Independent component analysis for naive bayes classification

... naïve Bayes MRMR Minimum redundancy maximum relevance NB Naïve Bayes PCA Principal component analysis PC-ICA Partition-conditional independent component analysis TCA Tree-dependent component analysis ... CCICA for naïve Bayes classifier PC-ICA for NB classification of microarray data A sequential feature extraction approach for NB classification of microarray dat...

Ngày tải lên: 11/09/2015, 10:02

... transform three band MR images into three statistically independent component images so that these three ICA-generated independent components (ICs) can be stacked one atop another to form a new image ... Bagarinao, et al., “Application of independent component analysis to magnetic resonance imaging for enhancing the contrast of gray and white matter,” NeuroImage, vol 21, n...

Ngày tải lên: 21/06/2014, 22:20

... between reconfigurable FPGA system and C++ implementation CONCLUSION In this paper, we presented a run-time reconfigurable FPGA system implementation for the pICA algorithm to compensate for the performance ... reconfigurable FPGA system The speedup, compared to the C++ implementation, is 2.257 when the amount of weight vectors is twenty The proposed reconfigurable FPGA...

Ngày tải lên: 22/06/2014, 22:20

... by principal component analysis (PCA); see Sections 13.1.2 and 13.2.2 In noisy ICA, we also encounter a new problem: estimation of the noise-free realizations of the independent components (ICs) ... consider the ~ noisy independent components, given by si = si + ni , and rewrite the model as x = A~ s (15.3) We see that this is just the basic ICA model, with modified independent compo...

Ngày tải lên: 17/10/2013, 19:15

... ESTIMATION OF THE INDEPENDENT COMPONENTS Maximum likelihood estimation Many methods for estimating the mixing matrix use as subroutines methods that estimate the independent components for a known ... methods for reconstructing the independent components, assuming that we know the mixing matrix Let us denote by m the number of mixtures and by n the number of independent components Thu...

Ngày tải lên: 20/10/2013, 10:15

... unknown realvalued m -component mixing function, and is an n-vector whose elements are the n unknown independent components Assume now for simplicity that the number of independent components n equals ... : : : xn into n independent components y1 : : : yn , giving a solution for the nonlinear ICA problem This construction also clearly shows that the decomposition in independent compo...

Ngày tải lên: 20/10/2013, 10:15

... means that simply finding a matrix so that the components of the vector C A V z(t) = Vx(t) (18.3) are white, is not enough to estimate the independent components This is because there is an infinity ... infinity of different matrices that give decorrelated components This is why in basic ICA, we have to use the nongaussian structure of the independent components, for example, by minimizing t...

Ngày tải lên: 24/10/2013, 08:15

... the signal x(t) to be deconvolved Estimating just one independent component , we obtain the original deconvolved signal s(t) If several components are estimated, they correspond to translated ... one independent component, which x x 364 CONVOLUTIVE MIXTURES AND BLIND DECONVOLUTION is easier than estimating all of them In convolutive BSS, however, we often need to estimate all the indepe...

Ngày tải lên: 24/10/2013, 08:15

... by independent subspaces analysis, to be explained next 20.2.2 Independent subspace analysis Independent subspace analysis [204] is a simple model that models some dependencies between the components ... methods of independent subspaces or topographic ICA, on the other hand, we assume that we cannot really find independent components; instead we can find groups of independent c...

Ngày tải lên: 28/10/2013, 15:15

... into independent components One can always obtain uncorrelated components, and this is what we obtain with FastICA In image feature extraction, however, one can clearly see that the ICA components ... processing the signals, for example, to compress or denoise them Naturally, we shall use independent component analysis (ICA) as the principal model for natural images We shall also cons...

Ngày tải lên: 28/10/2013, 15:15

... the existence of statistically independent source signals, their instantaneous linear mixing at the sensors, and the stationarity of the mixing and the independent components (ICs) The independence ... concomitant sound Principal component analysis (PCA) has often been used to decompose signals of this kind, but as we have seen in Chapter 7, it cannot really separate independent sig...

Ngày tải lên: 07/11/2013, 09:15

... user’s subsequent transmitted symbols are assumed to be independent, these products are also independent for a given user i Denote the independent sources a1 m b1 m : : : aLm bKm by yi (m) i ... cost function can be separated, and the different independent components can be found one by one, by taking into account the previously estimated components, contained in the subspace spanned b...

Ngày tải lên: 07/11/2013, 09:15

... time-varying underlying factor or independent component sj (t) on the measured time series is approximately linear The assumption of having some underlying independent components in this specific application ... mean and unit variance), the independent components 444 OTHER APPLICATIONS 20 40 28 48 16 20 40 28 48 16 20 40 28 48 16 20 40 28 48 16 Fig 24.2 Four independent components or...

Ngày tải lên: 07/11/2013, 09:15

... is not enough to separate the components This is also the reason why principal component analysis (PCA) or factor analysis cannot separate the signals: they give components that are uncorrelated, ... the components yi should be statistically independent This means that the value of any one of the components gives no information on the values of the other components In fact, in factor a...

Ngày tải lên: 13/12/2013, 14:15