R ij can also be taken to be equal to σ i σ j Corr(i, j) where σi2 is the variance of the strength of the ith dipole and Corr(i, j) is the correlation between the strengths of the ith and jth dipoles. Thus any a priori information about correlation between the dipole strengths at different locations can be used as a constraint. R can also be taken as RiiRjj(Corr(i,j)) where Rii=f(1ζi) is such that it is large when the measure ζ i of projection onto the noise subspace is small. The matrix C can be taken as σ2I if it is assumed that the sensor noise is additive and white with constant variance σ2. R can also be constructed in such a way that it is equal to UU T where U is an orthonormal set of arbitrary basis vectors [12]. The new inverse operator using these arbitrary basis functions is the original forward solution projected onto the new basis functions.
