中国综合性科技类核心期刊(北大核心)

中国科学引文数据库来源期刊(CSCD)

美国《化学文摘》(CA)收录

美国《数学评论》(MR)收录

俄罗斯《文摘杂志》收录

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

卡尔曼滤波器在海马场电位ripple节律分析中的应用

张栌 林龙年

张栌, 林龙年. 卡尔曼滤波器在海马场电位ripple节律分析中的应用[J]. 华东师范大学学报(自然科学版), 2011, (6): 81-88.
引用本文: 张栌, 林龙年. 卡尔曼滤波器在海马场电位ripple节律分析中的应用[J]. 华东师范大学学报(自然科学版), 2011, (6): 81-88.
ZHANG Lu, LIN Long-nian. Analysis of hippocampal ripple osillations by application of Kalman filter[J]. Journal of East China Normal University (Natural Sciences), 2011, (6): 81-88.
Citation: ZHANG Lu, LIN Long-nian. Analysis of hippocampal ripple osillations by application of Kalman filter[J]. Journal of East China Normal University (Natural Sciences), 2011, (6): 81-88.

卡尔曼滤波器在海马场电位ripple节律分析中的应用

详细信息
  • 中图分类号: Q6

Analysis of hippocampal ripple osillations by application of Kalman filter

  • 摘要: 利用自适应自回归(adaptive autoregressive, AAR)模型和卡尔曼滤波器算法,分析小鼠海马CA1区场电位ripple高频振荡的时频特性.研究发现,与传统的基于短时傅立叶变换的实时频谱分析方法相比,利用AAR模型以及卡尔曼滤波器算法的参数化方法在对ripple高频振荡信号进行实时频谱分析时,具有更高的时域和频域分辨率.因此,基于卡尔曼滤波器得到的ripple能量变化,可更为准确、实时地反映ripple高频振荡的发生与变化过程.
  • [1] [1] ANDERSEN P. The Hippocampus Book[M]. Oxford: Oxford University Press, 2007.

    [2] BUZSAKI G, HORVATH Z, URIOSTE R, et al. High-frequency network oscillation in the hippocampus[J]. Science, 1992, 256: 1025-1027.

    [3] O′KEEFE J, NADEL L. The Hippocampus as a Cognitive Map[M]. Oxford: Clarendon Press, 1978.

    [4] O′KEEFE J, DOSTROYSKY J. The hippocampus as a spatial map. Preliminary evidence from unit activity in the freely-moving rat[J]. Brain Res, 1971, 34: 171-175.

    [5] WILSON M A, MCNAUGHTON B L. Reactivation of hippocampal ensemble memories during sleep[J]. Science, 1994, 265: 676-679.

    [6] LEE A K, WILSON M A. Memory of sequential experience in the hippocampus during slow wave sleep[J]. Neuron, 2002, 36: 1183-1194.

    [7] FOSTER D J, WILSON M A. Reverse replay of behavioural sequences in hippocampal place cells during the awake state[J]. Nature, 2006,440: 680-683.

    [8] O'NEILL J, SENIOR T J, ALLEN K, et al. Reactivation of experience-dependent cell assembly patterns in the hippocampus[J]. Nat Neurosci, 2008(11): 209-215.

    [9] BENEDICKS M. On fourier transforms of functions supported on sets of finite Lebesgue measure[J]. Journal of Mathematical Analysis and Applications, 1985, 106: 180-183.

    [10] KALMAN R E. A new approach to linear filtering and prediction problems[J]. Transactions of the ASME, 1960: 35-45.

    [11] KALMAN R E, BUCY R S. New results in linear filtering and prediction theory[J]. Transactions of the ASME Series D, Journal of Basic Engineering, 1961, 83: 95-107.

    [12] ANDERSON B D O, MOORE J B. Optimal Filtering[M]. New Jersey: Prentice Hall, 1979.

    [13] TARVAINEN M P, HILTUNEN J K, RANTA-AHO P O, et al. Estimation of nonstationary EEG with Kalman smoother approach: an application to event-related synchronization (ERS)[J]. Biomedical Engineering, IEEE Transactions on, 2004, 51: 516-524.

    [14] CRAMER H. On the theory of stationary random processes[J]. The Annals of Mathematics, 1940, 41: 215-230.〖JP〗

    [15] WIENER N. Extrapolation, Interpolation, and Smoothing of Stationary Time Series, with Engineering Applications[M]. Cambridge: Technology Press of the Massachusetts Institute of Technology, 1949.

    [16] MORF M, VIEIRA A, LEE D T L, et al. Recursive multichannel maximum entropy spectral estimation[J]. Geoscience Electronics, IEEE Transactions on, 1978, 16: 85-94.

    [17] DING M, BRESSLER S L, YANG W, et al. Short-window spectral analysis of cortical event-related potentials by adaptive multivariate autoregressive modeling: data preprocessing, model validation, and variability assessment[J]. Biological Cybernetics, 2000, 83: 35-45.

    [18] AKAIKE H. A new look at the statistical model identification[J]. Automatic Control, IEEE Transactions on, 2003, 19: 716-723.

    [19] HAMITON J D. Time Series Analysis[M]. Princeton: Princeton University Press, 1994.

    [20] ALOIS S. The electroencephalogram and the adaptive autoregressive model: theory and applications[D]. Technischen Universitat Graz, 2000.

    [21] NGUYEN D P, KLOOSTERMAN F, BARBIERI R, et al. Characterizing the dynamic frequency structure of fast oscillations in the rodent hippocampus[J]. Front Integr Neurosci, 2009(3): 11-11.

    [22] BOHLIN T. Analysis of EEG signals with changing spectra using a short-word Kalman estimator[J]. Mathematical Biosciences, 1977, 35: 221-259.

    [23] AMOLD M, MILNER X H R, WITTE H, et al. Adaptive AR modeling of nonstationary time series by means of Kalman filtering[J]. Biomedical Engineering, IEEE Transactions on, 1998, 45: 553-562.

    [24] COHEN B A, SANCES A. Stationarity of the human electroendephalogram[J]. Med Biol Eng Comput, 1977, 15: 513-518.
  • 加载中
计量
  • 文章访问数:  2289
  • HTML全文浏览量:  6
  • PDF下载量:  2232
  • 被引次数: 0
出版历程
  • 收稿日期:  2010-11-01
  • 修回日期:  2011-01-01
  • 刊出日期:  2011-11-25

目录

    /

    返回文章
    返回