LVD中心传火管与常规中心传火管的传火性能比较

通过高速摄影和压力——时间曲线的测试比较了LVD中心传火管和常规中心传火管的传火性能。研究表明。LVD中心传火管与常规中心传火管相比较有比较高的传火一致性和传火速度。在不同装药条件下其燃烧波宽度在3～4ms左右,传火压力在30～40MPa左右,平均传火速度在350～1800m／s之间。     

ISAR imaging of maneuvering target with complex motions based on ACCF–LVD

This paper considers the inverse synthetic aperture radar (ISAR) imaging problem for a maneuvering target with complex motions, involving range migration (RM) and Doppler frequency migration (DFM) within the coherent integration period of radar imaging, which will degrade the imaging quality. A nonsearching ISAR imaging algorithm based on adjacent cross correlation function (ACCF) and Lv's distribution (LVD), i.e., ACCF–LVD, is proposed, where the ACCF is applied to correct the RM and reduce the order of DFM. Then the motion parameters are estimated via LVD and Fourier transform. With the estimated motion parameters, high quality ISAR images can be achieved. The advantage of the presented method is that it can estimate the motion parameters under low signal-to-noise ratio (SNR) without searching procedures. Finally, several simulation examples are shown to confirm the validity of the proposed algorithm.     

Linearly varying surface-implanted n layer used for improving trade-off between breakdown voltage and on-resistance of RESURF LDMOS transistor

A new RESURF LDMOS transistor using a linearly varying surface-implanted doped (LVD) n⁻ layer is reported. Detailed numerical simulations demonstrate the characteristics of this device incorporating an LVD n⁻ layer and indicate an enhancement on the performance in comparison to an optimal conventional structure with an uniform epi-layer concentration.     

低尺度血管检测在视网膜血管分割中的应用

视网膜图像分析成为目前诊断多种疾病非侵入的主要方式,其中血管的提取是最重要的一步。监督学习的方法在血管提取上有很好的效果,为了进一步提高检测的精度,提出了低尺度血管检测(LVD)算法。该网络除了有一个提取输入原尺度下特征的子网络外,还增加了两个低尺度下的特征提取子网络,并将低尺度下的单一输出融合原尺寸下的特征,降维后得到最后的输出结果。考虑到眼底血管结构特性,在LVD中设计了具有较深层数和较少参数的非对称固定深度子网络(ADS)。在公共的数据库DRIVE中进行测试,仅采用彩色眼底图像的绿色分量和B-COSFIRE滤波响应作为特征输入,其敏感性、特异性、准确率以及AUC指标分别为0.819 2、0.984 2、0.969 5、0.978 2,达到了先进水平。     

基于LVD变换的大时宽带宽信号雷达高速目标检测方法

随着电子战及超高速武器的快速发展,在现有雷达体制下,传统目标探测技术面临着严峻的挑战。为了在提高雷达高速目标的检测性能的同时,兼顾雷达抗干扰能力和战场生存能力,雷达发射需具有低截获特性的大时宽带宽信号。这种情况下,高速运动目标产生尺度效应和脉内多普勒使得匹配滤波失效。针对该问题,提出一种基于吕氏分布(LVD)的大时宽带雷达信号高速多目标检测方法。该方法对高速目标回波的自相关函数进行尺度变换,消除时间变量与延迟变量之间的耦合;再通过2D-FFT变换将回波能量在变换域中积累成峰值;最后通过峰值检测实现对高速目标的检测与参数估计。仿真分析表明,该方法不仅在低信噪比(SNR)下具有较高的检测性能,并且在复杂场景中能够检测多个目标,同时具有较高的参数估计精度。