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Michael J. Corinthios, "A Weighted Z Spectrum, Parallel Algorithm, and Processors for Mathematical Model Estimation," IEEE Transactions on Computers, vol. 45, no. 5, pp. 513528, May, 1996.  
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@article{ 10.1109/12.509904, author = {Michael J. Corinthios}, title = {A Weighted Z Spectrum, Parallel Algorithm, and Processors for Mathematical Model Estimation}, journal ={IEEE Transactions on Computers}, volume = {45}, number = {5}, issn = {00189340}, year = {1996}, pages = {513528}, doi = {http://doi.ieeecomputersociety.org/10.1109/12.509904}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Computers TI  A Weighted Z Spectrum, Parallel Algorithm, and Processors for Mathematical Model Estimation IS  5 SN  00189340 SP513 EP528 EPD  513528 A1  Michael J. Corinthios, PY  1996 KW  Complex exponential decomposition KW  complex frequency decomposition KW  digital filter synthesis KW  generalized spectral analysis KW  mathematical model estimation KW  parallel algorithms KW  parallel processing KW  polezero estimation KW  system identification KW  Z transform. VL  45 JA  IEEE Transactions on Computers ER   
Abstract—A novel generalized spectral analysis approach which applies a weighting to ztransform spectra evaluated on contours in the ztransform plane is proposed. A parallel algorithm and 1D and 2D parallel processor architectures for the estimation of the polezero mathematical model of a system from a truncated version of its impulse response by succesive parallel evaluations of the proposed weighted ztransform spectra are subsequently presented. The algorithm is applicable to system identification and digital filter synthesis. The proposed weighted ztransform spectra and associated energy spectra make possible the evaluation of the poles and zeros of an infinite impulse response system of which the order is unknown from a truncated version of its impulse response with reasonable accuracy. A parallel dynamic weighting of ztransform spectra that is a function of z is shown to overcome the effect of exponential divergence of the ztransform of finite duration sequences as the zplane center is approached. The resulting "bidimensional spectral decomposition," in terms of both hyperbolic and circular function content, is in contrast with that of Fourier and ztransforms which for finite duration sequences are shown to effect a decomposition in terms of only circular function content. Using parallel fast transform operations the proposed algorithm unmasks polezero peaks and through interpolation estimates the associated residues. The corresponding timesequence component is deleted, the process repeated and the zeros determined using the evaluated residues. Optimal parallel and pipelined 1D and 2Dtype processor architectures are proposed, leading to the possibility of on line adaptive modeling of fast varying systems.
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