一种改进的查找表自适应预失真算法

峰平比高是OFDM技术的固有缺点之一,因此功率放大器的线性化是非常重要的.采用了一种改进的RASCAL算法来实现查找表自适应预失真,并使用Simulink对OFDM系统进行模块仿真.仿真结果表明:与原算法相比,改进算法不仅可进一步降低互调失真9dB,还能明显提高算法的收敛速度.     

基于BP神经网络的透明转发卫星功放预失真

研究卫星通信功放性能优化问题,传统的预失真技术通常用来补偿地面功放的非线性失真或仅考虑卫星功放的失真补偿,线性化性能有限.为解决上述问题,提出了一种适合透明转发卫星的星地一体BP神经网络预失真算法.改进算法的学习结构同时考虑了卫星地球站固态功放和透明转发卫星功放的记忆非线性特性,利用带抽头延迟的BP神经网络作为预失真器,并结合收敛速度较快的Levenberg-Marquardt算法对其权值和阈值矢量进行自适应更新.仿真结果表明,经过神经网络预失真的星座图误差矢量幅度改善了84.67％,输出信号功率谱带外再生抑制提升近了13 dB,线性化效果十分显著.     

一种高效的功放自适应预失真器设计

在对高功率放大器(HPA)进行自适应预失真过程中,为提高自适应算法运用的灵活性和自适应的收敛速率,解决幅度自适应预处理过程中对幅度过度压缩而影响功放输出功率和效率的问题,设计出一种高效的HPA自适应预失真器。该方案中幅度、相位预失真器相级联,对幅度预失真器采用间接自适应结构进行训练;相位预失真器直接对功放幅度-相位(AM-PM)特性进行辨识,然后取反得到,AM-PM特性辨识器同时又是相位预失真器,能够提高HPA自适应预失真过程中自适应算法运用的灵活性和自适应收敛速率;幅度预失真器基于正弦函数系模型,自适应预失真过程可以同时兼顾功放效率、输出功率和线性度3项重要指标。最后以M-QAM和双音信号为例进行仿真测试,验证了该方法的优势。     

改进变步长LMS自适应预失真算法研究

在数字预失真过程中,针对传统的最小均方差(LMS)自适应算法收敛速度较慢和稳态误差较大的缺点,通过分析各种改进的变步长LMS算法的优势和劣势,提出了一种组合曲线的归一化变步长LMS数字预失真算法。仿真结果表明,新算法在保证预失真效果的前提下,算法性能得到极大提升。     

一种宽带OFDM系统中记忆非线性功放的预失真方法*

针对宽带OFDM系统中功放的记忆非线性失真问题,提出一种新的频域预失真方案。该方案在频域建立具有自适应更新的幅度、相位预失真矩阵,对信号幅度和相位分别进行多次预失真处理。为提高自适应预失真收敛速度,提出一种新的预失真矩阵自适应更新算法,即Linear Convergence算法。仿真结果表明,发送信号频谱旁瓣较二维查表法压低6dB。误码率为时,该方法比二维查表法约有2dB的信噪比增益。此外,Linear Convergence更新算法收敛速度比二维查表法中的更新算法提高75%。本文提出的频域预失真方案能够有效提高收敛精度和收敛速度。     

一种求解函数优化问题的改进鲸鱼优化算法

为提高鲸鱼优化算法求解复杂函数优化问题的性能,提出一种基于自适应参数及小生境技术的改进鲸鱼优化算法。首先,引入自适应概率阈值协调算法的全局探索及局部开发能力;其次,利用自适应位置权重对鲸鱼位置更新公式进行调整,提高算法的收敛速度及寻优精度;最后,采用预选择小生境技术,避免算法出现早熟收敛的现象。通过对12个典型基准测试函数的仿真表明,改进算法的寻优精度和收敛速度较对比算法均有明显提升,证明了提出的改进策略能有效提高鲸鱼优化算法求解复杂函数优化问题的性能。     

数字基带自适应预失真算法设计及仿真实现

从算法的递归方式、收敛速度和三阶互调失真改善效果方面考虑,对各种自适应算法做了详细的分析,完成了数字基带自适应预失真算法的设计。Matlab仿真结果表明,以自适应预失真算法为核心的数字基带预失真功放较线性化之前三阶互调失真改善12dB。     

增益衰减对预失真算法的性能优化

在放大器功率增益对预失真线性化性能的影响问题的研究中,线性化技术需要更大的线性工作区域和更高的线性化性能.为提高变压器的性能,提出一种新的预失真算法优化方法,调整预失真器的应用模式,通过衰减输出功率增益扩展线性工作区域,并能实现较好的线性化性能.实验验证了上述优化方法的有效性.合理选择实际输出功率增益,利用增益衰减优化预失真算法,可以增大预失真放大器的线性工作区域,提升变压器的线性化性能.改进的优化方法为预失真技术的研究和应用提供了科学依据.     

基于粒子群神经网络线控转向故障诊断的研究

改进的自适应粒子群优化算法根据群体早熟收敛程度和个体适应值来调整惯性权重和阈值系数,以及对粒子速度与位置进行更新,该算法兼顾全局寻优和局部寻优,有效地避免早熟收敛.使用改进的自适应粒子群优化算法训练神经网络,并根据汽车线控转向系统构建故障诊断模型.实验结果表明:与传统的粒子群优化算法、遗传算法训练神经网络相比,基于改进的自适应粒子群优化算法的神经网络能够有效改善神经网络的训练效率,加快了收敛速度,提高故障模式识别的准确率.     

基于自适应模糊神经网络的功放预失真新方法

针对无线通信系统中记忆非线性功率放大器预失真结构不足和精度不高等问题,提出了一种基于模糊神经网络模型识别的双环学习结构自适应预失真方法。该方法以实数延时模糊神经网络模型为基础,采用改进的简化粒子群优化（Simplified Particle Swarm Optimization,SPSO）算法进行间接学习结构离线训练模糊神经网络来确定模型参数,作为预失真器的初值,再利用最小均方（Least Mean Square,LMS）算法进行直接学习结构在线微调整预失真器参数,拟合功放的非线性和记忆效应。该方法结构简单,收敛速度快且精度高,避免了局部最优。实验结果表明,该方案邻信道功率比经典的双环结构预失真方法约改善7 dB,功放的线性化性能明显提高,由此验证了其可行性。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.