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The relative gain array (RGA) and Niederlinski index (NI) are generally employed to eliminate unworkable pairings.
In this paper, Bristol's relative gain array (RGA) is extended to non-square multivariable systems.
A centralized controller designed based on a relative normalized gain array (RNGA) gives a better performance than a centralized controller designed based on a relative gain array (RGA).
Controllability measures such as relative gain array (RGA) and singular value decomposition (SVD) are used.
Relative gain array is used to minimize the interaction and to select the variable pairings.
The best candidates to CVs were paired with the manipulated variables using the relative gain array.
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Based on the control rate optimized, two inverse normalized gain arrays are obtained from SFPC and MGPC which show the dynamic effects of controlled variables on manipulated variables.
With the inverse normalized gain arrays, the regulator configuration design of unstable systems can be carried out due to the effect of multivariable centralized control.
To test for other chromosomal deletions or gains, array comparative genomic hybridisation was carried out on DNA extracted from the R482Q/+ adenocarcinoma, but no copy number variants were identified.
As a result, the balance between spatial multiplexing gains and array gains may be ignored in mmWave communications.
Especially, the first method supersedes the second one for high-gain arrays.
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