Nonlinear and Variable Structure Excitation Controller for Power System Stability

A new nonlinear variable structure excitation controller is proposed. Its design combines the differential geometry theory and the variable structure controlling theory. The mathematical model in the form of ＂an affme nonlinear system＂ is set up for the control of a large-scale power system. The static and dynamic performances of the nonlinear variable structure controller are simulated. The response of system with the controller proposed is compared to that of the nonlinear optimal controller when the system is subjected to a variety of disturbances. Simulation results show that the nonlinear variable structure excitation controller gives more satisfactorily static and dynamic performance and better robustness.     

An Adaptive Joint Source/Channel Coding Using Error Correcting Arithmetic Codes

An approximately optimal adaptive arithmetic coding (AC) system using a forbidden symbol (FS) over noisy channels was proposed which allows one to jointly and adaptively design the source decoding and channel correcting in a single process, with superior performance compared with traditional separated techniques. The concept of adaptiveness is applied not only to the source model but also to the amount of coding redundancy. In addition, an improved branch metric computing algorithm and a faster sequential searching algorithm compared with the system proposed by Grangetto were proposed. The proposed system is tested in the case of image transmission over the AWGN channel, and compared with traditional separated system in terms of packet error rate and complexity. Both hard and soft decoding were taken into account.     

A New Full Bridge High Intensity Focused Ultrasound Power System with Harmonic Cancellation

The feasibility of a new full bridge high intensity focused ultrasound(HIFU) amplifier system with harmonic cancellation is evaluated in this study. Harmonic cancellation technique is applied to these power amplifiers, which can eliminate the 3rd harmonic and all even harmonics. Since this technique requires two channels of phase signal to control one channel of power amplifier, the signal generator is required to double its output. The transducer array proposed in this study has 100 elements. So we choose an FPGA chip to generate 200 driving signals, and each channel has a phase resolution of 2ns, less than 1°. The phase signal from the FPGA meets the requirement of driving the power amplifiers. The output waveform of one channel of power amplifier(voltage across the transducer) is evaluated, and shows fewer harmonic components.     

The Cooperative Multi-agent Learning with Random Reward Values

This paper investigated how to learn the optimal action policies in cooperative multi-agent systems if the agents‘ rewards are random variables, and proposed a general two-stage learning algorithm for cooperative multiagent decision processes. The algorithm first calculates the averaged immediate rewards, and considers these learned rewards as the agents‘ immediate action rewards to learn the optimal action policies. It is proved that the learning algorithm can find the optimal policies in stochastic environment. Extending the algorithm to stochastic Markov decision processes was also discussed.     

A probability approach to anomaly detection with twin support vector machines

AbstractClassification of intrusion attacks and normal network flow is a critical and challenging issue in network security study. Many intelligent intrusion detection models are proposed, but their performances and efficiencies are not satisfied to real computer networks. This paper presents a novel effective intrusion detection system based on statistic reference model and twin support vector machines (TWSVMs). Moreover, a network flow feature selection procedure has been studied and implemented with TWSVMs. The performances of proposed system are evaluated through using the fifth international conference on knowledge discovery and data mining in 1999 (KDD’99) data set collected at MIT’s Lincoln Labs and the results indicate that the proposed system is more efficient and effective than conventional support vector machines (SVMs) and TWSVMs.     

Parallel Distributed Implementation of Truss Optimization on a Local Area Network

A two-level optimization method for the design of complex truss and parallel distributed implementation on a LAN is presented using parallel virtual machine (PVM) for Win 32 as message passing between PCs. The volumes of truss are minimized by decomposing the original optimization problem into a number of bar optimization problems executed concurrently and a coordinate optimization problem, subject to constraints on nodal displacements, and stresses, buckling and crippling of bars, etc. The system sensitivity analysis that derives the partial derivatives of displacements and stresses with respect to areas are also performed in parallel so as to shorten the analysis time. The convergence and the speedup performances as well as parallel computing efficiency of the method are investigated by the optimization examples of a 52-bar planar truss and a 3 126-bar three-diraensional truss. The results show that the ideal speedup is obtained in the cases of 2 PCs for the 3 126-bar space truss optimization, while no speedup is observed for the 52-bar truss. It is concluded that (1) the parallel distributed algorithm proposed is efficient on the PC-based LAN for the coarsegrained large optimization problem; (2) to get a high speedup, the problem granularity should match with the network granularity;and (3) the larger the problem size is, the higher the parallel efficiency is.     

