Signal Processing最新文献_第2页

RIS-assisted differential transmitted spatial modulation design

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-22 DOI: 10.1016/j.sigpro.2024.109767

Chaorong Zhang, Yuyan Liu, Benjamin K. Ng, Chan-Tong Lam

{"title":"RIS-assisted differential transmitted spatial modulation design","authors":"Chaorong Zhang, Yuyan Liu, Benjamin K. Ng, Chan-Tong Lam","doi":"10.1016/j.sigpro.2024.109767","DOIUrl":"10.1016/j.sigpro.2024.109767","url":null,"abstract":"<div><div>In this paper, we propose a novel reconfigurable intelligent surface (RIS)-assisted wireless communication design called the RIS-assisted differential transmitted spatial modulation (DTSM) scheme. The encoding process of the differential spatial modulation (DSM) is integrated into the DTSM scheme, where only one transmit antenna is activated per time slot to transmit the <span><math><mi>M</mi></math></span>-ary phase shift keying (PSK) modulation symbol through the RIS. Due to the detection characteristics of DSM, the bit error rate (BER) performance remains satisfactory without requiring channel state information estimation, thereby enhancing robustness. The RIS application in the proposed scheme mitigates the effects of shadow area fading by adjusting the phase of the reflected signals to improve the signal-to-noise ratio at the receiver. In simulation results by comparing to other RIS-assisted spatial modulation schemes, we can find that the proposed DTSM scheme demonstrates good BER performance across various scenarios, including Nakagami-<span><math><mi>m</mi></math></span> fading, which also indicates its potential for practical applications.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109767"},"PeriodicalIF":3.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mitigating impulsive noise in airborne PLC: Introducing the S-SAMP-PV algorithm for MIMO OFDM systems

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-22 DOI: 10.1016/j.sigpro.2024.109798

Ruowen Yan, Qiao Li, Huagang Xiong

{"title":"Mitigating impulsive noise in airborne PLC: Introducing the S-SAMP-PV algorithm for MIMO OFDM systems","authors":"Ruowen Yan, Qiao Li, Huagang Xiong","doi":"10.1016/j.sigpro.2024.109798","DOIUrl":"10.1016/j.sigpro.2024.109798","url":null,"abstract":"<div><div>Power Line Communication (PLC) offers an efficient solution for data transmission over electrical power lines, presenting a promising avenue for in-flight communication in More Electrical Aircraft (MEA). A significant challenge in airborne PLC is Impulsive Noise (IN), which hampers transmission reliability. Existing noise mitigation methods, while valuable, face limitations in airborne settings due to computational intensiveness and sub-optimal sparse recovery performance. This paper introduces the Structured Sparsity Adaptive Matching Pursuit with Preliminary partial support estimation and Variable step-size (S-SAMP-PV) algorithm, devised for Multiple-Input-Multiple-Output (MIMO) systems. It uniquely pre-estimates partial support of sparse IN signals, enabling adaptive convergence without prior sparsity knowledge. This methodology substantially reduces computational demands, satisfying stringent real-time requirements of airborne applications. In simulation, the S-SAMP-PV algorithm exhibits marked advantages over traditional algorithms such as Orthogonal Matching Pursuit (OMP). Specifically, it realizes an approximate 81.3<span><math><mtext>%</mtext></math></span> reduction in Normalized Mean Square Error (NMSE) and demonstrates around 37<span><math><mtext>%</mtext></math></span> improvement in computational efficiency relative to OMP. Moreover, its Bit Error Rate (BER) performance at high Signal to Noise Ratio (SNR) approaches the ideal scenario where IN is assumed to be perfectly eliminated. These results emphasize the promise of S-SAMP-PV in elevating the performance of airborne PLC systems by efficient IN mitigation.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109798"},"PeriodicalIF":3.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142756675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Tensor singular value decomposition and low-rank representation for hyperspectral image unmixing

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-22 DOI: 10.1016/j.sigpro.2024.109799

