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{99} | |||
PMID-15928412[0] Naive coadaptive Control May 2005. see notes ____References____ | |||
{1413} | |||
PMID-24711417 Evidence for a causal inverse model in an avian cortico-basal ganglia circuit
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{989} | |||
PMID-19603074[0] Unscented Kalman filter for brain-machine interfaces.
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{301} | |||
040507. wiener pred. same deal as {262} kalman fit/pred. per-unit and channel aggregate SNR summary unit chan lag snr behav var 1.0000 69.0000 1.0000 1.1159 2.0000 1.0000 58.0000 1.0000 1.1074 6.0000 2.0000 44.0000 2.0000 1.1040 2.0000 2.0000 44.0000 1.0000 1.0953 2.0000 2.0000 93.0000 1.0000 1.0868 3.0000 2.0000 64.0000 0 1.0728 3.0000 1.0000 69.0000 2.0000 1.0698 2.0000 1.0000 32.0000 0 1.0684 3.0000 2.0000 44.0000 0 1.0634 8.0000 1.0000 58.0000 0 1.0613 6.0000 1.0000 33.0000 1.0000 1.0594 1.0000 2.0000 93.0000 3.0000 1.0523 3.0000 1.0000 63.0000 0 1.0507 3.0000 1.0000 67.0000 1.0000 1.0490 5.0000 1.0000 47.0000 0 1.0489 3.0000 1.0000 12.0000 4.0000 1.0472 3.0000 2.0000 93.0000 2.0000 1.0460 3.0000 1.0000 24.0000 0 1.0459 3.0000 1.0000 42.0000 1.0000 1.0447 6.0000 1.0000 24.0000 1.0000 1.0440 3.0000 1.0000 69.0000 3.0000 1.0431 2.0000 2.0000 60.0000 0 1.0429 5.0000 1.0000 61.0000 0 1.0410 4.0000 1.0000 12.0000 1.0000 1.0400 1.0000 1.0000 32.0000 3.0000 1.0395 3.0000 1.0000 8.0000 1.0000 1.0387 1.0000 1.0000 33.0000 0 1.0386 11.0000 1.0000 0 1.0000 1.0383 4.0000 2.0000 77.0000 2.0000 1.0383 1.0000 1.0000 47.0000 1.0000 1.0382 3.0000 2.0000 60.0000 1.0000 1.0376 10.0000 2.0000 77.0000 1.0000 1.0375 1.0000 1.0000 28.0000 1.0000 1.0374 1.0000 1.0000 69.0000 5.0000 1.0359 3.0000 1.0000 42.0000 0 1.0358 3.0000 1.0000 8.0000 0 1.0357 3.0000 1.0000 63.0000 3.0000 1.0357 3.0000 2.0000 68.0000 1.0000 1.0348 1.0000 1.0000 51.0000 0 1.0343 3.0000 1.0000 30.0000 1.0000 1.0341 1.0000 1.0000 24.0000 2.0000 1.0341 3.0000 2.0000 93.0000 5.0000 1.0340 3.0000 1.0000 63.0000 4.0000 1.0338 3.0000 1.0000 63.0000 2.0000 1.0337 3.0000 1.0000 12.0000 2.0000 1.0329 1.0000 2.0000 23.0000 1.0000 1.0325 1.0000 1.0000 46.0000 1.0000 1.0324 2.0000 1.0000 28.0000 0 1.0323 1.0000 2.0000 93.0000 4.0000 1.0321 3.0000 1.0000 58.0000 3.0000 1.0316 6.0000 1.0000 47.0000 2.0000 1.0314 6.0000 1.0000 48.0000 0 1.0311 4.0000 1.0000 12.0000 3.0000 1.0310 3.0000 1.0000 12.0000 0 1.0309 3.0000 1.0000 48.0000 1.0000 1.0303 11.0000 1.0000 28.0000 2.0000 1.0300 1.0000 2.0000 60.0000 2.0000 1.0294 10.0000 1.0000 46.0000 0 1.0293 8.0000 1.0000 49.0000 0 1.0291 3.0000 1.0000 24.0000 3.0000 1.0286 1.0000 2.0000 77.0000 3.0000 1.0282 3.0000 1.0000 8.0000 2.0000 1.0282 1.0000 2.0000 15.0000 1.0000 1.0281 3.0000 2.0000 68.0000 2.0000 1.0278 1.0000 2.0000 23.0000 0 1.0273 1.0000 1.0000 112.0000 1.0000 1.0261 7.0000 1.0000 69.0000 4.0000 1.0258 3.0000 2.0000 92.0000 3.0000 1.0244 3.0000 2.0000 42.0000 1.0000 1.0244 11.0000 1.0000 58.0000 2.0000 1.0238 3.0000 1.0000 61.0000 