Wavelet De-noising of Speech Using Singular Spectrum Analysis for Decomposition Level Selection

The problem of speech enhancement using threshold de-noising in wavelet domain was considered.The appropriate decomposition level is another key factor pertinent to de-noising performance.This paper proposed a new wavelet-based de-noising scheme that can improve the enhancement performance significantly in the presence of additive white Gaussian noise.The proposed algorithm can adaptively select the optimal decomposition level of wavelet transformation according to the characteristics of noisy speech.The experimental results demonstrate that this proposed algorithm outperforms the classical wavelet-based de-noising method and effectively improves the practicability of this kind of techniques.     

An Improved Group Space-Time Block Code Through Constellation Rotation

A new improved group space-time block code （G-STBC） based on constellation rotation for four transmit antennas was proposed. In comparison with the traditional G-STBC coding scheme, the proposed space-time code has longer code length and adopts proper rotation-based symbols, which can increase the minimum distance of space-time codes and thereby improve code gain and achieve full diversity performance. The simulation results verify that the proposed group space-time code can achieve better bit error performance than both the traditional group space-time code and other quasi-orthogonal space-time codes. Compared with Ma＇s full diversity full rate （FDFR） codes, the proposed space-time code also can achieve the same excellent error performance. Furthermore, the design of the new space-time code gives another new and simple method to construct space-time codes with full diversity and high rate in case that it is not easy to design the traditional FDFR space-time codes.     

Optimal Genetic View Selection Algorithm for Data Warehouse

To efficiently solve the materialized view selection problem, an optimal genetic algorithm of how to select a set of views to be materialized is proposed so as to achieve both good query performance and low view maintenance cost under a storage space constraint. First, a pre-processing algorithm based on the maximum benefit per unit space is used to generate initial solutions. Then, the initial solutions are improved by the genetic algorithm having the mixture of optimal strategies. Furthermore, the generated infeasible solutions during the evolution process are repaired by loss function. The experimental results show that the proposed algorithm outperforms the heuristic algorithm and canonical genetic algorithm in finding optimal solutions.     

Soft-Sensing Method with Online Correction Based on Semi-Supervised Learning

Soft sensing has been widely used in chemical industry to build an online monitor of the variables which are unmeasurable online or measurable online but with a high cost. One inherent difficulty is insufficiency of the training samples because the labeled data are limited. Besides, the traditional soft-sensing structure has no online correction mechanism. The forecasting result may be incorrect if the working condition is changed. In this work, a semi-supervised learning(SSL) method is proposed to build the soft-sensing model by use of the unlabeled data. Meanwhile, an online correction mechanism is proposed to establish a soft-sensing approach. The mechanism estimates the input variables at each step by a prediction model and calibrates the output variables by a compensation model. The experimental results show that the proposed method has better prediction accuracy and generalization ability than other approaches.     

STC-OFDM系统的post-IDFT多波束形成技术

提出了适用于空时编码-正交频分复用(OFDM)系统的后-逆离散傅立叶变换(post-IDFT)多波束形成技术.该技术通过对空频信道相关矩阵进行特征分解获得多个特征模式,再利用空时分组码(STBC)各发射分支信号的正交性使OFDM系统形成多个post-IDFT波束.接收端根据STBC传输矩阵的正交性对多波束解码.系统获得的空间分集增益为空频信道相关矩阵的特征值之和,最大空间分集增益与子载波波束形成方案相同,误码率比STC-OFDM的低.该技术将复杂度降低到子载波波束形成方案的1/S(S为OFDM系统的子载波数目),而且当波束维数(m)小于发射天线数目(M)时,可进一步减少M-m个IDFT模块     

Switching between antenna subset selection and quasi-orthogonal space-time block code in presence of correlation

We address the problem of adaptive modulation and coding scheme (AMCS) for a multi-input multioutput (MIMO) system in presence of time-varying transmitting correlation. Antenna subset selection and quasiorthogonal space-time block code (QOSTBC) have different error performances with different signal-to-noise ratios (SNRs) and in different spatial correlation scenarios. The error performance can be improved by selecting an appropriate transmission scheme to adapt to various channel conditions. The maximum distance criterion is the simplest and very effective algorithm for the antenna subset selection without needs of complex calculation and channel state information at transmitter (CSIT). The minimum error performance criteria and the simplified linear decision strategy are developed for constant transmission rate traffic to select the optimal transmission scheme. It can dramatically decrease algorithm complexity for obtaining error probability according to the known quantities comparing with using instant CSIT. Simulation results show that, remarkable performances including low SNR and weak spatial correlation at the expense of simple calculation and almost no bandwidth loss by adopting AMCS can be achieved. The proposed AMCS improves robustness of slowly varying spatial correlated channels.     

鱼雷声呐空时自适应混响抑制方法

对于窄带信号情形,空时自适应方法具有良好的混响抑制性能.文中通过发射波形设计,设计了既具有窄带信号的低多普勒容限,又具有频率分集特性的多频信号,使得空时自适应方法对于具有准宽带特性的信号也具有良好的混响抑制能力,从而提高主动声自导鱼雷检测性能.     

