The GIF Analysis

The PCA decomposition is directly fed into ind.m, which calculates the generalized indicator functions.
 

$$[\Phi ,\mathbf{R},\Gamma ,SNR]=\mathbf{ind}(\Psi ,\mathbf{A},\mathbf{D},K,thr)$$

where K  is the total number of experimental conditions, and thr is the threshold signal-to-noise ratio, whose default value is 4, and
 

$$\mathbf{R}=\left[ \begin{array}{ccc}\rho _{1} & \cdots & \r......s & \phi _{l}\\\downarrow & & \downarrow\end{array}\right]$$

is a P x l matrix which contains the column vectors of l; l < K, indicator functions (orthogonal signal images),  is the list of l eigenvalues, and R is a KT x l matrix of the response amplitude, , corresponding to each indicator functions.  SNR is the signal-to-noise ratios of the 's, which are guaranteed to be > thr by the algorithm.

After the indicator functions and their response amplitudes are obtained, one can use eigenview.m or its analog to display the signal image and to plot its amplitude.