SwiftArray: Accelerating Queries on Multidimensional Arrays

Scientific instruments and simulation programs are generating large amounts of multidimensional array data.Queries with value and dimension subsetting conditions are commonly used by scientists to find useful information from big array data,and data storage and indexing methods play an important role in supporting queries on multidimensional array data efficiently.In this paper,we propose SwiftArray,a new storage layout with indexing techniques to accelerate queries with value and dimension subsetting conditions.In SwiftArray,the multidimensional array is divided into blocks and each block stores sorted values.Blocks are placed in the order of a Hilbert space-filling curve to improve data locality for dimension subsetting queries.We propose a 2-D-Bin method to build an index for the blocks’value ranges,which is an efficient way to avoid accessing unnecessary blocks for value subsetting queries.Our evaluations show that SwiftArray surpasses the NetCDF-4 format and FastBit indexing technique for queries on multidimensional arrays.     

Polynomial-rooting based fourth-order MUSIC for direction-of-arrival estimation of noncircular signals

A polynomial-rooting based fourth-order cumulant algorithm is presented for direction-of-arrival（DOA） estimation of second-order fully noncircular source signals, using a uniform linear array（ULA）. This algorithm inherits all merits of its spectralsearching counterpart except for the applicability to arbitrary array geometry, while reducing considerably the computation cost.Simulation results show that the proposed algorithm outperforms the previously developed closed-form second-order noncircular ESPRIT method, in terms of processing capacity and DOA estimation accuracy, especially in the presence of spatially colored noise.     

基于贝叶斯方法的Meta-分析

本文基于贝叶斯Meta-分析给出了Jeffreys无信息先验B(1/2,1/2)时的链接分布,并将其进行推广,给出了先验分布为B(α,β)时的链接分布。     

基于RFID阵列的无轨AGV系统的研究与设计

为改进有轨自动导航小车(AGV)的不足,研究一种基于RFID阵列的无轨AGV系统。该系统包括RFID阵列地板、无线通信网络、上位机、运行场地地图、小车运行控制系统;AGV安装若干RFID读卡器,运行在RFID阵列地板上,运行时通过读取地板下RFID电子标签的ID号,并通过无线通信网络发送到上位机;上位机构建和存储RFID阵列地板地图,上机位将接收到的ID号与存储的地图进行对照,计算出小车当前的位置的运行姿态,依据预设的运行路径生成AGV当前的控制指令并通过无线网络发送小车,控制小车的运行。系统通过利用RFID与地图实现定位,上位机生成控制指令的方式,实现AGV无轨运行。验证测试结果表明,AGV在预设运行路径上行驶,平均定位精度5cm,实用性好,稳定性高。     

基于卷积神经网络和稀疏滤波的调制识别方法

针对当前通信系统所采用的主要调制方式,提出了一种基于卷积神经网络和稀疏滤波的调制识别方法。首先,分析了利用信号循环谱二维灰度图进行通信信号调制识别的可行性;然后,通过降采样和裁剪技术对循环谱图预处理;最后,设计了深度卷积神经网络架构,并提出了稀疏滤波预训练的方法。仿真结果表明:相比于经典的基于深度学习的调制识别方法,该方法模型简单,优化量少,且在小样本场景下性能最佳,具有很高应用价值。     

φ混合随机变量阵列加权和的收敛性质

利用φ混合随机变量的Rosenthal型矩不等式,考虑一定权重条件下,不同分布φ混合随机变量阵列的强收敛性质,得到了一些新结果.     

核稀疏概念编码算法及在图像表示中的应用

稀疏编码算法是一种常用的图像数据表示方法.为了处理高度非线性分布的数据,文中提出了一种核稀疏概念编码算法,并应用于图像表示.该算法首先对邻域图进行谱分析,提取数据的几何流形结构信息;然后将原始特征空间数据映射到高维特征空间中,利用谱回归在高维特征空间中来计算基向量;最后在高维特征空间中对每个样本逐个进行表示.文中算法不仅能有效地处理非线性结构数据,而且只需求解一个稀疏特征值问题和两个回归问题,计算简单有效.在Yale、ORL和PIE图像库的聚类实验表明,文中算法的准确率和归一化互信息均优于其它几种对比算法.     

基于MVDR波束形成的FDA平台外干扰抑制

针对频控阵(frequency diverse array, FDA)在对与目标位置相近的平台外干扰进行抑制时, 传统FDA与非线性频偏结合不能实现距离-角度去耦合、对数递增FDA主瓣展宽较大和汉明窗加权FDA距离维旁瓣过高的问题, 在充分研究汉明窗加权的线性FDA(Hamming linear FDA, HL-FDA)方案的基础上, 对4种频偏方案的性能进行了分析, 提出采用FDA多输入多输出结构代替传统的一维均匀线性FDA结构, 通过结合最小方差无失真响应(minimum variance distortion free respinse, MVDR)准则, 将HL-FDA应用到MVDR自适应波束形成层面, 对平台外干扰进行抑制。仿真验证了HL-FDA在结合MVDR自适应波束形成算法后能有效地对抗距离-角度二维平台外干扰。     

Underdetermined DOA estimation and blind separation of non-disjoint sources in time-frequency domain based on sparse representation method

This paper deals with the blind separation of nonstation-ary sources and direction-of-arrival （DOA） estimation in the under-determined case, when there are more sources than sensors. We assume the sources to be time-frequency （TF） disjoint to a certain extent. In particular, the number of sources presented at any TF neighborhood is strictly less than that of sensors. We can identify the real number of active sources and achieve separation in any TF neighborhood by the sparse representation method. Compared with the subspace-based algorithm under the same sparseness assumption, which suffers from the extra noise effect since it can-not estimate the true number of active sources, the proposed algorithm can estimate the number of active sources and their cor-responding TF values in any TF neighborhood simultaneously. An-other contribution of this paper is a new estimation procedure for the DOA of sources in the underdetermined case, which combines the TF sparseness of sources and the clustering technique. Sim-ulation results demonstrate the validity and high performance of the proposed algorithm in both blind source separation （BSS） and DOA estimation.     

Image separation using wavelet-complex shearlet dictionary

This paper presents a new method for image separation through employing a combined dictionary consisting of wavelets and complex shearlets. Because the combined dictionary sparsely represents points and curvilinear singularities respectively, the image can be decomposed into pointlike and curvelike parts as accurate as possible. The proposed method based on the geo- metric separation theory introduced by Donoho in 2005 shows that accurate geometric separation of the morphologically distinct fea- tures of points and curves can be achieved by l1 minimization. The experimental results show that the proposed method can not only be effective but also greatly reduce the computing time.