Automatic modulation recognition of radiation source signals based on two-dimensional data matrix and improved residual neural network

Automatic modulation recognition(AMR)of radiation source signals is a research focus in the field of cognitive radio.However,the AMR of radiation source signals at low SNRs still faces a great challenge.Therefore,the AMR method of radiation source signals based on two-dimensional data matrix and improved residual neural network is proposed in this paper.First,the time series of the radiation source signals are reconstructed into two-dimensional data matrix,which greatly simplifies the signal preprocessing process.Second,the depthwise convolution and large-size convolutional kernels based residual neural network(DLRNet)is proposed to improve the feature extraction capability of the AMR model.Finally,the model performs feature extraction and classification on the two-dimensional data matrix to obtain the recognition vector that represents the signal modulation type.Theoretical analysis and simulation results show that the AMR method based on two-dimensional data matrix and improved residual network can significantly improve the accuracy of the AMR method.The recognition accuracy of the proposed method maintains a high level greater than 90% even at -14 dB SNR.

Single-cell manipulation by two-dimensional micropatterning

Cells are highly sensitive to their geometrical and mechanical microenvironment that directly regulate cell shape,cytoskeleton and organelle,as well as the nucleus morphology and genetic expression.The emerging two-dimensional micropatterning techniques offer powerful tools to construct controllable and well-organized microenvironment for single-cell level investigations with qualitative analysis,cellular standardization,and in vivo environment mimicking.Here,we provide an overview of the basic principle and characteristics of the two most widely-used micropatterning techniques,including photolithographic micropatterning and soft lithography micropatterning.Moreover,we summarize the application of micropatterning technique in controlling cytoskeleton,cell migration,nucleus and gene expression,as well as intercellular communication.

Eigenfunction expansion method of upper triangular operator matrixand application to two-dimensional elasticity problems based onstress formulation

This paper studies the eigenfunction expansion method to solve the two dimensional （2D） elasticity problems based on the stress formulation. The fundamental system of partial differential equations of the 2D problems is rewritten as an upper tri angular differential system based on the known results, and then the associated upper triangular operator matrix matrix is obtained. By further research, the two simpler com plete orthogonal systems of eigenfunctions in some space are obtained, which belong to the two block operators arising in the operator matrix. Then, a more simple and conve nient general solution to the 2D problem is given by the eigenfunction expansion method. Furthermore, the boundary conditions for the 2D problem, which can be solved by this method, are indicated. Finally, the validity of the obtained results is verified by a specific example.

Design of Discrete-time Repetitive Control System Based on Two-dimensional Model

This paper presents a novel design method for discrete-time repetitive control systems （RCS） based on two-dimensional （2D） discrete-time model. Firstly, the 2D model of an RCS is established by considering both the control action and the learning action in RCS. Then, through constructing a 2D state feedback controller, the design problem of the RCS is converted to the design problem of a 2D system. Then, using 2D system theory and linear matrix inequality （LMI） method, stability criterion is derived for the system without and with uncertainties, respectively. Parameters of the system can be determined by solving the LMI of the stability criterion. Finally, numerical simulations validate the effectiveness of the proposed method.

Fast forward modeling of gravity anomalies for two-dimensional bodies of arbitrary shape and density distribution

A fast and high precision spatial domain algorithm is presented for forward modeling of two-dimensional(2D)body gravity anomalies of arbitrary shape and density distribution.The new algorithm takes advantage of the convolution properties of the expression for 2D gravity anomalies,uses a rectangular cell as a grid subdivision unit,and then 2D bodies with irregular cross-sections are approximated by a combination of 2D bodies with a rectangular cross section.The closed-form expression is used to calculate the gravitational anomalies of the combination of 2D bodies with a rectangular cross section.To improve computing effi ciency,the new algorithm uses a fast algorithm for the implementation of the Toeplitz matrix and vector multiplication.The synthetic 2D models with rectangular and circular cross-sections and constant and variable densities are designed to evaluate the computational accuracy and speed of the new algorithm.The experiment results show that the computation costs less than 6 s for a grid subdivision with 10000×10000 elements.Compared to the traditional forward modeling methods,the proposed method significantly improved computational effi ciency while guaranteeing computational accuracy.

