I developed an algorithm for using local ICA in denoising multidimensional data. It uses delay embedded version of the data, clustering and ICA for the separation between data and noise.

denoise
.......\aconv.m
.......\autocor.m
.......\choosenumberofcomponents.m
.......\cplot.m
.......\degrade.m
.......\delay.m
.......\demo.m
.......\denoise.m
.......\denoise_delayedcoordinates.m
.......\denoise_locca.m
.......\denoise_locca_findbest.m
.......\dist.m
.......\fastica.m
.......\fasticapearson.m
.......\findbeststep.m
.......\fpica.m
.......\gbd_momentfit.m
.......\gbd_score.m
.......\getmdl.m
.......\icaplot.m
.......\jade.m
.......\kmeans_cluster.m
.......\kurtosis.m
.......\lena.mat
.......\mdl.m
.......\ort.m
.......\pcamat.m
.......\pearson_ica.m
.......\pearson_momentfit.m
.......\pearson_score.m
.......\remmean.m
.......\scplot.m
.......\SNR.m
.......\undelay.m
.......\whitenv.m

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