Zi-Yue Zhu , Ting-Zhu Huang , Jie Huang , Ling Wu

{"title":"Tensor singular value decomposition and low-rank representation for hyperspectral image unmixing","authors":"Zi-Yue Zhu , Ting-Zhu Huang , Jie Huang , Ling Wu","doi":"10.1016/j.sigpro.2024.109799","DOIUrl":"10.1016/j.sigpro.2024.109799","url":null,"abstract":"<div><div>Hyperspectral unmixing (HU) finds pure spectra (endmembers) and their proportions (abundances) in hyperspectral images (HSIs). The matrix–vector non-negative tensor factorization (MV-NTF) describes the HSI as the sum of the outer products of the endmembers and their corresponding abundance maps. Concatenating these abundance maps in the third dimension is precisely the abundance tensor. Many subsequent studies have focused on exploiting different priors to improve the accuracy of MV-NTF. Most of them, however, explore the properties of abundance matrices or abundance maps, which is hard to fully utilize the structural similarity in abundance tensors corresponding to HSIs containing mixed materials. In this paper, we use the tensor singular value decomposition (T-SVD) to directly exploit the structural information in the abundance tensor. For this purpose, we propose a new low-rank representation by dividing the abundance tensor into a main feature tensor and a disturbance term. We characterize the low-rank property of the feature tensor after performing T-SVD and characterize the sparsity of the disturbance term. In this vein, we establish a model named abundance low-rank structure based on T-SVD (ALRSTD) and propose the solution algorithm. Experiments show that ALRSTD has better unmixing effect compared with several state-of-the-art methods, especially in the abundance estimation and the computation speed.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109799"},"PeriodicalIF":3.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Proximal gradient algorithm with dual momentum for robust compressive sensing MRI

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-22 DOI: 10.1016/j.sigpro.2024.109817

Zhonghua Xie , Lingjun Liu , Zehong Chen , Cheng Wang

{"title":"Proximal gradient algorithm with dual momentum for robust compressive sensing MRI","authors":"Zhonghua Xie , Lingjun Liu , Zehong Chen , Cheng Wang","doi":"10.1016/j.sigpro.2024.109817","DOIUrl":"10.1016/j.sigpro.2024.109817","url":null,"abstract":"<div><div>Adopting the new signal acquisition technology Compressive Sensing (CS) to Magnetic Resonance Imaging (MRI) reconstruction has been proved to be an effective scheme for reconstruction of high-resolution images with only a small fraction of data, thus making it the key to design a reconstruction algorithm with excellent performance. To achieve accelerated and robust CS-MRI reconstruction, a novel combination of Proximal Gradient (PG) and two types of momentum is developed. Firstly, to accelerate convergence of the PG iteration, we introduce the classical momentum method to solve the data-fitting subproblem for fast gradient search. Secondly, inspired by accelerated gradient strategies for convex optimizations, we further modify the obtained PG algorithm with the Nesterov's momentum technique to solve the prior subproblem, boosting its performance. We demonstrate the effectiveness and flexibility of the proposed method by combining it with two categories of prior models including a weighted nuclear norm regularization and a deep CNN (Convolutional Neural Network) prior model. As such, we obtain a dual momentum-based PG method, which can be equipped with any denoising engine. It is shown that the momentum-based PG method is closely related to the well-known Approximate Message Passing (AMP) algorithm. Experiments validate the effectiveness of leveraging dual momentum to accelerate the algorithm and demonstrate the superior performance of the proposed method both quantitatively and visually as compared with the existing methods.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109817"},"PeriodicalIF":3.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142758832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

PIPO-Net: A Penalty-based Independent Parameters Optimization deep unfolding Network PIPO-Net：基于惩罚的独立参数优化深度展开网络

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-22 DOI: 10.1016/j.sigpro.2024.109796

Xiumei Li , Zhijie Zhang , Huang Bai , Ljubiša Stanković , Junpeng Hao , Junmei Sun

{"title":"PIPO-Net: A Penalty-based Independent Parameters Optimization deep unfolding Network","authors":"Xiumei Li , Zhijie Zhang , Huang Bai , Ljubiša Stanković , Junpeng Hao , Junmei Sun","doi":"10.1016/j.sigpro.2024.109796","DOIUrl":"10.1016/j.sigpro.2024.109796","url":null,"abstract":"<div><div>Compressive sensing (CS) has been widely applied in signal and image processing fields. Traditional CS reconstruction algorithms have a complete theoretical foundation but suffer from the high computational complexity, while fashionable deep network-based methods can achieve high-accuracy reconstruction of CS but are short of interpretability. These facts motivate us to develop a deep unfolding network named the penalty-based independent parameters optimization network (PIPO-Net) to combine the merits of the above mentioned two kinds of CS methods. Each module of PIPO-Net can be viewed separately as an optimization problem with respective penalty function. The main characteristic of PIPO-Net is that, in each round of training, the learnable parameters in one module are updated independently from those of other modules. This makes the network more flexible to find the optimal solutions of the corresponding problems. Moreover, the mean-subtraction sampling and the high-frequency complementary blocks are developed to improve the performance of PIPO-Net. Experiments on reconstructing CS images demonstrate the effectiveness of the proposed PIPO-Net.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"229 ","pages":"Article 109796"},"PeriodicalIF":3.4,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An interference power allocation method against multi-objective radars based on optimized proximal policy optimization 基于优化近端策略的多目标雷达干扰功率分配方法

