波在PTL介质中传播的旅行时反演

本文对Byun(1990)的横向各向同性介质的旅行时反演方法作了两点改进:其一是根据优化后的V_r值计算一个初始的F值,然后再根据这个初始值进行最小均方误差分析;其二是对初始值进行优化分析时,提出用测量值(或由式(4)和式(10)计算的理论值)作为实际值进行拟合,而Byun的方法是用式(11)的计算来得到一个实际值。理论模型证明:本文所述方法有一个比较宽的适应性,而Byun方法只在弱各向异性时才可以得到较精确的结果。     

Application of Wavelet Packet De-noising in Time-Frequency Analysis of the Local Wave Method

The local wave method is a very good time-frequency method for nonstationary vibration signal analysis. But the interfering noise has a big influence on the accuracy of time-frequency analysis. The wavelet packet de-noising method can eliminate the interference of noise and improve the signal-noise-ratio. This paper uses the local wave method to decompose the de-noising signal and perform a time-frequency analysis. We can get better characteristics. Finally, an example of waveletpacket denoising and a local wave time-frequency spectrum application of diesel engine surface vibration signal is put forward.     

Pure perceptual-based sequence learning.

Learning a sequence of target locations when the sequence is uncorrelated with a sequence of responses and target location is not the response dimension (pure perceptual-based sequence learning) was examined. Using probabilistic sequences of target locations, the author shows that such learning can be implicit, is unaffected by distance between target locations, and is mostly limited to first-order transition probabilities. Moreover, the mechanism underlying learning affords processing of information at anticipated target locations and appears to be attention based. Implications for hypotheses of implicit sequence learning are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

On using peak amplitude and rise time for AE source characterization

Acoustic Emission (AE) signals, which are electrical version of acoustic emissions, are usually analysed using a set of signal parameters. The major objective of signal analysis is to study the characteristics of the sources of emissions. Peak amplitude(P _a ) and rise time(R _t ) are two such parameters used for source characterization. In this paper, we theoretically investigate the efficiency ofP _a andR _t to classify and characterize AE sources by modelling the input stress pulse and transducer. Analytical expressions obtained forP _a andR _t clearly indicate their use and efficiency for source characterization. It is believed that these results may be of use to investigators in areas like control systems and signal processing also     

某实时控制系统在QNX上的具体实现

简述了QNX实时操作系统的特点，详细介绍了一实时控制系统在QNX4．25上的具体实现。     

单光子时间分辨在线谱仪系统中的接口电路

本文介绍单光子时间分辨在线谱仪系统中的多道分析器与IBM PC/XT微型计算机接口的工作原理及控制程序。     

Lyapunov‐stable discrete‐time model reference adaptive control

Discrete‐time model reference adaptive control (MRAC) is considered with both least squares and projection algorithm parameter identification. For both cases complete Lyapunov proofs are given for stability and convergence. The results extend the approach of Johansson (Int. J. Control 1989; 50 (3):859–869) to include Lyapunov stability for MRAC when the normalized projection algorithm is used for parameter identification. Copyright © 2005 John Wiley & Sons, Ltd.     

VTI介质中弹性参数地震反演方法

根据地震波在具有垂直对称轴的横向各向同性（VTI）介质中的运动学特征，应用传播时间反演方法，进行了水平层状VTI介质的地层弹性参数反演方法研究。在VTI介质中，P－P波的传播时间曲线不再是双曲线，尤其在长排列情况下，已不能用二项泰勒展式精确地反演P－P波的传播时间，用三项泰勒展式则可以达到更高精度；P－SV波的传播时间也可用三项泰勒展式表达，在中等及短排列长度时可达到一定精神。对P－P波、P－SV波的传播时间进行三项泰勒展开时，它们的系数中包含了地震波的各向异性信息及垂直速度信息，中以为地震波的弹性参数反演提供提供基础，模试验分析及江苏油田某地区的二维多波资料实际反演结果表明，在最大炮间距为1．5倍地层埋深时，可以很精确地得到三项泰勒展式的系数，应用这些系数能精确反演地层弹性参数，包括P波、S波的垂直速度和各向异性参数。图4表1参5（杜丽英摘）     

The Effect of Post-Cooking Holding Times on Sensory Assessment of Low- and High-Fat Beefburgers

ABSTRACT: The effect of post-cooking holding-time on sensory assessment of low (89 g/kg) and high (218 g/kg) fat beefburgers was assessed. Burgers were served to panelists approximately 3 or 18 min after cooking. Fat content influenced fattiness, moistness/juiciness and overall appearance (P < 0.05), overall acceptability and overall texture (P< 0.01) and tenderness and crumbliness (p<0.001). Burgers with the higher fat content had higher scores. Holding-time influenced sensory overall appearance only with lower scores at extended holding times (P < 0.01). Treatment differences were small, mostly less than one sensory scale unit. Higher lightness and yellowness values were found for burgers with higher fat contents.