基于网络的智能辅导模式研究与系统设计

针对目前辅导行业的现状,为解决课后辅导的自动化、实时化的问题,分析了学生课后学习掌握知识的过程,提出了一个基于学生课后学习规律的辅导模型,建立了面向问题的多层面知识辅导新模式,构建了基于此模式的网络智能家教系统的框架结构。该系统采用基于知识的自动推理技术使得推理过程得以完整保存来分析后续的多层面辅导信息,采用资源模型分解知识粒度保证抽象度,采用网络服务模式满足用户的实时使用。以学生提出的几何问题为实例,展示了多层面辅导过程,实验结果表明了该模式和系统设计的可行性。     

Performance Analysis of Gradient Neural Network Exploited for Online Time-Varying Matrix Inversion

This technical note presents theoretical analysis and simulation results on the performance of a classic gradient neural network (GNN), which was designed originally for constant matrix inversion but is now exploited for time-varying matrix inversion. Compared to the constant matrix-inversion case, the gradient neural network inverting a time-varying matrix could only approximately approach its time-varying theoretical inverse, instead of converging exactly. In other words, the steady-state error between the GNN solution and the theoretical/exact inverse does not vanish to zero. In this technical note, the upper bound of such an error is estimated firstly. The global exponential convergence rate is then analyzed for such a Hopfield-type neural network when approaching the bound error. Computer-simulation results finally substantiate the performance analysis of this gradient neural network exploited to invert online time-varying matrices.     

Continuous-variable quantum homomorphic signature

Quantum cryptography is believed to be unconditionally secure because its security is ensured by physical laws rather than computational complexity. According to spectrum characteristic, quantum information can be classified into two categories, namely discrete variables and continuous variables. Continuous-variable quantum protocols have gained much attention for their ability to transmit more information with lower cost. To verify the identities of different data sources in a quantum network, we propose a continuous-variable quantum homomorphic signature scheme. It is based on continuous-variable entanglement swapping and provides additive and subtractive homomorphism. Security analysis shows the proposed scheme is secure against replay, forgery and repudiation. Even under nonideal conditions, it supports effective verification within a certain verification threshold.     

Hybrid filtering for linear systems with non-Gaussian disturbances

This paper is concerned with hybrid filtering of a non-Gaussian system coupled by a hidden switching process. An optimal control approach is used to derive a finite-dimensional recursive filter that is optimal in the sense of the most probable trajectory (MPT) estimate. An approximate scheme is obtained when the probability distribution of the switching process converges to a limiting distribution, which is often easier to obtain. Numerical examples are considered, and computational experiments are reported. In these examples, our schemes outperform popular filtering schemes available in the literature     

医院超声图象管理系统的设计与实现

介绍了医院超声图象管理系统的功能和特点,并阐述了其关键技术。     

一种低压低功耗共源共栅带隙基准电压源的实现

提出了一种低压低功耗的带隙基准电压源电路,设计基于0.5μm2P3M BiCMOS Process,并使用了低压共源共栅电流镜结构减少了对电源电压的依赖,消除了精度与余度之间的矛盾,并用HL50S-S3.1S.lib库文件用HSPICE进行了仿真,其电源抑制比PSRR大约为-78.9dB。     

Initial high beta operation of the HBT-EP Tokamak

HBT-EP is a new research tokamak designed and built to investigate passive and active feedback techniques to control MHD instabilities. In particular, HBT-EP will be able to test techniques to control fast MHD instabilities occurring at high Troyon-normalized beta, _N Ba/I_p [Tm/MA], since it is equipped with a thick, close-fitting, and adjustable conducting shell. The major goals of the initial operation of HBT-EP have been the achievement of high beta operation (_N 3) using only ohmic heating and the observation of MHD instabilities. By using a unique fast startup technique, we have successfully achieved these goals. A variety of MHD phenomena were observed during the high beta operation of HBT-EP. At modest beta (_N 2), discharges have been maintained for more than 10 msec, and these discharges exhibit saturated resistive instabilities. When _N approaches 3, major disruptions occur preceded by oscillating, growing precursors. During start-up, one or more minor disruptions are usually observed. A 1-D transport code has been used to simulate the evolution of the current profile, and these early minor instabilities are predicted to be double tearing modes. The simulation also reproduces the observed high beta operation when saturated neo-Alcator energy confinement scaling is assumed.     

Application of a multilayer decision tree in computer recognition of chinese characters

A multistage classifier with general tree structure has been developed to recognize a large number of Chinese characters. A simple and efficient method of classifying the characters was achieved by choosing the best feature at each stage of the tree. The features used are Walsh coefficients obtained from two profiles of a character projected onto the X-Y orthogonal axes. Some algorithms for aligning the characters were compared and one of them was adopted in this recognition scheme. A high recognition rate of about 99.5 percent was obtained in an experiment with more than 3000 different Chinese characters.