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We therefore propose in this work an integrated modal expansion/inverse problem methodology combined with an optimization procedure.
The results show that identification and optimization procedure for the integrated modal expansion/inverse problem approach provides more accurate predictions than the ones given by the pure modal expansion method.
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We end this essay by discussing two related problems: Modal problems and temporal problems.
This study addresses the modal retrieval problem.
(iii) We show how to extend the sparse 1-D modal estimation problem to R-D modal problems.
These are: (a) the lone ammonium molecule problem; (b) the modal status problem; (c) the epiphenomenal ectoplasm problem; and (d) the blockers problem.
Meanwhile, a PSO algorithm is adopted to cope with the modal selection problem in RDA.
In Section 5, we extend the sparse multigrid approach to the R-D modal estimation problem.
Then the modal estimation problem can be formulated as a penalized ℓ2 - ℓ0 sparse signal estimation problem (2).
Then the R-D modal retrieval problem can be formulated as a penalized ℓ2 - ℓ0 sparse signal estimation problem (2).
For this we approximate modal state variables by finite number of orthogonal exponential zero-interpolants to reduce the modal optimization problem to the system of algebraic equations.
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