diff --git a/Docs/Math.html b/Docs/Math.html index e1819b45..944f0ca7 100644 --- a/Docs/Math.html +++ b/Docs/Math.html @@ -486,6 +486,18 @@

Unary operators

Data segmentation (k-means)
+ pca
+ + Principal component coordinates
+ + 0
+ +
+ + Principal component analysis
+ + + resize
Resized signal
@@ -930,7 +942,10 @@

Convolution/correlation

computes the cross correlation of two signals. The auto-correlation is simply xcorr(a).

-Last, the corrcoef method returns the Pearson product-moment correlation coefficient, which measures the similarity between two data sets. It returns a measure of the similarity between data sets (1=equal, 0=non correlated, -1=anti-correlated).
+Last, the corrcoef method returns the Pearson product-moment correlation coefficient, + which measures the similarity between two data sets. It returns a +measure of the similarity between data sets (1=equal, 0=non correlated, +-1=anti-correlated).

Warning: The accuracy of the conv and xcorr operators depends on the axis sampling. A coarse axis sampling (that is @@ -1053,6 +1068,11 @@

Data segmentation (partitioning The wavelet transform cwt may also be used to perform a peak analysis, separating sharp features from broad ones (see above).
+
+The principal component analysis + (PCA) methodology consists in finding similarities between data sets. +Groups of 'close' data sets can then be defined. The corresponding iData + method is pca .

Projection, integration and sum

iData: sum and projectionThere are diff --git a/Docs/Methods.html b/Docs/Methods.html index fd5a8134..9f6ec2cd 100644 --- a/Docs/Methods.html +++ b/Docs/Methods.html @@ -35,6 +35,9 @@

iF 
>> methods(iData)
The help windows then displays the help for each command (usage, input and output arguments, examples, ...).

+To get help of any of these iData methods, type e.g.:
+
>> help iData/load
+ Most of these methods are also valid for iFunc model objects, and the naming corresponds with standard Matlab functions.

data structure, aliases, signal and axes

@@ -42,17 +45,17 @@