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the excitation coefficients (voltage distribution) of the elements within a subarray. In order to estimate the voltage distribution of the elements within a subarray, the equivalent load impedances experienced by the output ports of a PDN must be determined. To account for mutual coupling between the radiating elements, the terminating loads are collectively represented by an impedance matrix (equivalently, by admittance or by scattering matrices). Two different methods exist for obtaining the above impedance matrix. The first method considers a subarray as a unit cell for the infinite array of subarrays and then performs the Floquet modal analysis of the infinite periodic structure of such large unit cells [3]. This method requires excessive analytical and computational efforts, because a large number of unknowns need to be solved simultaneously. The large number of unknowns is primarily due to multiple elements inside a large cell, requiring several basis functions to represent unknown aperture fields or currents for the elements. In this section, we will articulate an alternative approach to determine the impedance matrix of a subarray. The method is elegant and accurate and computationally simpler but applicable for elements that are equally spaced. Using matrix theory and Floquet modal analysis, we prove that the subarray characteristics can be estimated from the characteristics of an individually fed element array. We present the derivation of a subarray impedance matrix under Floquet excitation of the array of subarrays. The Floquet impedance at the subarray input can then be determined from the subarray impedance matrix and the PDN impedance matrix. Treating each subarray as an element and then employing the theory developed in 4, one can determine the active impedances of a finite array of subarrays.
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The Asynchronous Completion Token and Memento patterns [GoF95] are similar with respect to their participants. In the Memento pattern, originators give mementos to caretakers who treat the Memento as 'opaque' objects. In the Asynchronous Completion Token pattern, initiators give ACTs to services that treat the ACTs as 'opaque' objects. These patterns differ in motivation and applicability however. The Memento pattern takes 'snapshots' of object states, whereas the Asynchronous Completion Token pattern associates state with the completion of asynchronous operations. Another difference is in their dynamics. In the Asynchronous Completion Token pattern, the initiator which corresponds to the originator in Memento creates the ACT proactively and passes it to the service. In Memento, the caretaker which is the initiator in terms of Asynchronous
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