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Iterative System Modeling Using Multigrid Techniques

机译：基于多重网格技术的迭代系统建模

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One and two-dimensional system identification and modeling algorithms utilizingmultigrid techniques are presented. Finite impulse response (FIR), autoregressive (AR), infinite impulse response (IIR), and 2-D block matrix iterative system modeling algorithms are enhanced and made more efficient using the multigrid methods. The convergence performance of these algorithms is improved with the multigrid techniques. The reduction in the number of iterations required to converge to a solution is realized by forcing the low frequency error components to appear to be at a higher frequency by transferring to a coarser sampling period. Performance comparisons are presented for FIR, AR, IIR, and 2-D block matrix modeling simulations with and without the multigrid-techniques employed.

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