一种改进的GSM/GPRS网络信道分配策略

在对GSM／GPRS(global system for mobile communications／general packet radio service)蜂窝系统现有典型信道分配策略FRA(fixed resource allocation)和DRA(dynamical resource allocation)及其排队策略进行分析的基础上，提出了基于DRA的改进策略DMC—DRA(dynamical minimum channels of packets for DRA)．新策略能动态改变GPRS包下限信道数，在FRA和DRA之间折衷，提高信道利用率、包传输时间、呼叫阻塞率等综合性能．     

基于模块化仿真的共享汽车联合调度优化

运营商在调度车辆时单独采用员工或顾客调度策略均难以有效解决共享汽车分布不均衡导致的盈利难问题.为此，在传统时空网络基础上，考虑道路拥堵和用车需求随时间变化对运营的影响，基于C#语言和O2DES(object-oriented discrete event simulation)离散事件仿真框架，建立由模块化站点和路段模型组成、可高效率运行的共享汽车仿真系统；在此基础上，提出一个以运营商日均净收益最大化为目标，联合决策车辆库存量阈值和行程定价的仿真优化模型，并为解决随机环境下的全局优化问题，设计了EGA-OCBA (elitist genetic algorithm with optimal computing budget allocation)算法；最后，以成都市的5个共享汽车站点为例，验证了仿真优化模型的有效性.仿真优化结果表明：在相同车队规模下，与采用固定价格的顾客调度策略相比，联合策略可使日均净收益提升10.37%～162.30%；与单独的员工调度策略相比，联合策略可使日均净收益提升15.34%.     

基于公交时空过程的城市时空可达性计算方法

交通系统的本质目标是为了提高个体的可达性.已有的基于时空维的时空可达 性计算方法忽略交通模式选择的约束,以及对于出行时间没有确切的概念,因此,提出了 基于公交时空过程的城市时空可达性计算方法.该方法以特定的公交出行时空约束作为 效用函数,从历史公交时空过程中获取公交出行时间,对于出行时间的计算更具可操作 性;并且,其考虑特定的时空约束下个体参与活动的效用值,显得更加严谨.同时该方法将 特定的交通出行方式作为一种出行的时空约束,更加符合现实情况.最终,以广州市公交 系统为研究对象,运用该方法计算特定时空约束下个体出行的城市时空可达性.结果表明 该方法具有有效性和可操作性.     

物体表面重建轮廓拼接的改进遗传算法

为解决物体表面重建中的轮廓拼接问题，将其转化为在有向图中寻求最优路径问题．提出了基于遗传算法的适用各种目标函数的轮廓拼接算法，其中对初始种群的产生、交叉算子和变异算子等做了改进，以确保产生的个体均能代表有效解．算例模拟结果表明，该算法简单可行，在优化性能、收敛速度及鲁棒性等方面优于模拟退火算法．     

Residual Chart with Hidden Markov Model to Monitoring the Auto-Correlated Processes

Autocorrelations exist in real production extensively, and special statistical tools are needed for process monitoring. Residual charts based on autoregressive integrated moving average (ARIMA) models are typically used. However, ARIMA models need a quite amount of experience, which sometimes causes inconveniences in the implementation. With a good performance under less experience or even none, hidden Markov models (HMMs) were proposed. Since ARIMA models have many different performances in positive and negative autocorrelations, it is interesting and essential to study how HMMs affect the performances of residual charts in opposite autocorrelations, which has not been studied yet. Therefore, we extend HMMs to negatively auto-correlated observations. The cross-validation method is used to select the relatively optimal state number. The experiment results show that HMMs are more stable than Auto-Regressive of order one (AR(1) models) in both cases of positive and negative autocorrelations. For detecting abnormalities, the performance of HMMs approach is much better than AR(1) models under positive autocorrelations while under negative autocorrelations both methods have similar performances.     

基于结构性能的PC连续刚构桥损伤分析

为探讨PC(预应力混凝土)连续刚构桥开裂及下挠的原因,提出了基于结构性能的损伤分析方法.该方法立足于结构性能的客观表象,把对可能造成损伤的诸多因素对结构性能水平的影响分析作为主要手段;通过对大量理论计算与试验数据的对比分析,以基于实桥检测和荷载试验的性能水平参数作为评判依据,找出造成损伤的因素及其达到的程度,同时获得损伤桥梁较为真实的性能水平,作为可靠性评估和加固设计的依据.通过对一座跨径160 m的PC连续刚构桥基于性能的损伤分析,结果表明:用该方法,结构挠度的校验系数可达0.9.