Further studies on stability analysis of nonlinear Roesser-type two-dimensional systems

This paper is concerned with further relaxations of the stability analysis of nonlinear Roesser-type two-dimensional （2D） systems in the Takagi-Sugeno fuzzy form. To achieve the goal, a novel slack matrix variable technique, which is homogenous polynomially parameter-dependent on the normalized fuzzy weighting functions with arbitrary degree, is developed and the algebraic properties of the normalized fuzzy weighting functions are collected into a set of augmented matrices. Consequently, more information about the normalized fuzzy weighting functions is involved and the relaxation quality of the stability analysis is significantly improved. Moreover, the obtained result is formulated in the form of linear matrix inequalities, which can be easily solved via standard numerical software. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed result.

Corrigendum to“Atomic-scale electromagnetic theory bridging optics in microscopic world and macroscopic world”

The signs of the electric field markers in Figs.2 and 4 of the paper[Chin.Phys.B 32104211(2023)]have been corrected.These modifications do not affect the results derived in the paper.

低秩矩阵恢复下的自适应图像超分辨率重建

低分辨率自适应图像的像素密度过于稀疏,导致图像清晰度达不到超分辨标准。为此提出低秩矩阵恢复下的自适应图像超分辨率重建方法。构建低秩矩阵恢复模型,计算峰值信噪比参数,完成低秩矩阵恢复下的自适应图像降噪处理。在图像区域中提取自适应特征,根据超分辨率判别条件定义具体的重建函数表达式,完成低秩矩阵恢复下自适应图像超分辨率重建方法的设计。实验结果表明,该方法的应用可使图像有效去噪,信噪比高于31 dB,重建后图像分辨率均值达到100 PPI,实现了超分辨重建。

一种用电设备分析识别原理与应用

非侵入式负荷监测(NILM)与识别是智能电网建设的重要方面。针对非侵入式用电负荷监测技术提出了一种基于V-I轨迹与奇次谐波分量特征的混合特征矩阵和卷积神经网络相结合的方法。具体内容为:分析用电设备的基本特征,包括输入电流稳态特征和暂态特征。建立了六种单相交流电源供电的用电设备MATLAB/Simulink仿真电路,分别为电阻加热器、电吹风、LED灯串、电源适配器、变频空调和变频冰箱,作为待分析识别的用电设备,并提取了这六种负荷模型的网侧电流波形和频谱、V-I轨迹以及奇次谐波电流分量数据作为基本特征量;提出了一种采用V-I轨迹与奇次谐波特征的混合特征矩阵以及卷积神经网络(CNN)进行用电设备分析识别,经过PLAID数据集的训练和测试,能够有效识别稳态运行下的用电设备,给出了详细的解算过程,并提供了应用算例。此外,对比分析了已有三种检测方法,验证本文提出的基于混合特征矩阵以及卷积神经网络用电设备分析识别方法的优越性。

Altered expression of nuclear matrix proteins in etoposide induced apoptosis in HL-60 cells

The events of cell death and the expression of nuclear matrix protein (NMP) have been investigated in a promyelocytic leukemic cell line HL-60 induced with etoposide. By means of TUNEL assay, the nuclei displayed a characteristic morphology change, and the amount of apoptotic cells increased early and reached maximun about 39% after treatment with etoposide for 2 h. Nucleosomal DNA fragmentation was observed after treatment for 4 h. The morphological change of HL-60 cells, thus, occurred earlier than the appearance of DNA ladder. Total nuclear matrix proteins were analyzed by 2-dimensional gel electrophoresis. Differential expression of 59 nuclear matrix proteins was found in 4 h etoposide treated cells. Western blotting was then performed on three nuclear matrix acssociated proteins, PML, HSC70 and NuMA. The expression of the suppressor PML protein and heat shock protein HSC70 were significantly upregulated after etoposide treatment, while NuMA, a nuclear mitotic apparatus protein, was down regulated. These results demonstrate that significant biochemical alterations in nuclear matrix proteins take place during the apoptotic process.

