Transmit Diversity Schemes for WCDMA

Previous work on transmitter antenna diversity has shown that the use of multiple transmitter antennas at the base station results in improved performance due to increase of diversity (path diversity). This happens with no bandwidth cost, even when the signal quality along several paths is poor, but the receiver estimates the channel with accuracy. This paper evaluates the effects of channel estimation errors in the performance of the schemes designated as Space-Time Transmitter Diversity (STTD) and Selective Transmitter Diversity (STD). We consider low to medium signal to noise ratios characteristic of Wideband Code Division Multiple Access (WCDMA) networks. Different fading channel models are considered for comparison between the two schemes. The improvement due to convolutional coding associated with these techniques is also evaluated.     

数字混沌扩频序列的盲估计

混沌序列具有非线性、宽带类噪声、大的码族、任意长的周期且容易产生的特性,因此在扩频通信系统中很有实用价值。本文将文献[1]中对伪随机扩频序列盲估计的方法推广应用到混沌扩频通信中,并对其不足提出了改进方法。在只知道扩频码周期而无其它任何先验知识的条件下,利用特征值分析的方法可以对数字混沌直扩序列进行盲估计,仿真实验证明了该方法的有效性。     

Bioprocess applications of model-based estimation techniques

The last decade has seen the development of a number of approaches for estimating those variables which are difficult to measure on-line in industrial process situations. Whilst a range of techniques is available, a common element is the use of process knowledge in the form of a system model. In the case of bioprocess systems, although a large range of models has been presented in the literature, their use in estimation schemes on an industrial scale has been limited. A number of reasons can be identified for their low level of utilisation. Of particular significance is the uncertainty which exists in quantifying system performance and the process-model mismatch which inevitably results. The level of ‘pre-defined model’ uncertainty, together with the knowledge gained during the course of the fermentation, serves to dictate estimator structure. The paper considers a range of estimation strategies and contrasts, through industrial applications, their performance characteristics and utility.     

European intercomparison on electron spin resonance identification of irradiated foodstuffs

The results of a co-trial organized by the Community Bureau of Reference on the use of Electron Spin Resonance spectroscopy for the identification of irradiated food in 21 laboratories are presented. The trial was qualitative on beef and trout bones, sardine scales, pistachio nut shells, dried grapes, and papaya, and quantitative on poultry bones. There was no difficulty in identifying irradiated meat bones, dried grapes, and papaya. In the case of fish bones there is a need for further kinetic study on different species. Identification of irradiation in pistachio nuts is more complicated and additional research is needed before further trials. All laboratories were able to distinguish between chicken bones irradiated at 1 to 3 kGy or 7 to 10 kGy although there was a partial overlap between the results.     

Two- or three-stage least squares?

Two elements enter the choice between 2 and 3SLS for full-system estimation: statistical efficiency and computational cost. 2SLS always has the computational edge, but 3SLS can be more efficient, a relative advantage that increases with the strength of the interrelations among the error terms. A measure of these interrelations is thus helpful in making the choice, and, when there are only two equations, this has suggested using a high pairwise error correlation as an indicator of when to use 3SLS. In larger systems of equations, however, these pairwise correlations can remain small even though more general interrelations give 3SLS the relative advantage. More general indicators are therefore needed, and this paper suggests three such and demonstrates their efficacy.Professor of Economics, Boston College, and Principal Research Associate, Center for Computational Research in Economics and Management Science, MIT. All computation was done on the TROLL system at MIT. My thanks go to Josh Charap for his able research assistance. This research was sponsored in part by the National Science Foundation under grant #IST-8420614.     

Improved Estimates for the Accuracy of Small Disjuncts

Learning systems often describe a target class as a disjunction of conjunctions of conditions. Recent work has noted that small disjuncts, i.e., those supported by few training examples, typically have poor predictive accuracy. One model of this accuracy is provided by the Bayes-Laplace formula based on the number of training examples covered by the disjunct and the number of them belonging to the target class. However, experiments show that small disjuncts associated with target classes of different relative frequencies tend to have different error rates. This note defines the context of a disjunct as the set of training examples that fail to satisfy at most one of its conditions. An empirical adaptation of the Bayes-Laplace formula is presented that also makes use of the relative frequency of the target class in this context. Trials are reported comparing the performance of the original formula and the adaptation in six learning tasks.     

Spectral estimation of video signals

Spectrum analyzers are ubiquitous in laboratory work concerning one dimensional signals. This is because linear operators are best examined in the frequency domain. Linear operators, such as linear filters, DCT coders, line shufflers, etc., dominate also the video systems scenario. Their frequency domain study is as appropriate and informative as it is in the case of their one-dimensional counterparts. This paper considers the problems associated with the introduction of two well-known spectral estimation techniques, the periodogram and AR estimates, to the context of television signals. The potential for application of spectral estimation to video problems is exemplified by a number of applications related to the fields of enhanced quality television and HDTV. Special attention is paid to the computational aspects, whose effective solution conditions the practical applicability of the proposed spectral estimation techniques.R. Rinaldo is currently at the Department of Electrical and Computer Engineering of the University of California, Berkeley.     

非平稳ARMA信号自校正滤波器及其应用

本文处理带白色观测噪声的非平稳ARMA信号估计问题.应用状态空间方法和现代时 间序列分析方法[1],基于ARMA新息模型,提出了非平稳ARMA信号自校正滤波器,推广了 Hagander和Wittenmafk的结果[2],并给出了在雷达跟踪系统和检测数据数字滤波方面的应 用.仿真结果说明了本文结果的实用性和有效性.