ass日本风韵熟妇pics男人扒开女人屁屁桶到爽|扒开胸露出奶头亲吻视频|邻居少妇的诱惑|人人妻在线播放|日日摸夜夜摸狠狠摸婷婷|制服 丝袜 人妻|激情熟妇中文字幕|看黄色欧美特一级|日本av人妻系列|高潮对白av,丰满岳妇乱熟妇之荡,日本丰满熟妇乱又伦,日韩欧美一区二区三区在线

基于BBSRIA的測(cè)量系統(tǒng)動(dòng)態(tài)精度損失分解與溯源
CSTR:
作者:
作者單位:

作者簡(jiǎn)介:

通訊作者:

中圖分類號(hào):

基金項(xiàng)目:


Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 圖/表
  • |
  • 訪問統(tǒng)計(jì)
  • |
  • 參考文獻(xiàn)
  • |
  • 相似文獻(xiàn)
  • |
  • 引證文獻(xiàn)
  • |
  • 資源附件
  • |
  • 文章評(píng)論
    摘要:

    利用單子帶信號(hào)重構(gòu)改進(jìn)算法在信號(hào)分解中的優(yōu)勢(shì),,實(shí)現(xiàn)了對(duì)測(cè)量系統(tǒng)動(dòng)態(tài)精度損失信號(hào)的有效分解,得到測(cè)量系統(tǒng)各主要結(jié)構(gòu)單元的頻率成分,,在此基礎(chǔ)上利用神經(jīng)網(wǎng)絡(luò)所具有的輸入到輸出之間的非線性映射能力完成求解各頻率成分所包含的未知參數(shù),。同時(shí)根據(jù)測(cè)量系統(tǒng)內(nèi)部各結(jié)構(gòu)單元的誤差特性完成分解信號(hào)的溯源,。實(shí)驗(yàn)結(jié)果表明利用單子帶信號(hào)重構(gòu)改進(jìn)算法可以實(shí)現(xiàn)精度損失信號(hào)的可靠分解與溯源,。

    Abstract:

    Based on wholesystem dynamic error modeling method and theory, the theory and method of dynamic accuracy loss decomposition and tracing were studied. Using bill belt signal reconstruction improvement arithmetic, the accuracy loss signal of emulation system was decomposed, its frequency components of the system’s main insider structural units was obtained. Then by using non-linear mapping ability from input to output of BP NN, model parameters of the built accuracy loss function model of each insider cells were estimated, and the signals decomposing were achieved. Using the error characteristic of each insider structural units and the systemic whole error model, the signals tracing were achieved. Experimental result indicated that by using BBSRIA (bill belt signal reconstruction improvement arithmetic), reliably decompose and tracing of the accuracy loss signal could be achieved. 

    參考文獻(xiàn)
    相似文獻(xiàn)
    引證文獻(xiàn)
引用本文

蔣敏蘭,汪曉東.基于BBSRIA的測(cè)量系統(tǒng)動(dòng)態(tài)精度損失分解與溯源[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2008,39(10):183-186.[J]. Transactions of the Chinese Society for Agricultural Machinery,2008,39(10):183-186.

復(fù)制
分享
文章指標(biāo)
  • 點(diǎn)擊次數(shù):
  • 下載次數(shù):
  • HTML閱讀次數(shù):
  • 引用次數(shù):
歷史
  • 收稿日期:
  • 最后修改日期:
  • 錄用日期:
  • 在線發(fā)布日期:
  • 出版日期:
文章二維碼