Impact point prediction guidance of ballistic missile in high maneuver penetration condition

An impact point prediction(IPP) guidance based on supervised learning is proposed to address the problem of precise guidance for the ballistic missile in high maneuver penetration condition.An accurate ballistic trajectory model is applied to generate training samples,and ablation experiments are conducted to determine the mapping relationship between the flight state and the impact point.At the same time,the impact point coordinates are decoupled to improve the prediction accuracy,and the sigmoid activation function is improved to ameliorate the prediction efficiency.Therefore,an IPP neural network model,which solves the contradiction between the accuracy and the speed of the IPP,is established.In view of the performance deviation of the divert control system,the mapping relationship between the guidance parameters and the impact deviation is analysed based on the variational principle.In addition,a fast iterative model of guidance parameters is designed for reference to the Newton iteration method,which solves the nonlinear strong coupling problem of the guidance parameter solution.Monte Carlo simulation results show that the prediction accuracy of the impact point is high,with a 3 σ prediction error of 4.5 m,and the guidance method is robust,with a 3 σ error of 7.5 m.On the STM32F407 singlechip microcomputer,a single IPP takes about 2.374 ms,and a single guidance solution takes about9.936 ms,which has a good real-time performance and a certain engineering application value.

Surface Deposition of Ni(OH)_(2) and Lattice Distortion Induce the Electrochromic Performance Decay of NiO Films in Alkaline Electrolyte

NiO,an anodic electrochromic material,has applications in energy-saving windows,intelligent displays,and military camouflage.However,its electrochromic mechanism and reasons for its performance degradation in alkaline aqueous electrolytes are complex and poorly understood,making it challenging to improve NiO thin films.We studied the phases and electrochemical characteristics of NiO films in different states(initial,colored,bleached and after 8000 cycles)and identified three main reasons for performance degradation.First,Ni(OH)_(2)is generated during electrochromic cycling and deposited on the NiO film surface,gradually yielding a NiO@Ni(OH)_(2)core-shell structure,isolating the internal NiO film from the electrolyte,and preventing ion transfer.Second,the core-shell structure causes the mode of electrical conduction to change from first-to second-order conduction,reducing the efficiency of ion transfer to the surface Ni(OH)_(2)layer.Third,Ni(OH)_(2)and NiOOH,which have similar crystal structures but different b-axis lattice parameters,are formed during electrochromic cycling,and large volume changes in the unit cell reduce the structural stability of the thin film.Finally,we clarified the mechanism of electrochromic performance degradation of NiO films in alkaline aqueous electrolytes and provide a route to activation of NiO films,which will promote the development of electrochromic technology.

Charge self-consistent dynamical mean field theory calculations incombination with linear combination of numerical atomic orbitalsframework based density functional theory

We present a formalism of charge self-consistent dynamical mean field theory(DMFT)in combination with densityfunctional theory(DFT)within the linear combination of numerical atomic orbitals(LCNAO)framework.We implementedthe charge self-consistent DFT+DMFT formalism by interfacing a full-potential all-electron DFT code with threehybridization expansion-based continuous-time quantum Monte Carlo impurity solvers.The benchmarks on several 3d,4fand 5f strongly correlated electron systems validated our formalism and implementation.Furthermore,within the LCANOframework,our formalism is general and the code architecture is extensible,so it can work as a bridge merging differentLCNAO DFT packages and impurity solvers to do charge self-consistent DFT+DMFT calculations.

Effect of deposition temperature on SrFe12O19@carbonyl iron core–shell composites as high-performance microwave absorbers

The SrFe12O19@carbonyl iron(CI) core–shell composites used in microwave absorption are prepared by the metal–organic chemical vapor deposition(MOCVD). The x-ray diffractometer, scanning electron microscope, energy dispersive spectrometer, and vector network analyzer are used to characterize the structural, electromagnetic, and absorption properties of the composites. The results show that the SrFe12O19@CI composites with a core–shell structure could be successfully prepared under the condition: deposition temperatures above 180℃, deposition time 30 min, and gas flow rate 30 m L/min.The electromagnetic properties of the composites change significantly, and their absorption capacities are improved. Of the obtained samples, those samples prepared at a deposition temperature of 180℃ exhibit the best absorption performance.The reflection loss of SrFe12O19@CI(180℃) with 1.5 mm–2.5 mm in thickness is less than-10 dB in a frequency range of 8 GHz–18 GHz, which covers the whole X band and Ku band.

