合成孔径雷达(synthetic aperture radar,SAR)图像是一种能够全天时、全天候产生高分辨率图像的主动式对地观测系统,在农业和军事等方面得到了广泛应用.然而,由于相干成像机制受到相干斑噪声的影响,因此提出了一种基于生成式对抗网络的...合成孔径雷达(synthetic aperture radar,SAR)图像是一种能够全天时、全天候产生高分辨率图像的主动式对地观测系统,在农业和军事等方面得到了广泛应用.然而,由于相干成像机制受到相干斑噪声的影响,因此提出了一种基于生成式对抗网络的SAR图像盲去噪算法,构造了基于残差结构的深度卷积神经网络(deep convolutional neural network,DCNN)作为生成网络,可以加速训练过程,提高去噪性能.本文还利用峰值信噪比(peak signal to noise ratio,PSNR)和结构相似指数(structural similarity index measure,SSIM)定义一种新的损失函数,使得去噪后的图像更符合人眼的视觉感知要求.实验结果表明,本文算法可以有效地抑制SAR图像中的相干噪声,获得良好的去噪效果.展开更多
利用生物芯片真菌毒素阵列,选用其中的赭曲霉毒素A、脱氧雪腐镰刀菌烯醇、黄曲霉毒素B1和玉米赤霉烯酮4个组分,同时测定其在奶牛饲料中的残留量,考察该生物芯片的准确性、精密度和重现性等指标.结果表明:4种真菌毒素的标准曲线线性相关...利用生物芯片真菌毒素阵列,选用其中的赭曲霉毒素A、脱氧雪腐镰刀菌烯醇、黄曲霉毒素B1和玉米赤霉烯酮4个组分,同时测定其在奶牛饲料中的残留量,考察该生物芯片的准确性、精密度和重现性等指标.结果表明:4种真菌毒素的标准曲线线性相关系数均可达到0.99以上;试剂盒质控样品和阴性样品2个水平的加标回收率在80%~120%之间,变异系数(coefficient of variance,CV)在15%以内,方法准确性和重复性较好;对奶牛饲料样品检测结果重现性考察的CV在10%以内,表明方法重现性较好;与高效液相色谱法相比,2种检测方法的结果差异性小,且生物芯片法前处理更为简便.真菌毒素阵列生物芯片法操作简单、结果准确,缩短了大量样本的筛查时间,为批量样品筛查提供了可靠的技术保证.展开更多
In order to improve the reliability and resource utilization efficiency of vehicle-to-vehicle(V2V)communication system,in this paper,the fairness optimization and power allocation for the cognitive V2V network that ta...In order to improve the reliability and resource utilization efficiency of vehicle-to-vehicle(V2V)communication system,in this paper,the fairness optimization and power allocation for the cognitive V2V network that takes into account the realistic three-dimensional(3D)channel are investigated.Large-scale and small-scale fading are considered in the proposed channel model.An adaptive non-orthogonal multiple access(NOMA)/orthogonal multiple access(OMA)scheme is proposed to reduce the complexity of successive-interference-cancellation(SIC)in decoding and improve spectrum utilization.Also,a fairness index that takes into account each user's requirements is proposed to indicate the optimal point clearly.In the imperfect SIC,the optimization problem of maximizing user fairness is formulated.Then,a subgradient descent method is proposed to solve the optimization problem with customizable precision.And the computational complexity of the proposed method is analyzed.The achievable rate,outage probability and user fairness are analyzed.The results show that the proposed adaptive NOMA/OMA(A-NOMA/OMA)outperforms both NOMA and OMA.The simulation results are compared with validated analysis to confirm the theoretical analysis.展开更多
文摘合成孔径雷达(synthetic aperture radar,SAR)图像是一种能够全天时、全天候产生高分辨率图像的主动式对地观测系统,在农业和军事等方面得到了广泛应用.然而,由于相干成像机制受到相干斑噪声的影响,因此提出了一种基于生成式对抗网络的SAR图像盲去噪算法,构造了基于残差结构的深度卷积神经网络(deep convolutional neural network,DCNN)作为生成网络,可以加速训练过程,提高去噪性能.本文还利用峰值信噪比(peak signal to noise ratio,PSNR)和结构相似指数(structural similarity index measure,SSIM)定义一种新的损失函数,使得去噪后的图像更符合人眼的视觉感知要求.实验结果表明,本文算法可以有效地抑制SAR图像中的相干噪声,获得良好的去噪效果.
文摘利用生物芯片真菌毒素阵列,选用其中的赭曲霉毒素A、脱氧雪腐镰刀菌烯醇、黄曲霉毒素B1和玉米赤霉烯酮4个组分,同时测定其在奶牛饲料中的残留量,考察该生物芯片的准确性、精密度和重现性等指标.结果表明:4种真菌毒素的标准曲线线性相关系数均可达到0.99以上;试剂盒质控样品和阴性样品2个水平的加标回收率在80%~120%之间,变异系数(coefficient of variance,CV)在15%以内,方法准确性和重复性较好;对奶牛饲料样品检测结果重现性考察的CV在10%以内,表明方法重现性较好;与高效液相色谱法相比,2种检测方法的结果差异性小,且生物芯片法前处理更为简便.真菌毒素阵列生物芯片法操作简单、结果准确,缩短了大量样本的筛查时间,为批量样品筛查提供了可靠的技术保证.
基金supported by the National Natural Science Foundation of China(62001166,62172139)the Open Subject of Hebei Key Laboratory of Power Internet of Things Technology(2023KFKT002)the Natural Science Foundation of Hebei Province of China(F2022201055).
文摘In order to improve the reliability and resource utilization efficiency of vehicle-to-vehicle(V2V)communication system,in this paper,the fairness optimization and power allocation for the cognitive V2V network that takes into account the realistic three-dimensional(3D)channel are investigated.Large-scale and small-scale fading are considered in the proposed channel model.An adaptive non-orthogonal multiple access(NOMA)/orthogonal multiple access(OMA)scheme is proposed to reduce the complexity of successive-interference-cancellation(SIC)in decoding and improve spectrum utilization.Also,a fairness index that takes into account each user's requirements is proposed to indicate the optimal point clearly.In the imperfect SIC,the optimization problem of maximizing user fairness is formulated.Then,a subgradient descent method is proposed to solve the optimization problem with customizable precision.And the computational complexity of the proposed method is analyzed.The achievable rate,outage probability and user fairness are analyzed.The results show that the proposed adaptive NOMA/OMA(A-NOMA/OMA)outperforms both NOMA and OMA.The simulation results are compared with validated analysis to confirm the theoretical analysis.
