**Omnet projects in Western Australia:**

**Omnet projects in Western Australia **Following decomposition of the signal along a new set of basis functions , filtering can be achieved by assigning weightings to each basis omnet projects in Western Australiafunction where is the filtered output signal with the same dimensions as .

In many standard filtering approaches, the filter weightings are chosen *a priori *based on an assumption of the source signal of interest. In frequency-domain filtering using omnet projects in Western Australiathe DFT, when basis functions are composed of complex exponentials, weightings are assigned based on the assumed frequency composition of the source signals.

In the application of clutter filtering, signal originating from the desired sources are assumed to have higheromnet projects in Western Australia frequency than the more static clutter signal, and therefore a high pass filter is typically used Similarly, in PCA-based filtering approaches,

the weightings can be defined *a priori *based on the assumed relative amount of variance accounted for omnet projects in Western Australiaby the desired source signal. This procedure entails rejecting a set number of basis functions with the largest eigenvalues

based on the assumption that clutter is more energetic than the underlying tissue While this *a priori *strategy for defining weighting coefficients parallels standard DFT filtering design, it is generally inadequate in PCAbased methods since PCA basisomnet projects in Western Australia functions are not known *a priori *as in the DFT.

As a result of adaptively determining the basis functions, the same weighting coefficients at different omnet projects in Western Australiaspatial locations in the image have the potential to filter different source signals.