期刊文献+

一类适用于陀螺随机漂移预报的非线性模型 被引量:3

A Non-Linear Model Suitable for Gyro Random Drift Forecast
下载PDF
导出
摘要 本文针对陀螺随机漂移的弱非线性和非平稳性,提出了一种多项式NAR模型及其辨识方法。对陀螺随机漂移测试数据的仿真表明,该模型能很好地用来预报陀螺随机漂移。 To counter weak non-linear and nonstationary characteristics of gyro random drift,a polynomial NAR model and its identification is proposed in this paper. Digital simulations have shown that the model can be applied to forecast gyro random drift well.
机构地区 东南大学
出处 《中国惯性技术学报》 EI CSCD 1993年第1期37-41,共5页 Journal of Chinese Inertial Technology
  • 相关文献

同被引文献13

  • 1LIU Hui,TIAN Hongqi,LI Yanfei.Comparison of two new ARIMA-ANN and ARIMA-Kalman hybrid methods for wind speed prediction[J].Applied Energy,2012,98(10):415-424.
  • 2LOUKA P.Improvements in wind speed forecasting for wind power prediction purposes using Kalman filtering[J].Journal of Wind Engineering and Industrial Aerodynamics,2008,96(12):2348-2362.
  • 3CAO Qing,EWING B T,THOMPSON M A.Forecasting wind speed with recurrent neural networks[J].European Journal of Operational Research,2012,221(1):148-154.
  • 4GUO Zhenhai,WU Jie,LU Haiyan.A case study on a hybrid wind speed forecasting method using BP neural network[J].Knowledge Based Systems,2011,24(7):1048-1056.
  • 5YASSIN I M,ZABIDI A,SALLEH M K M,et al.Malaysian tourism interest forecasting using nonlinear autoregressive(NAR)model[C]//20131EEE 3rd International Conference on System Engineering and Technology,2013:32-36.
  • 6KADIR S N,TAHIR N M,YASSIN I M,et.al.Malaysian tourism interest forecasting using nonlinear auto-regressive moving average(NARMA)model[C]//2014IEEE Symposium on Wireless Technology and Applications,2014:193-198.
  • 7URTEAGA I,DJURIC P M.Estimation of ARMA state processes by particle filtering[C]//2014IEEE International Conference on Acoustics,Speech and Signal Processing,2014:8033-8037.
  • 8LOPES H,TSAY R S.Particle filters and bayesian inference In financial econometrics[J].Journal of Forecasting,2011,30(1):168-209.
  • 9侯代文,殷福亮.非线性系统中状态和参数联合估计的双重粒子滤波方法[J].电子与信息学报,2008,30(9):2128-2133. 被引量:11
  • 10熊剑,刘建业,赖际舟,郑智明.基于高斯粒子滤波的陀螺ARIMA模型辨识方法[J].中国惯性技术学报,2010,18(4):493-497. 被引量:5

引证文献3

二级引证文献9

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部