Synergistic Effect and Electrochromic Mechanism of Nanoflake Li-doped NiO in LiOH Electrolyte

Inorganic metal oxide electrochromic materials have good application prospects for energy-saving windows in buildings and smart display applications.Therefore,the development of electrochromic films with good cycling stabilities,fast color-change response times,and high coloring efficiencies has attracted considerable attention.In this study,nanoflake Li-doped NiO electrochromic films were prepared using a hydrothermal method,and the films exhibited superior electrochromic performances in the LiOH electrolyte.Li^(+)ions doping increased the ion transmission rates of the NiO films,and effectively promoted the transportation of ions from the electrolyte into NiO films.Meanwhile,the nanoflake microstructure caused the NiO films to have larger specific surface areas,providing more active sites for electrochemical reactions.It was determined that the NiO-Li20%film exhibited an ultra-fast response in the LiOH electrolyte(coloring and bleaching times reached 3 and 1.5 s,respectively).Additionally,the coloration efficiency was 62.1 cm^(2)C^(−1),and good cycling stability was maintained beyond 1500 cycles.Finally,the simulation calculation results showed that Li doping weakened the adsorption strengths of the NiO films to OH^(−),which reduced the generation and decomposition of NiOOH and helped to improve the cycling stabilities of the films.Therefore,the research presented in this article provides a strategy for designing electrochromic materials in the future.

Synchronization of High-order Discrete-time Linear Complex Networks with Time-varying Delays

Synchronization of high-order discrete-time complex networks with undirected topologies is studied and the impacts of time delays are investigated. Firstly,by the state decomposition,synchronization problems are transformed into asymptotic stability ones of multiple lower dimensional time-delayed subsystems. Then,linear matrix inequality( LMI) criteria for synchronization are given,which can guarantee the scalability of complex networks since they only include three LMI constraints independent of the number of agents. Moreover,an explicit expression of the synchronization function is presented,which can describe the synchronization behavior of all agents in complex networks. Finally,a numerical example is given to demonstrate the theoretical results,where it is shown that if the gain matrices of synchronization protocols satisfy LMI criteria for synchronization,synchronization can be achieved.

Air-Ground Collaborative Mobile Edge Computing:Architecture,Challenges,and Opportunities

By pushing computation,cache,and network control to the edge,mobile edge computing(MEC)is expected to play a leading role in fifth generation(5G)and future sixth generation(6G).Nevertheless,facing ubiquitous fast-growing computational demands,it is impossible for a single MEC paradigm to effectively support high-quality intelligent services at end user equipments(UEs).To address this issue,we propose an air-ground collaborative MEC(AGCMEC)architecture in this article.The proposed AGCMEC integrates all potentially available MEC servers within air and ground in the envisioned 6G,by a variety of collaborative ways to provide computation services at their best for UEs.Firstly,we introduce the AGC-MEC architecture and elaborate three typical use cases.Then,we discuss four main challenges in the AGC-MEC as well as their potential solutions.Next,we conduct a case study of collaborative service placement for AGC-MEC to validate the effectiveness of the proposed collaborative service placement strategy.Finally,we highlight several potential research directions of the AGC-MEC.

Modeling for multi-resonant behavior of broadband metamaterial absorber with geometrical substrate

Despite widespread use for extending absorption bandwidth, the coexistence and coupling mechanism of multiple resonance is not well understood. We propose two models to describe the multi-resonant behavior of a broadband metamaterial absorber with geometrical-array substrate （GAS）. The multi-resonance coupling of GAS is well described by logarithmic law. The interaction between metasurface and GAS can further broaden the absorption bandwidth by generating a new resonance which coexists with original resonances in substrate. The proposed models can thoroughly describe this multiple-resonance behavior, highlighting guidelines for designing broadband absorbers.

Preparation of multi-walled carbon nanotube–Fe composites and their application as light weight and broadband electromagnetic wave absorbers

Multi-walled carbon nanotube （MWCNT）-Fe composites were prepared via the metal organic chemical vapor deposi- tion by depositing iron pentacarbonyl on the surface of MWCNTs. The structural and morphological analyses demonstrated that Fe nanoparticles were deposited on the surface of the MWCNTs. The electromagnetic properties of the MWCNTs were significantly changed, and the absorbing capacity evidently improved after the Fe deposition on the MWCNT surface. A minimum reflection loss of -29.4 dB was observed at 8.39 GHz, and the less than -10 dB bandwidth was about 10.6 GHz, which covered the whole X band （8.2-12.4 GHz） and the whole Ku band （12.4-18 GHz）, indicating that the MWCNT-Fe composites could be used as an effective microwave absorption material.