1.0000 1.0234 7.0000 1.0000 32.0000 4.0000 1.0232 3.0000 1.0000 33.0000 2.0000 1.0231 1.0000 1.0000 30.0000 4.0000 1.0231 3.0000 1.0000 46.0000 2.0000 1.0227 2.0000 1.0000 30.0000 3.0000 1.0226 3.0000 1.0000 45.0000 0 1.0225 3.0000 1.0000 60.0000 0 1.0225 3.0000 2.0000 84.0000 5.0000 1.0222 3.0000 1.0000 32.0000 1.0000 1.0221 1.0000 1.0000 24.0000 4.0000 1.0220 1.0000 1.0000 28.0000 3.0000 1.0219 1.0000 1.0000 64.0000 1.0000 1.0216 4.0000 2.0000 84.0000 1.0000 1.0215 3.0000 1.0000 30.0000 0 1.0212 3.0000 2.0000 77.0000 5.0000 1.0211 3.0000 1.0000 63.0000 1.0000 1.0210 3.0000 1.0000 33.0000 4.0000 1.0209 1.0000 1.0000 7.0000 1.0000 1.0209 3.0000 2.0000 35.0000 0 1.0202 3.0000 | |||
{262} | |||
clementine, 040207, Miguel's sorting. top 200 lags selected via bmisql.m , decent SNR on all channels but I had to z-score the state and measurement matricies. -- standard wiener -- linear kalman. -- associated behavior | |||
{1007} | |||
IEEE-5910570 (pdf) Spiking neural network decoder for brain-machine interfaces
____References____ Dethier, J. and Gilja, V. and Nuyujukian, P. and Elassaad, S.A. and Shenoy, K.V. and Boahen, K. Neural Engineering (NER), 2011 5th International IEEE/EMBS Conference on 396 -399 (2011) | |||
{97} | |||
From Uncertain Spikes to Prosthetic Control a powerpoint presentation w/ good overview of all that the Brown group has done | |||
{983} | |||
PMID-21976021[0] Active tactile exploration using a brain-machine-brain interface.
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{258} | |||
PMID-17271178[0] automatic spike sorting for neural decoding
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{37} |
ref: bookmark-0
tags: Unscented sigma_pint kalman filter speech processing machine_learning SDRE control UKF
date: 0-0-2007 0:0
revision:0
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{98} | |||
http://hardm.ath.cx/pdf/unscentedKalmanFilter.pdf -- the square root transform. contains a nice tabulation of the original algorithm, which i what I use. http://hardm.ath.cx/pdf/unscentedKalmanFilter2000.pdf -- the original, with examples of state, parameter, and dual estimation http://en.wikipedia.org/wiki/Kalman_filter -- wikipedia page, also has the unscented kalman filter http://www.cs.unc.edu/~welch/kalman/media/pdf/Julier1997_SPIE_KF.pdf - Julier and Ulhmann's original paper. a bit breif. http://www.cs.ubc.ca/~murphyk/Papers/Julier_Uhlmann_mar04.pdf -- Julier and Ulhmann's invited paper, quite excellent. | |||
{40} |
ref: bookmark-0
tags: Bayes Baysian_networks probability probabalistic_networks Kalman ICA PCA HMM Dynamic_programming inference learning
date: 0-0-2006 0:0
revision:0
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http://www.cs.ubc.ca/~murphyk/Bayes/bnintro.html very, very good! many references, well explained too. | |||
{92} | |||
with the extended kalman filter, from '92: http://ftp.ccs.neu.edu/pub/people/rjw/kalman-ijcnn-92.ps with the unscented kalman filter : http://hardm.ath.cx/pdf/NNTrainingwithUnscentedKalmanFilter.pdf |