基于卷积神经网络的新奇检测技术在结构损伤识别中的应用

针对新奇检测难以同时识别结构损伤时刻和损伤位置的问题,提出在新奇检测中引入卷积神经网络以实现损伤时刻和损伤位置的一次性确定。首先,采用小波包技术处理结构响应得到小波包能量,并将相邻测点对应频带的能量比作为新奇检测模型的特征向量;然后,以结构健康时的特征向量作为训练数据,建立健康模式下的基于卷积神经网络的新奇检测模型;接着,将结构实时输出的特征向量输入到新奇检测模型,所得输出与健康状态的输出进行对比,并将输出和输入的欧氏距离作为新奇指标;最后,根据新奇指标的变化识别结构损伤时刻和损伤位置。数值模拟和实验室试验验证了该方法的有效性。     

石榴枯萎病的生防木霉菌株的筛选及鉴定

目的 石榴枯萎病是由甘薯长喙壳菌引起,对石榴有严重危害的土传病害。利用拮抗微生物抑制病原菌的繁殖是石榴枯萎病绿色防控的有效手段。通过筛选具有对石榴枯萎病原菌产生拮抗效果的微生物,研究其抑制菌作用,以期为石榴枯萎病生物防控提供菌种资源。方法 从石榴的根际土壤中分离出真菌,根据产孢量、生长速率、拮抗系数及平板对峙结果进行筛选,对防效较好的真菌根据形态学和分子系统学进行鉴定,通过盆栽实验评估其对石榴枯萎病的防治效果。结果 能有效抑制石榴枯萎病菌菌丝的生长的菌株T9经鉴定为非洲哈茨木霉菌（Trichoderma afroharzianum）,盆栽防治效果最高可达71.35%。结论 该菌株展现出了对石榴枯萎病的生物防治效果,具有应用价值。     

血吸虫病蔓延周期的灰色预测模型

对血吸虫病蔓延高峰期的预测具有深远的意义。本文建立一种新的灰色预测模型,对该病蔓延发展的高峰期进行预测,通过实例计算分析,预测结果正确,模型拟合精度为优。     

SEA方法及其在C~3I系统效能分析中的应用(Ⅱ)——交战模型

本文采用ＳＥＡ方法建立了Ｃ３Ｉ系统在一种典型交战环境下的系统效能模型及其分析程序,举例说明了系统效能计算结果的战术涵义。由于Ｃ３Ｉ系统所处的交战环境是千变万化的,因此采用ＳＥＡ方法建立一般交战情形下通用的Ｃ３Ｉ系统效能模型仍是十分困难的工作。然而,本文的分析过程可起到一定的示范作用。     

基于神经网络和微分对策理论的制导律

根据微分对策制导律目前面临的困境,本文尝试将神经网络引入微分对策制导律。采用ＢＰ模型,将微分对策的定量和定性分析结合起来。以导弹与飞机格斗为例,探讨其实现的可能性和优点,为将来发展基于微分对策理论的智能制导律提供了一定的思路。     

Research on secure buyer-seller watermarking protocol

A new buyer-seller watermarking protocol is proposed by applying a double encryption method and a novel mechanism of embedding a buyer＇s watermark. The protocol can effectively prevent against collusion attacks and the man in the middle attack if the third party is not trusted. Also, based on the proposed scheme for the first-hand transaction, a new buyer-reseller watermarking protocol and a formal multi-party watermarking protocol are also proposed. The proposed buyer-resell watermarking protocol only needs the original seller to provide transfer certificate and encryption-decryption service to support the second-hand transaction, and the multi-party watermarking protocol with distributed certificate authorities can overcome the difficulty in the combination of multicast mechanism with multiple unique watermarks and allow a seller to multicast the watermarked digital contents and key transaction information to n buyers. Furthermore, the idea of zero knowledge proof is also applied into the proposed scheme to allow the seller to take an effective control on the task performed by the third party.     

Compressed sensing based channel estimation for fast fading OFDM systems

A compressed sensing (CS) based channel estimation algorithm is proposed by using the delay-Doppler sparsity of the fast fading channel. A compressive basis expansion channel model with sparsity in both time and frequency domains is given. The pilots in accordance with a novel random pilot matrix in both time and frequency domains are sent to measure the delay-Doppler sparsity channel. The relatively nonzero channel coefficients are tracked by random pilots at a sampling rate significantly below the Nyquist rate. The sparsity channels are estimated from a very limited number of channel measurements by the basis pursuit algorithm. The proposed algorithm can effectively improve the channel estimation performance when the number of pilot symbols is reduced with improvement of throughput efficiency.     

Application of improved equivalent edge currents in synthetic aperture radar imaging

Target modeling and scattering function calculating are important prerequisites and groundwork for the synthetic aperture radar (SAR) imaging simulation. According to the difficult problems that normal methods cannot calculate the scattering function of electrically large object under the condition to wideband, an effective method of improved equivalent edge currents is presented and applied to SAR imaging simulation for the first time. This method improves calculating velocity and has relatively high precision. The concrete steps of applying the method are given. By way of the simulation experiment, the effectiveness of the method is verified.     

Fast motion estimation algorithm for H.264/AVC based on centered prediction

H.264/AVC video coding standard can achieve roughly half of the bit-savings over MPEG2 and MPEG4 for a given quality. However, this comes at a cost in considerably increased complexity at the encoder and thus increases the difficulty in hardware implementation. The high redundancy that exists between the successive frames of a video sequence makes it possible to achieve a high data compression ratio. Motion estimation (ME) plays an important role in motion compensated video coding. A fast motion estimation algorithm for H.264/AVC is proposed based on centered prediction, called centered prediction based fast mixed search algorithm (CPFMS). It makes use of the spatial and temporal correlation in motion vector (MV) fields and feature of all-zero blocks to accelerate the searching process. With the initialized searching point prediction, adaptive search window changing and searching direction decision, CPFMS is provided to reduce computation in block-matching process. The experimental results show that the speed of CPFMS is nearly 12 times of FS with a negligible peak signal-noise ratio (PSNR) loss. Also, the efficiency of CPFMS outperforms some popular fast algorithms such as hybrid unsymmetrical cross multi-hexagongrid search and a novel multidirectional gradient descent search evidently.     

Two-scale finite element Green’s function approximations with applications to electrostatic potential computation

<正> In this paper,a two-scale finite element approach is proposed and analyzed for approximationsof Green's function in three-dimensions.This approach is based on a two-scale finite elementspace defined,respectively,on the whole domain with size H and on some subdomain containing singularpoints with size h (h H).It is shown that this two-scale discretization approach is very efficient.In particular,the two-scale discretization approach is applied to solve Poisson-Boltzmann equationssuccessfully.