Coupled Cross-correlation Neural Network Algorithm for Principal Singular Triplet Extraction of a Cross-covariance Matrix

This paper proposes a novel coupled neural network learning algorithm to extract the principal singular triplet (PST) of a cross-correlation matrix between two high-dimensional data streams. We firstly introduce a novel information criterion (NIC), in which the stationary points are singular triplet of the crosscorrelation matrix. Then, based on Newton's method, we obtain a coupled system of ordinary differential equations (ODEs) from the NIC. The ODEs have the same equilibria as the gradient of NIC, however, only the first PST of the system is stable (which is also the desired solution), and all others are (unstable) saddle points. Based on the system, we finally obtain a fast and stable algorithm for PST extraction. The proposed algorithm can solve the speed-stability problem that plagues most noncoupled learning rules. Moreover, the proposed algorithm can also be used to extract multiple PSTs effectively by using sequential method. © 2014 Chinese Association of Automation.

First-principles study of co-adsorption behavior of O_(2)and CO_(2)molecules onδ-Pu(100)surface

First principles calculation is performed to study the co-adsorption behaviors of O_(2)and CO_(2)onδ-Pu(100)surface by using a slab model within the framework of density functional theory(DFT).The results demonstrate that the most favorable co-adsorption configurations are T_(v)-C_(4)O_(7)and T_(p1)-C_(2)O_(8),with adsorption energy of-17.296 e V and-23.131 e V for CO_(2)-based and O_(2)-based system,respectively.The C and O atoms mainly interact with the Pu surface atoms.Furthermore,the chemical bonding between C/O and Pu atom is mainly of ionic state,and the reaction mechanism is that C 2 s,C 2 p,O 2s,and O 2p orbitals overlap and hybridize with Pu 6 p,Pu 6 d,and Pu 5 f orbital,resulting in the occurrence of new band structure.The adsorption and dissociation of CO_(2)molecule are obviously promoted by preferentially occupying adsorbed O atoms,therefore,a potential CO_(2)protection mechanism for plutonium-based materials is that in CO_(2)molecule there occurs complete dissociation of CO_(2)→C+O+O,then the dissociated C atom combines with O atom from O_(2)dissociation and produces CO,which will inhibit the O_(2)from further oxidizing Pu surface,and slow down the corrosion rate of plutoniumbased materials.

Effect of preload force on heat generation of fatigue crack in ultrasonic infrared thermography

The heat generation behaviors of fatigue crack are deeply investigated under different preload forces combing numerical simulation and experiment.Firstly,a multi-contact simulation model is applied to stimulate the crack surfaces contact and the horn-sample contact under ultrasonic excitation for calculating the temperature fields.Then,the ultrasonic infrared thermography testing and the microscope testing are carried out for the heat generation and the plastic deformation behaviors of crack region under different preload forces.On this basis,an indirect observation method based on dots distribution is proposed to estimate the plastic deformation on crack contact surfaces.The obtained results show that the temperature rise of crack region increases with the increase of preload force when the preload force is less than 250 N,while the temperature rise rapidly declines due to the plastic deformation on crack contact surfaces and the inhibition effect when the preload force is 280 N.Moreover,the plastic deformation does not lead to the crack propagation,but reduces the detection repeatability of fatigue crack.This work provides an effective method for optimizing testing conditions in practical testing processes,which will be helpful to the establishment of testing standards for batches of test objects in ultrasonic infrared thermography testing.

Parameter analysis of chaotic superlattice true random number source

Superlattices in chaotic state can be used as a key part of a true random number generator. The chaotic characteristics of the signal generated in the superlattice are mostly affected by the parameters of the superlattice and the applied voltage, while the latter is easier to adjust. In this paper, the model of the superlattice is first established. Then, based on this model, the chaotic characteristics of the generated signal are studied under different voltages. The results demonstrate that the onset of chaos in the superlattice is typically accompanied by the mergence of multistability, and there are voltage intervals in each of which the generated signal is chaotic.

Convergence Analysis of a Self-Stabilizing Algorithm for Minor Component Analysis

The M?ller algorithm is a self-stabilizing minor component analysis algorithm.This research document involves the study of the convergence and dynamic characteristics of the M?ller algorithm using the deterministic discrete time(DDT)methodology.Unlike other analysis methodologies,the DDT methodology is capable of serving the distinct time characteristic and having no constraint conditions.Through analyzing the dynamic characteristics of the weight vector,several convergence conditions are drawn,which are beneficial for its application.The performing computer simulations and real applications demonstrate the correctness of the analysis’s conclusions.

Directional Analysis of the Chaotic Superlattice around the Equilibrium Point in the Phase Space

The recently proposed method of our research group named as directional Lyapunov exponents（DLEs） is presented. Then, DLEs are used to analyze the eigenstructure of the output phase space around the equilibrium points. Finally, the impacts of the superlattice parameter changes on the characteristics of the output chaotic signal are analyzed. The experimental results show that parameter changes of the superlattice will affect the eigenstructure around the equilibrium points in the output phase space, and DLEs are sensitive to these changes.