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-21 DOI: 10.1016/j.sigpro.2024.109785

Wenxu Zhang , Yajie Wang , Xiuming Zhou , Zhongkai Zhao , Feiran Liu

{"title":"An interference power allocation method against multi-objective radars based on optimized proximal policy optimization","authors":"Wenxu Zhang , Yajie Wang , Xiuming Zhou , Zhongkai Zhao , Feiran Liu","doi":"10.1016/j.sigpro.2024.109785","DOIUrl":"10.1016/j.sigpro.2024.109785","url":null,"abstract":"<div><div>Aiming at the problem of interference resource scheduling in cognitive electronic warfare, a multi-objective interference power allocation method based on the proximal policy optimization (PPO) framework is proposed in this paper. Firstly, the confrontation between jammers and multi-objective radar networks is mapped as the interaction between the agent and the environment, and the radar target detection model under suppression interference is established. On this basis, an interference power allocation model against multi-objective radars based on PPO framework is constructed. Moreover, a reward normalization mechanism is introduced to optimize the reward setting, and an interference power allocation method based on optimized PPO is proposed. Meanwhile, this paper constructs a confrontation scenario in which the jammer covers the target aircraft to break through the multi-objective radar network. Simulation experiments are conducted based on this scenario to verify the effectiveness of the method proposed in this paper. The interference power allocation method proposed in this paper can intelligently adjust the power allocation scheme of the jammer according to the electromagnetic situation on the battlefield, optimize the resource utilization of the jammer, and occupy the initiative on the battlefield.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109785"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142697674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Sparse Bayesian Learning with Jeffreys’ Noninformative Prior for Off-Grid DOA Estimation

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-21 DOI: 10.1016/j.sigpro.2024.109809

Mahmood Karimi, Mohammadreza Zare, Mostafa Derakhtian

{"title":"Sparse Bayesian Learning with Jeffreys’ Noninformative Prior for Off-Grid DOA Estimation","authors":"Mahmood Karimi, Mohammadreza Zare, Mostafa Derakhtian","doi":"10.1016/j.sigpro.2024.109809","DOIUrl":"10.1016/j.sigpro.2024.109809","url":null,"abstract":"<div><div>Sparse Bayesian learning (SBL) algorithms are attractive methods for direction-of-arrival (DOA) estimation and have certain advantages over other sparse representation-based DOA estimation methods. In this paper, a new computationally efficient SBL algorithm for DOA estimation is developed which considers a noninformative prior for hyperparameters. This noninformative prior is obtained using the well-known Jeffreys’ rule which is based on the Fisher information and the hyperparameters are powers of the source signals. The Jeffreys’ prior that is obtained for the hyperparameters is different from the conventional Jeffreys’ prior used in the literature. Moreover, a method for refining the DOA estimates obtained by the SBL algorithm is derived to reduce the off-grid error. Analysis indicates that the computational complexity of the proposed SBL algorithm per iteration is less than that of other existing SBL algorithms. Simulation results exhibit the superior performance of the proposed SBL algorithm compared to state-of-the-art SBL algorithms in terms of DOA estimation accuracy and total computational complexity. Moreover, simulations reveal that, unlike certain other state-of-the-art SBL algorithms, the proposed algorithm is robust to changes in noise power.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109809"},"PeriodicalIF":3.4,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142744532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Codesign of transmit waveform and reflective beamforming for active reconfigurable intelligent surface-aided MIMO ISAC system 为主动可重构智能表面辅助多输入多输出 ISAC 系统设计发射波形和反射波束成形

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-20 DOI: 10.1016/j.sigpro.2024.109795

