带噪声 meaning in English
band noise
Examples
- The result shows that the efficiency and precision of prediction for clean data are satisfactory . although there are some errors in the prediction of noisy and chaotic data , the result is acceptable
实验结果表明，当数据无噪声时，预测效率与精度都非常高；在处理带噪声，并呈现混沌特性的数据时，虽有一定的误差，但预测结果还是在可以接受的范围内。 - The objective of this study is to develop approaches to correct the stripe noises and overlaps at the edge of modis imagery . the suitable geometric correction methods for modis data are studied as well . the templet interpolation algorithm is used to remove stripe noises
本研究工作采用模板插值法将噪声像元灰度值用其周边非噪声像元的灰度数据以距离的倒数为权重值进行加权平均而得到的数值替换，以此消除modis数据中的条带噪声。 - The whole processing procedure consists of three steps , i . e . , inputting the noisy ap signal to a low - pass filter , constructing a corresponding square wave according to the output of the low - pass filter and then applying it to the wave forming filter to get noise free ap signal
利用矩形波重建方法，将带噪声动作电位信号通过低通滤波器建立相应的矩形波，然后再采用计算机辅助设计法设计一个波形形成数字滤波器，使矩形波通过此滤波器后重建出纯净的细胞动作电位。 - In the course of remote sensing digital image preparation , the paper , based on many experiments , chooses histogram match for radiation correction , texture filter method for strip noise reduction , and , with tm image in 1996 as the standard , carries out geometric correction and re - sampling of multi - band combined colored image by means of binary multinomial and closest pixel , with the error of one pixel
在遥感数字图像预处理中,通过多次试验,采用纹理滤波法消除条带噪声,以96年tm影像为参考标准进行二阶多项式几何精校正和最邻近像元法重采样,误差控制在1个像元内。 - At first , the concept of perfect reconstrution of input signal from the view of filter banks and wavelet transform are introduced , . and then the analysis / synthesis system is analyzed in time domain , third , the kalman filter is explained , finally , a multirate kalman synthesis filter and multirate kalman filterirng algorithm are intruduced to achieve optimal reconstruction of the input signal with the consideraion of the subband noises . simulation results show that the performance improvement of signal reconstruction in noisy filter bank system is remarkble
本文从滤波器组和子波变换两个方面阐述了分析/综合系统及其对输入信号完全重构的概念；研究了考虑子带噪声条件下，基于滤波器组的多抽样率分析/综合成系统对输入信号的最佳重构问题。实现了用多抽样率卡尔曼综合滤波器取代常规的综合滤波器达到对输入信号的最佳重构。