These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

135 related articles for article (PubMed ID: 21096739)

  • 1. Extended Kalman filtering of point process observation.
    Salimpour Y; Soltanian-Zadeh H; Abolhassani MD
    Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():6670-3. PubMed ID: 21096739
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Neuronal spike train analysis in likelihood space.
    Salimpour Y; Soltanian-Zadeh H; Salehi S; Emadi N; Abouzari M
    PLoS One; 2011; 6(6):e21256. PubMed ID: 21738626
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Real-time particle filtering and smoothing algorithms for detecting abrupt changes in neural ensemble spike activity.
    Hu S; Zhang Q; Wang J; Chen Z
    J Neurophysiol; 2018 Apr; 119(4):1394-1410. PubMed ID: 29357468
    [TBL] [Abstract][Full Text] [Related]  

  • 4. The time-rescaling theorem and its application to neural spike train data analysis.
    Brown EN; Barbieri R; Ventura V; Kass RE; Frank LM
    Neural Comput; 2002 Feb; 14(2):325-46. PubMed ID: 11802915
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Hybrid Cubature Kalman filtering for identifying nonlinear models from sampled recording: Estimation of neuronal dynamics.
    Madi MK; Karameh FN
    PLoS One; 2017; 12(7):e0181513. PubMed ID: 28727850
    [TBL] [Abstract][Full Text] [Related]  

  • 6. The Discriminative Kalman Filter for Bayesian Filtering with Nonlinear and Nongaussian Observation Models.
    Burkhart MC; Brandman DM; Franco B; Hochberg LR; Harrison MT
    Neural Comput; 2020 May; 32(5):969-1017. PubMed ID: 32187000
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Estimating a state-space model from point process observations.
    Smith AC; Brown EN
    Neural Comput; 2003 May; 15(5):965-91. PubMed ID: 12803953
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Real-Time Point Process Filter for Multidimensional Decoding Problems Using Mixture Models.
    Rezaei MR; Arai K; Frank LM; Eden UT; Yousefi A
    J Neurosci Methods; 2021 Jan; 348():109006. PubMed ID: 33232686
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Sequential Monte Carlo point-process estimation of kinematics from neural spiking activity for brain-machine interfaces.
    Wang Y; Paiva AR; Príncipe JC; Sanchez JC
    Neural Comput; 2009 Oct; 21(10):2894-930. PubMed ID: 19548797
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A point-process matched filter for event detection and decoding from population spike trains.
    Sadras N; Pesaran B; Shanechi MM
    J Neural Eng; 2019 Oct; 16(6):066016. PubMed ID: 31437831
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Dynamic analysis of neural encoding by point process adaptive filtering.
    Eden UT; Frank LM; Barbieri R; Solo V; Brown EN
    Neural Comput; 2004 May; 16(5):971-98. PubMed ID: 15070506
    [TBL] [Abstract][Full Text] [Related]  

  • 12. An analysis of neural receptive field plasticity by point process adaptive filtering.
    Brown EN; Nguyen DP; Frank LM; Wilson MA; Solo V
    Proc Natl Acad Sci U S A; 2001 Oct; 98(21):12261-6. PubMed ID: 11593043
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A mixed filter algorithm for cognitive state estimation from simultaneously recorded continuous and binary measures of performance.
    Prerau MJ; Smith AC; Eden UT; Yanike M; Suzuki WA; Brown EN
    Biol Cybern; 2008 Jul; 99(1):1-14. PubMed ID: 18438683
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Neural Decoding: A Predictive Viewpoint.
    Todorova S; Ventura V
    Neural Comput; 2017 Dec; 29(12):3290-3310. PubMed ID: 28957019
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Identification of time-varying neural dynamics from spike train data using multiwavelet basis functions.
    Xu S; Li Y; Guo Q; Yang XF; Chan RHM
    J Neurosci Methods; 2017 Feb; 278():46-56. PubMed ID: 28062244
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation.
    Jiang C; Zhang SB; Zhang QZ
    Sensors (Basel); 2016 Dec; 16(12):. PubMed ID: 27999361
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Construction of point process adaptive filter algorithms for neural systems using sequential Monte Carlo methods.
    Ergün A; Barbieri R; Eden UT; Wilson MA; Brown EN
    IEEE Trans Biomed Eng; 2007 Mar; 54(3):419-28. PubMed ID: 17355053
    [TBL] [Abstract][Full Text] [Related]  

  • 18. A Copula-Based Granger Causality Measure for the Analysis of Neural Spike Train Data.
    Hu M; Li W; Liang H
    IEEE/ACM Trans Comput Biol Bioinform; 2018; 15(2):562-569. PubMed ID: 29610104
    [TBL] [Abstract][Full Text] [Related]  

  • 19. EMG prediction from motor cortical recordings via a nonnegative point-process filter.
    Nazarpour K; Ethier C; Paninski L; Rebesco JM; Miall RC; Miller LE
    IEEE Trans Biomed Eng; 2012 Jul; 59(7):1829-38. PubMed ID: 21659018
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Fast Kalman filtering on quasilinear dendritic trees.
    Paninski L
    J Comput Neurosci; 2010 Apr; 28(2):211-28. PubMed ID: 19943188
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 7.