing new forms of energy to achieve the country’s 2030 carbon peak and 2060 carbon neutrality targets. Existing natural gas pipelines in China facilitate the transport of hydrogen blended into the natural gas network and offer the possibility of storing hydrogen blended into natural gas pipelines. This paper proposes an optimal integrated energy dispatch strategy based on electricity-gas-hydrogen-heat-cooling demand, taking into account carbon emissions and economic efficiency, where renewable energy is no longer connected to the grid or stored in batteries, but converted to hydrogen mixed into the natural gas grid for transport and storage, with the economic objective of minimizing the total IES operating cost, the wind and light abandonment cost and the carbon emission cost. The CPLEX solver is used to solve the problem, and the feasibility of the proposed model is verified by simulation results, which promotes the consumption of renewable and clean energy.

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Enhanced Target Localization based on Double RIS

Enhanced Target Localization based on Double RIS

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International Symposium on Wireless Communication Systems (ISWCS)

作者： Lei He Liping Li Yingsong Li Paulo S. R. Diniz Run Ying The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei The Universidade Federal do Rio de Janeiro Rio de Janeiro

ISBN: (数字)9798350362510

ISBN: (纸本)9798350362527

Reconfigurable intelligent Surface (RIS) has become an enabling technology for economically and efficiently realizing intelligent and reconfigurable wireless communication environments. Previous positioning research based on RIS has mainly focused on single RIS without considering the improvement in positioning accuracy brought by double RIS, thus failing to reveal the full potential of a double RIS-assisted wireless communication system. This paper investigates a target positioning system assisted by double RIS, where double RIS is used to enhance communication between users and the receiver. Firstly, the reception signal model based on the collab.rative effect of double RIS is constructed, and then we formulate the target positioning problem based on this model, aiming to obtain the optimal target signal while minimizing system noise. Moreover, to verify the effectiveness of the localization system with double RIS assistance, we also configured a scenario of a single RIS localization system for comparative analysis. Simulation results indicate that the proposed target positioning method based on double RIS exhibits certain superiority in improving system positioning performance compared to single RIS.

关键词： Location awareness Wireless communication Accuracy Simulation Noise Estimation Collab.ration

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Linear Precoding for Faster-Than-Nyquist signaling with Imperfect Channel State Information

Linear Precoding for Faster-Than-Nyquist Signaling with Impe...

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International Conference on Wireless Communications and signal processing (WCSP)

作者： Yan Wang Qiang Li Yingsong Li Liping Li Xingwang Li Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China School of Physics and Electronic Information Engineering Henan Polytechnic University China

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

In faster-than-Nyquist (FTN) transmission over frequency-selective fading channels, it is essential to eliminate both FTN-induced intersymbol-interference (ISI) (FTN-ISI) and channel-induced ISI (channel-ISI). Although frequency domain equalization (FDE) techniques can mitigate channel-ISI at the receiver, their performance is often inadequate. In contrast, cyclic prefix/suffix (CPS)-G-to-minus-half (GTMH) precoding shows superior effectiveness in mitigating channel-ISI. However, existing CPS-GTMH precoding techniques assume the transmitter obtains perfect channel state information (CSI) estimated at the receiver. This is impractical due to the high latency in satellite communication links. Therefore, this paper explores precoding for FTN signaling under imperfect CSI (ICSI) and proposes CPS-minimum mean squared error (MMSE) and linear pre-equalization (LPE)-MMSE precoding schemes based on the MMSE criterion. Both schemes employ a cyclic prefix to transform the channel-ISI matrix into the circular matrix, thereby avoiding inter-block interference. The primary distinction is that CPS-MMSE precoding handles FTN-ISI and channel-ISI together using MMSE precoding. In contrast, LPE-MMSE precoding addresses FTN-ISI with LPE and channel-ISI with MMSE precoding separately. Simulation results indicate that CPS-MMSE and LPE-MMSE precodings outperform CPS-FDE and LPE-FDE in mitigating channel-ISI when the estimation error is 0.005 and 0.01. For instance, with a packing ratio of 0.9, a roll-off factor of 0.25, and an estimation error of 0.01, CPS-MMSE and LPE-MMSE precodings achieve bit error rate (BER) gains of approximately 0.8 dB and 1 dB at a BER of 1e4, respectively. However, when the estimation error increases to 0.1, the BER performance of CPS-FDE and LPE-FDE surpasses that of the CPS-MMSE and LPE-MMSE precodings, indicating the proposed precoding schemes' unsuitability for larger channel estimation errors.

关键词： Estimation error Precoding Simulation Bit error rate Channel estimation Interference Receivers Matrix converters Satellite communications Channel state information

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