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The procedure of projection matching is much easier to understand in principle, but it needs an initial model.
The procedure of projection calculation does not guarantee the uniqueness of the representation and the results can be dramatically different (visually) for the very close distance matrices.
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For simplicity, we take GS for example to describe the procedures of iterative projection approach with phase sparse constraint, which is shown in Algorithm 2. Algorithm 2 GS-type iterative projection approach with phase sparse constraint (GS-PhSparse) for phase retrieval.
In the next, we take GS approach for an example to describe the procedures of iterative projection approach, which are shown in details in Algorithm 1. Algorithm 1 GS-type approach (GS) for phase retrieval.
Then a generalized procedure for projection kinematic analysis is presented.
To build an imaging array, the multiplexing procedure via method of projections allows for readout from columns or rows, not from individual pixels, so the number of leads can be reduced to N+M for N×M double-polarized array.
In smoothing procedure, we need to divide the summation of projection vector data which are overlap with smoothing filter to the length of the smoothing filter, AFlen.
In this case, our procedure of adjusting the AR(1) projection downwards to adjust for the influence of homicides is almost exactly the same, we subtract (0.0489 + 0.0192)*geomortrate from the AR(1) projection that begins in September of 2001.22 Figure 3 shows the AR(1) projection as a solid line and there is a dashed line with its downwards adjustment.
A procedure for the projection of structure-borne sound fields is introduced, following the basic idea behind Near-Field Acoustic Holography.
Perhaps it was a case of projection.
A second common type of projection is called stereographic projection.
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