CHANGES OF NUCLEAR MATRIX PROTEIN AND ITS RELATIONSHIP WITH c-erbB-2 IN HUMAN COLON ADENOCARCINOMA

Objective： Nuclear matrix protein is tissue, cell-type specific, and tumor-relative. It plays an important role in the regulation of intranuclear processes. Some researches also showed that a c-erbB-2 promoter-specific DNA-binding nuclear matrix protein is present only in malignant human breast tissues and induces mitogenesis and cell surface expression of the c-erbB-2 protein in resting NIH/3T3 cells. But it is not clear that how it in colon adenocarcinomas. Methods： Two-dimensional gel electrophoretic method was used for NMP identification and immunohistochemistry was used for c-erbB-2 detection in 12 cases of colon adenocarcinomas and matched adjacent normal colon tissues. Results： 5 different nuclear matrix proteins （named C1-C5） were identified in 12 colon adenocarcinoma specimens, but not in the matched adjacent normal colon tissues; 3 nuclear matrix proteins （named N1-N3） were identified in all 12 matched adjacent normal colon tissues, but not in colon adenocarcinoma specimens. A nuclear matrix protein （named N4） was detected in all of 9 moderated-well differentiated adenocarcinomas and all 12 matched adjacent normal colon tissues, but not in 3 poor-differentiated adenocarcinomas. All of the 10 colon adenocarcinomas which had the nuclear matrix protein C4 were c-erbB-2 expression positive. Conclusion： The data suggest that there are specific nuclear matrix proteins in colon adenocarcinomas and its subtypes, which maybe valuable to serve as markers of colon adenocarcinomas in future. Nuclear matrix protein C4 probably is a c-erbB-2 promotor-specific nuclear matrix protein in colon adenocarcinomas, and may induce the expression of c-erbB-2.

不同稀疏基对单像素相机矩阵性能的影响

针对不同稀疏基与单像素相机矩阵构成的重构矩阵研究较少的问题。首先将DCT矩阵和DWT矩阵这两种稀疏基分别与单像素相机矩阵组合成不同的重构矩阵,将得到的重构矩阵进行优化,分析优化过程中重构矩阵与优化矩阵性质的改变,再用重构矩阵与优化矩阵对信号进行重构实验。实验结果表明,基于DWT矩阵得到的重构矩阵和优化矩阵对信号的重构效果更好。基于DWT矩阵的重构矩阵和优化矩阵比基于DCT矩阵的重构矩阵和优化矩阵展现出了更好的重构性能。

近20年鄂西地区植被覆盖度时空变化特征分析

基于2000—2020年的MOD13Q1 NDVI遥感数据,使用像元二分模型计算湖北省西部山体区域的植被覆盖度,并利用斜率模型、马尔可夫转移矩阵模型和赫斯特指数综合分析了植被覆盖度的时空变化规律。结果表明,研究区的植被覆盖度总体呈上升趋势,平均植被覆盖度增加了0.025,轻微增长区域面积为44 359.26 km^(2),显著性增长面积为3 069.375 km^(2),不显著性变化的面积为39 862 km^(2)。2000—2020年期间,时序植被覆盖度的赫斯特指数为0.63,表明研究区内植被覆盖度的增长趋势在未来是可持续的。本研究成果不仅可为城市生态环境评价提供科学依据,而且可为城市的生态建设和可持续发展提供决策支持。

基于后验信息的压缩感知图像重构方法

单像素相机的测量数据可采用正交匹配追踪(orthogonal matchingpursuit,OMP)算法重构,但是重构得到的图像质量不好。本文提出一种提高图像重构效果的方法,该方法利用先验信息(列模平均值)判断重构效果优劣;通过测量数据相邻列相减的操作,以增强稀疏度。首先,基于OMP对测量数据逐列重构;然后,对重构效果差的列,作相邻列相减的操作后逐列重构;最后,通过逐列累加操作得到重构效果更好的图像。实验结果表明,该方法在仅使用OMP的情况下可以使重构图像的信噪比(signal tonoiseratio,SNR)得到很大提高,虽然重构图像上有很明显的条纹,但是重构结果依然获得很大改善。

基于分离障碍物的地下车库车位排布算法

地下车库中的障碍物是车位排布中除不规则外轮廓边界之外最复杂的约束条件,为此本文提出了一种根据障碍物分离处理的启发式算法。根据障碍物分布,将整个车库区域分为带障碍物和不带障碍物两部分,对其分别使用不同的方法计算。其中,包含障碍物部分通过像素分割构建用于描述空旷程度的矩阵,并计算最优排布方案;不包含障碍物的部分通过遗传算法处理,同时考虑两部分结合部位的车位损失,并合理规划承重柱,保证连通性。通过对不同形状、内部结构的地下车库的排布,该算法可以在有限运算时间内得到排布结果,为人工设计师提供参考辅助。

