Generalized adaptive notch filters with frequency debiasing for tracking of polynomial phase systems

Generalized adaptive notch filters are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. For general patterns of frequency variation the generalized adaptive notch filtering algorithms yield biased frequency estimates. We show that when system frequencies change slowly in a smooth way, the estimation bias can be substantially reduced by means of post-filtering of the frequency estimates. The modified (debiased) algorithm has better tracking capabilities than the original algorithm.     

Nonlinear parametric identification based on the criterion of minimum probability of estimation error

The importance of studies of alternative (as compared to traditional) methods of nonlinear stochastic parametric identification is demonstrated. Synthesis of a procedure of identification of the parameter, “discrete observer,” with the use of the criterion, “minimum probability of estimation error,” is proposed for the first time. A model example that demonstrates the efficiency of the proposed approach is considered.     

舰用燃气轮机框架模型的模态参数识别

本文采用一次有理正交多项式－多模态曲线合法对一舰用燃气轮机框架模型进行了实验模态分析，以Ｆｏｒｓｙｔｈｅ复合交多项式作为频响函数的理论值，用实测的频响函数建立系数矩阵，来寻找使目标函数最小的最优值，本文在ＨＰ９８２６微机上建立了建立了测试，数据采集及参数识别等系统识别软件，给出了具有工程实用意义的前五阶振动模态参数，识别结果和有限元计算相比较，令人满意。     

地层微电阻率成像测井在中原油田的应用

介绍地层微电阻率测井(FMI)技术以及它在地质构造解释、沉积学解释、裂缝识别、地层分析等方面独特的枝术优势,并详细介绍了FMI在中原油田濮深X井的实际应用,进行了应用效果分析,指出成像测井是未来油田油气勘探开发的重要技术手段。     

用过零时间法分析的中能重离子探测器望远镜

本文描述了中能重离子探测器望远镜ＮＥ１０２Ａ＋ＣｓＩ（Ｔｌ）＋ＰＭＴ采用过零时间的方法鉴别粒子，实验结果表明可清楚地分辨ｐ、ｄ、ｔ同位素和探测到的全部碎片。     

火箭弹道附近大气参数辨识系统的研究

研究了利用雷达实测数据对沿火箭飞行弹道的大气参数进行辨识和外推落点的方法，进而提出了一个对效力射诸元进行修正的方法。在此基础上，对软件系统进行了设计。最后通过仿真试验，分析了系统的准确性。     

Performance analysis of the forgetting factor RLS algorithm

An analysis is given of the performance of the standard forgetting factor recursive least squares (RLS) algorithm when used for tracking time-varying linear regression models. Three basic results are obtained: (1) the ‘P-matrix’ in the algorithm remains bounded if and only if the (time-varying) covariance matrix of the regressors is uniformly non-singular; (2) if so, the parameter tracking error covariance matrix is of the order O(μ + γ²/μ), where μ = 1 - λ, λ is the forgetting factor and γ is a quantity reflecting the speed of the parameter variations; (3) this covariance matrix can be arbitrarily well approximated (for small enough μ) by an expression that is easy to compute.     

Identification of Hammerstein systems with asymmetric dead-zone nonlinearities using canonical parameterized model

A non-iterative identification method with parameterization of the unknown dead-zone is proposed for Hammerstein systems in presence of asymmetric dead-zone nonlinearities.The canonical parameterized model which is a single expression without segmentation is utilized to describe the dead-zone,based on which a universal-type parametric model can be established to approximate the entire system.This model can be established without separating the nonlinear part from the linear part.The dead-zone parameters and the coefficients in the linear transfer function can be estimated simultaneously according to the proposed algorithm.Numerical experiments are presented to illustrate the effectiveness of the proposed scheme.     

中国民族乐器的特征值提取和分类

文章处理的是中国民族乐器的识别分类问题.提出了一种基于合适的音频特征值选择方法,该方法在基于MPEG_7标准的声学特征,在特征值的时间特性上进行改造,并加入改进后的特征值.从提取的音频特征值数据集选择K-最近邻算法.特别是对没有加入新特征值和加入新特征值后生成分类器模型的性能进行了比较.实验结果证明新特征值的加入提高了分类器的F1度量值.     

基于动态贝叶斯网络的汉语方言辨识

方言的差异性在语音层面上反映在时间序列结构的不同。传统的语音建模方法只能建立稳定的时间序列结构,而方言语音是典型的动态时变时间序列结构。为了更好地提取方言时间序列结构,文中采用动态贝叶斯网路（DBN）进行建模分析,并对DBN的构建方法进行了研究,这种结构与常用于语音识别中的隐马尔可夫模型的不同之处在于它揭示多个时间片内的节点之间的影响。文中探索了不同结构和参数对识别效果的影响。文中的研究表明动态贝叶斯网络对汉语方言的识别比传统方法要好,识别率达到了98．9％。