Efficient and Provably Secure Multi-Recipient Signcryption from Bilinear Pairings

0 Introduction Confidentiality, integrity, non-repudiation and au- thentication are the important requirements for many cryptographic applications. A traditional approach to achieve these requirements is to sign-then-encrypt the message. Signcryption, fir…     

大功率P沟道VDMOS器件设计与工艺仿真

作为现代电力电子核心器件之一的P沟道VDMOS(vertical double-diffuse,MOS)器件,一直以来由于应用领域狭窄而并未得到足够的研究。以P沟道VDMOS器件为研究对象,为一款击穿电压超过-200V的P沟道VDMOS设计了有源区的元胞结构及复合耐压终端结构,并开发了一套完整的P沟道VDMOS专用非自对准工艺流程。最后通过仿真得到器件的击穿电压超过-200V,阈值电压为-2.78V,完全满足了设计要求,也为下一步流片提供了有益的参考。     

基于最小均方误差的多用户MIMO系统下行链路预编码

针对多输入多输出(multple input multiple output,MIMO)系统下行链路的迫零预编码方法在块对角化的基础上追求最大化系统和容量,而并未考虑接收信号的均方误差,从接收信号具有最小均方误差的角度设计了多用户MIMO系统的下行链路预编码的方案,称为块对角化最小均方误差方案。理论分析和仿真结果表明,该方案相较于迫零算法具有较小的接收信号均方误差及较好的误码率性能,并且保持了迫零算法绝大部分的系统和容量,它在系统误码率与和容量方面提供了一种较好的折中。     

Adaptive output-feedback control for MIMO nonlinear systems with time-varying delays using neural networks

An adaptive neural network output-feedback regulation approach is proposed for a class of multi-input-multi-output nonlinear time-varying delayed systems. Both the designed observer and controller are free from time delays. Different from the existing results, this paper need not the assumption that the upper bounding functions of time-delay terms are known, and only a neural network is employed to compensate for all the upper bounding functions of time-delay terms, so the designed controller procedure is more simplified. In addition, the resulting closed-loop system is proved to be semi-globally ultimately uniformly bounded, and the output regulation error converges to a small residual set around the origin. Two simulation examples are provided to verify the effectiveness of control scheme.     

宽间隔跳频伪码序列设计及其性能检验

介绍了跳频伪码序列的产生，进行了非线性变换来增加保密性，宽间隔处理完成后，组建跳频系统，并对此 组网系统进行了一系列的指标验证，性能检测，得出了由RS码与修正的对偶频带法结合的方法产生的宽间隔调频 序列的性能是比较优良的，符合跳频组网的性能指标的结论。     

Output-feedback adaptive stochastic nonlinear stabilization using neural networks

For the first time, an adaptive backstepping neural network control approach is extended to a class of stochastic nonlinear output-feedback systems. Different from the existing results, the nonlinear terms are assumed to be completely unknown and only a neural network is employed to compensate for all unknown nonlinear functions so that the controller design is more simplified. Based on stochastic LaSalle theorem, the resulted closed-loop system is proved to be globally asymptotically stable in probability....     

Hooke and Jeeves algorithm for linear support vector machine

Coordinate descent method is a unconstrained optimization technique. When it is applied to support vector machine (SVM), at each step the method updates one component of w by solving a one-variable sub-problem while fixing other components. All components of w update after one iteration. Then go to next iteration. Though the method converges and converges fast in the beginning, it converges slow for final convergence. To improve the speed of final convergence of coordinate descent method, Hooke and Jeeves a...