Hongtao Li, Xu He, Shengyao Chen, Qi Feng, Sirui Tian, Feng Xi

{"title":"Codesign of transmit waveform and reflective beamforming for active reconfigurable intelligent surface-aided MIMO ISAC system","authors":"Hongtao Li, Xu He, Shengyao Chen, Qi Feng, Sirui Tian, Feng Xi","doi":"10.1016/j.sigpro.2024.109795","DOIUrl":"10.1016/j.sigpro.2024.109795","url":null,"abstract":"<div><div>This article discusses the active reconfigurable intelligent surface (ARIS)-aided integrated sensing and communication (ISAC) system for non-line-of-sight (NLoS) target sensing in cluttered environments while performing multi-user communication. To optimize sensing and communication performance simultaneously, we jointly design the shared transmit waveform, ARIS reflection coefficients and radar receive filter by using the multi-user interference and the reciprocal of radar output signal-to-interference-plus-noise ratio as metrics. Limited by practical requirements, the transmit waveform suffers from constant modulus or total energy constraints and the ARIS is subject to both maximum power and amplification gain constraints. Based on these considerations, the proposed codesign is formulated into a nonconvex constrained fractional function minimization problem. To tackle it effectively, we first translate the fractional objective into an integral form by employing Dinkelbach transform and then propose an alternating optimization-based algorithm, where the transmit waveform and ARIS reflection coefficients are respectively optimized by the customized algorithms based on the consensus alternating direction method of multipliers, and the receive filter has a closed-form optimal solution. Numerical results demonstrate that the ARIS-aided ISAC concurrently achieve superior NLoS sensing and communication performance to passive reconfigurable intelligent surface-aided and traditional ISACs in cluttered environments, regardless of waveform constraints and sensing-communication trade-off factor.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109795"},"PeriodicalIF":3.4,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142697675","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive three-dimensional histogram modification for JPEG reversible data hiding 用于 JPEG 可逆数据隐藏的自适应三维直方图修改

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-19 DOI: 10.1016/j.sigpro.2024.109786

Fengyong Li , Qiankuan Wang , Xinpeng Zhang , Chuan Qin

{"title":"Adaptive three-dimensional histogram modification for JPEG reversible data hiding","authors":"Fengyong Li , Qiankuan Wang , Xinpeng Zhang , Chuan Qin","doi":"10.1016/j.sigpro.2024.109786","DOIUrl":"10.1016/j.sigpro.2024.109786","url":null,"abstract":"<div><div>JPEG reversible data hiding (RDH) is a data hiding technique that requires both accurate data extraction and perfect recovery of the original JPEG image. Existing JPEG RDH schemes often rely on the distortion model of DCT coefficient frequency itself, failing to fully utilize the correlation between adjacent coefficients, resulting in inferior visual quality and significant file size expansion for JPEG image containing hidden data. To address the problem, we design a new JPEG RDH scheme by introducing three-dimensional (3D) histogram modification mechanism. We firstly evaluate the costs of each DCT block and frequency band to build coefficient triplet grouping mechanism. Furthermore, we construct a series of three-dimensional histogram mappings to perform data embedding according to the grouped DCT coefficient triplets, and then optimize the embedding efficiency by adaptively integrating multi-dimensional histogram mapping for the given embedding capacity. Extensive experiments demonstrate that our scheme significantly outperforms the state-of-the-art JPEG RDH schemes and can achieve efficient balance between higher visual quality and smaller file size changes while keeping JPEG file format unchanged.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"229 ","pages":"Article 109786"},"PeriodicalIF":3.4,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142706979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A fast-converging Bayesian tensor inference method for wireless channel estimation 用于无线信道估计的快速融合贝叶斯张量推理方法

IF 3.4 2区工程技术

Signal Processing Pub Date : 2024-11-19 DOI: 10.1016/j.sigpro.2024.109770

Yuzhe Sun, Wei Wang, Yuanfeng He, Yufan Wang

{"title":"A fast-converging Bayesian tensor inference method for wireless channel estimation","authors":"Yuzhe Sun, Wei Wang, Yuanfeng He, Yufan Wang","doi":"10.1016/j.sigpro.2024.109770","DOIUrl":"10.1016/j.sigpro.2024.109770","url":null,"abstract":"<div><div>In variational inference-based tensor channel estimation, high order singular value decomposition (HOSVD) initialization effectively captures the latent features of factor matrices, and accelerates convergence speed. However, HOSVD-based initialization further exacerbates the overfitting issue of the tensor variation Bayesian (TVB) method on each factor matrix element, leading to inaccurate rank estimation, and then significantly degrading channel parameter estimation performance. To prevent overfitting, we propose a new TVB method based on array spatial prior (ASP), which incorporates space correlations in tensor data, without introducing additional hierarchical probabilistic models. By analyzing the inferred posterior distribution and the non-decreasing property of the evidence lower bound (ELBO), we confirm the favorable convergence characteristics and global search capability of the proposed algorithm. Through simulations and experiments, we observe that compared to traditional TVB, the proposed algorithm achieves accurate automatic rank determination (ARD) in just a few iterations, significantly reducing convergence time. Meanwhile, it demonstrates superior parameter estimation accuracy with fewer iterations than the compared method.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"230 ","pages":"Article 109770"},"PeriodicalIF":3.4,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142723285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0