基于矩阵偏序关系的形态学算子

已有形态偏序由于忽略了图像像素的局部相关性导致运算结果产生噪声叠加、拓扑失真等问题,本文在矩阵Frobenius范数的基础上定义了一种新的偏序关系,从理论上证明了该序满足的自反性、传递性和反对称性.在此基础上,本文提出了基于新序的形态学膨胀、腐蚀算子和相关的梯度运算算子.为验证新序和算子的有效性,与已有的算法进行对比实验,结果表明,新序和相应的算子在保证颜色分量相关性的同时,利用矩阵运算保证了像素的局部相关性,在抑制噪声和边缘保持方面均优于现有的算法.同时,通过结果对比和理论分析发现,新的形态算子对结构元素尺寸的包容性强,克服了形态算子在应用时难以选择合适结构元素大小的问题.这种新序是多通道图像处理的基础,可以扩宽形态学理论的应用范围.

Atomic-scale electromagnetic theory bridging optics in microscopic world and macroscopic world

Atoms in the microscopic world are the basic building blocks of the macroscopic world. In this work, we construct an atomic-scale electromagnetic theory that bridges optics in the microscopic and macroscopic worlds. As the building block of the theory, we use the microscopic polarizability to describe the optical response of a single atom, solve the transport of electromagnetic wave through a single atomic layer under arbitrary incident angle and polarization of the light beam, construct the single atomic layer transfer matrix for light transport across the atomic layer. Based on this transfer matrix, we get the analytical form of the dispersion relation, refractive index, and transmission/reflection coefficient of the macroscopic medium. The developed theory can handle single-layer and few-layers of homogeneous and heterogeneous 2D materials, investigate homogeneous 2D materials with various vacancies or insertion atomic-layer defects, study compound 2D materials with a unit cell composed of several elements in both the lateral and parallel directions with respect to the light transport.

Two-dimensional van der Waals thin film transistors as active matrix for spatially resolved pressure sensing

The development of pressure sensor arrays capable of distinguishing the shape and texture details of objects is of considerable interest in the emerging fields of smart robots,prostheses,human-machine interfaces,and artificial intelligence(AI).Here we report an integrated pressure sensor array,by combining solution-processed two-dimensional(2D)MoS2 van der Waals(vdW)thin film transistor(TFT)active matrix and conductive micropyramidal pressure-sensitive rubber(PSR)electrodes made of polydimethylsiloxane/carbon nanotube composites,to achieve spatially revolved pressure mapping with excellent contrast and low power consumption.We demonstrate a 10×10 active matrix by using the 2D MoS2 vdW-TFTs with high on-off ratio>10^(6),minimal hysteresis,and excellent device-to-device uniformity.The combination of the vdW-TFT active matrix with the highly uniform micropyramidal PSR electrodes creates an integrated pressure sensing array for spatially resolved pressure mapping.This study demonstrates that the solution-processed 2D vdW-TFTs offer a solution for active-matrix control of pressure sensor arrays,and could be extended for other active-matrix arrays of electronic or optoelectronic devices.

多倾斜角度数字沙盘自适应投影算法

抬高数字沙盘一定倾斜角有利于提升实体沙盘和投影内容的观赏体验,但沙盘倾斜后投影内容会偏移。针对该问题,本文提出了多倾斜角度数控沙盘自适应投影算法,根据投影内容和现场环境参数建立原始像素矩阵;对不同的投影位置建立相应的坐标纠正模型;遍历像素点后计算出倾斜后的新坐标;将每个点的颜色值赋给新坐标点,得到纠正像素矩阵,从而实现自适应投影。试验结果表明,该算法能有效地保证投影内容准确地投影到沙盘上。

智能前照灯灯光功能现状与分析

智能前照灯技术是汽车行业智能化转型的先进技术。智能灯光是用户对智能汽车认知最简单、直接的方式之一。本文从已获上市的智能前照灯技术切入,聚焦现有高端智能灯光功能,由浅入深,总结并分析智能前照灯灯光功能现状与发展趋势。