Deep hybrid: Multi-graph neural network collaboration for hyperspectral image classification

With limited number of labeled samples,hyperspectral image(HSI)classification is a difficult Problem in current research.The graph neural network(GNN)has emerged as an approach to semi-supervised classification,and the application of GNN to hyperspectral images has attracted much attention.However,in the existing GNN-based methods a single graph neural network or graph filter is mainly used to extract HSI features,which does not take full advantage of various graph neural networks(graph filters).Moreover,the traditional GNNs have the problem of oversmoothing.To alleviate these shortcomings,we introduce a deep hybrid multi-graph neural network(DHMG),where two different graph filters,i.e.,the spectral filter and the autoregressive moving average(ARMA)filter,are utilized in two branches.The former can well extract the spectral features of the nodes,and the latter has a good suppression effect on graph noise.The network realizes information interaction between the two branches and takes good advantage of different graph filters.In addition,to address the problem of oversmoothing,a dense network is proposed,where the local graph features are preserved.The dense structure satisfies the needs of different classification targets presenting different features.Finally,we introduce a GraphSAGEbased network to refine the graph features produced by the deep hybrid network.Extensive experiments on three public HSI datasets strongly demonstrate that the DHMG dramatically outperforms the state-ofthe-art models.

Lightweight broadband microwave absorbing metamaterial with CB-ABS composites fabricated by 3D printing

The self-similarity,high geometric symmetry and spatial utilization properties of fractal structures provide new methods for the development of absorbing metamaterials.In this paper,the microwave absorption properties of the gradient dendritic fractal metamaterial structure(GDFMs)based on carbon black and acrylonitrile-butadiene-styrene composites were investigated.The optimal metamaterial structure has an effective absorption in the frequency range of 4.5-40 GHz.The rotational-symmetry GDFMs leads to the polarization independence,and the GDFMs exhibits a wide-angle absorption performance for both TE and TM waves.It is expected that the proposed GDFMs has good application prospects in electromagnetic wave absorption.

Temperature Field in Laser Line Scanning Thermography: Analytical Calculation and Experiment

The temperature field in laser line scanning thermography is investigated comprehensively in this work,including analytical calculation and experiment.Firstly,the principle of laser line scanning thermography is analyzed.On this basis,a physical laser line scanning model is proposed.Afterwards,based on Fourier transform(FT)and segregation variablemethod(SVM),the heat conduction differential equation in laser line scanning thermography is derived in detail.The temperature field of the composite-based coatings model with defects is simulated numerically.The results show that the laser line scanning thermography can effectively detect the defects in the model.The correctness of the analytical calculation is verified by comparing the surface temperature distribution obtained by analytical calculation and numerical simulation.Additionally,an experiment is carried out and the changeable surface temperature obtained by analytical calculation is compared with the experimental results.It shows that the error of maximum temperature obtained by analytical calculation and by experiment is 8%with high accuracy,which proves the correctness of analytical calculation and enriches the theoretical foundation of laser line scanning thermography.

Ultrasonic Nondestructive Signals Processing Based on Matching Pursuit with Gabor Dictionary

The success of ultrasonic nondestructive testing technology depends not only on the generation and measurement of the desired waveform, but also on the signal processing of the measured waves. The traditional time-domain methods have been partly successful in identifying small cracks, but not so successful in estimating crack size, especially in strong backscattering noise. Sparse signal representation can provide sparse information that represents the signal time-frequency signature, which can also be used in processing ultrasonic nondestructive signals. A novel ultrasonic nondestructive signal processing algorithm based on signal sparse representation is proposed. In order to suppress noise, matching pursuit algorithm with Gabor dictionary is selected as the signal decomposition method. Precise echoes information, such as crack location and size, can be estimated by quantitative analysis with Gabor atom. To verify the performance, the proposed algorithm is applied to computer simulation signal and experimental ultrasonic signals which represent multiple backscattered echoes from a thin metal plate with artificial holes. The results show that this algorithm not only has an excellent performance even when dealing with signals in the presence of strong noise, but also is successful in estimating crack location and size. Moreover, the algorithm can be applied to data compression of ultrasonic nondestructive signal.

DATA-MINING BASED FAULT DETECTION

This paper presents a fault-detection method based on the phase space reconstruction and data mining approaches for the complex electronic system. The approach for the phase space reconstruction of chaotic time series is a combination algorithm of multiple autocorrelation and F-test, by which the quasi-optimal embedding dimension and time delay can be obtained. The data mining algorithm, which calculates the radius of gyration of unit-mass point around the centre of mass in the phase space, can distinguish the fault parameter from the chaotic time series output by the tested system. The experimental results depict that this fault detection method can correctly detect the fault phenomena of electronic system.