Parameter determination for a generalized fuzzy model

This paper underlines a way to evolve a generalized fuzzy model (GFM), using the interpolation of CRI and TS models in their consequent parts of fuzzy rules. The GFM possesses the index of fuzziness of CRI model and the local model of the TS model. The parameters of the GFM are estimated by a two-step process. The consequent part of fuzzy rules is reformulated to suit the LSE framework for estimating the associated parameters. By assuming Generalized Gaussian membership function for the premise parts, Gradient descent technique is used to update its parameters. The performance of two classes of GFM has been tested on two systems and it is shown that class II GFM is the best out of all the fuzzy models tested.     

Optimal rapid multidisciplinary response networks: RAPIDDISK

The role of uncertainty in information rich design systems is critical to the development of advanced propulsion systems. Future turbine engines would have lower lifetime operating costs similar to current evolving automotive systems. Detailed multi-physics models (thermo-fluid, structural and mechanical systems) and an operational environment are enablers of rapid correction and model-based predictive analyses. Bayesian machine learning paradigms are developed to identify the behavior of turbo-machinery components for preliminary design. The embedded models approach enables systematic evolution from individual components level to the advanced engine. The embedded models approach enables systematic evolution from individual components level to the advanced engine. A rapid response strategy is proposed, for design of turbine disks by using multidisciplinary optimization and neural networks. iSIGHT optimization software is interfaced with ANSYS to find optimum designs for a given set of design boundary conditions (rpm, live rim load, thermals, etc.). The optimum designs obtained from iSIGHT for different set of design conditions are used for machine learning and design knowledge recognition using the neural network technique. The trained network is used to predict responses for design boundary conditions. Responses predicted by the neural network are validated using ANSYS. Discrete design points are chosen from the wide design space of turbine disks. A hierarchical neural network approach provides an ability to quickly train the network and predict responses (weight, stresses, burst margin, etc.) for applied design conditions. This basic building process involves four steps starting from identifying design boundary conditions to the prediction of design shape for the disk. Sensitivity-based scaling rules are developed, to accommodate different materials for the disk. The technique is developed in RAPIDDISK, which provides an optimal preliminary shape and design attributes for a turbine disk.     

Adaptive Transmit Diversity with Quadrant Phase Constraining Feedback

An adaptive transmit diversity scheme with quadrant phase constraining feedback is proposed in this paper. With simple linear operations at both transmitter and receiver, the proposed algorithm can achieve better system performances with only 2M−2 bits of feedback information for systems with M transmit antennas. Theoretical performance bounds of the proposed transmit diversity scheme are derived. Simulation examples and theoretical analyses show that the proposed transmit diversity scheme outperforms not only the conventional open-loop transmit diversity techniques, but also some closed-loop transmit diversity techniques with more information transmitted in the feedback channel.     

Signal Space Diversity Augmented Space Time Block Coded Communication System

In this paper we propose the combination of space-time diversity techniques and signal space diversity, in order to improve communication system performance. Specifically, we use prior knowledge of the channel behavior to design a mapping algorithm to generate a two-dimensional constellation with the same number of symbols as MPSK constellations currently used in coherent space time block coding applications, to demonstrate that superior performance can be achieved. This is accomplished by constructing a two-dimensional map that results from the minimization of the estimated symbol error probability when transmission occurs in a fading environment. System performance for each each mapping is assessed in quasi-static Rayleigh fading channels.     

提高系统容错性的软件技术

计算机在现代军事装备中的作用日益重要,他在装备研制中所占工作量的比例越来越大。由于军用计算机的工作环境一般较恶劣,常容易引起计算机电源不稳定等问题,因此,如何保证计算机系统的可靠性已成为影响装备质量的关键因素。本文综合分析嵌入式系统中提高计算机容错性的常用技术,并给出采用软件恢复块实现掉电恢复的实例。     

手机用TFT-LCD驱动控制芯片电源模块设计

电源模块是TFT-LCD驱动控制芯片内置模拟电路的一个重要组成部分,其性能直接影响着芯片的功耗以及彩屏手机的显示画质。文章从TFT-LCD的驱动原理出发,提出了一种低功耗、易调节的电源模块设计思想,所产生的电压值可实现编程控制。用Hspice对采用0.25μmCMOS工艺设计的电路进行仿真表明,系统在启动200ms后能够生成稳定、正确的驱动电源电压,其静态功耗小于2mW。     

基于ForCES协议的软件集群路由器模型研究

文章提出了软件集群路由器的参考模型。且对软件集群路由器模型的物理结构、逻辑结构和流量场景进行了深入的分析。通过一个简单的模型实例，提出了总体设计的方案。     

RC6中不同固定循环移位对差分分析的影响

论文首先讨论了不同的固定循环移位对RC6-I(用恒等函数代替平方函数的变体)的影响,从理论上证明了当固定循环移位的取值为lgw时,RC6-I抗差分分析的效果最好。     

构造短码长不规则LDPC码

在给定长度和度数分布对情况下,不规则短码长LDPC码的性能差别很大。本文给出了一种低复杂度的基于树的贪婪搜索算法(GTS),此算法通过调整校验矩阵中环的分布情况,尽量减少短长度环,获得最大的平均最小环,从而构造性能很好的短码长不规则LDPC码。     

马2断块油藏形成的控制因素及勘探建议

通过对马2断块地层沉积相、构造及油藏类型的分析介绍，参考马2断油藏储层基本特征、油藏开发动态、油气显示和数值模拟最新研究结果，根据马2断块区域石油地质条件，对马2断块油藏形成的控制因素进行了深入分析、研究，明确提出“储集沙全及断裂系统的发育和断裂性质是该区块油藏形成的主要控制因素”的观点。并结合剩余油分布特点，提出了进一步勘探的建议，为马2断块油藏的控潜和勘探目标的选择指明了方向。