• Title/Summary/Keyword: polynomial root

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ON THE DISTANCE TO A ROOT OF COMPLEX POLYNOMIALS UNDER NEWTON'S METHOD

  • Chaiya, Malinee;Chaiya, Somjate
    • Journal of the Korean Mathematical Society
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    • v.57 no.5
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    • pp.1119-1133
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    • 2020
  • In this paper, we derive an upper bound for the distance from a point in the immediate basin of a root of a complex polynomial to the root itself. We establish that if z is a point in the immediate basin of a root α of a polynomial p of degree d ≥ 12, then ${\mid}z-{\alpha}{\mid}{\leq}{\frac{3}{\sqrt{d}}\(6{\sqrt{310}}/35\)^d{\mid}N_p(z)-z{\mid}$, where Np is the Newton map induced by p. This bound leads to a new bound of the expected total number of iterations of Newton's method required to reach all roots of every polynomial p within a given precision, where p is normalized so that its roots are in the unit disk.

Study of Spectral Factorization using Circulant Matrix Factorization to Design the FIR/IIR Lattice Filters (FIR/IIR Lattice 필터의 설계를 위한 Circulant Matrix Factorization을 사용한 Spectral Factorization에 관한 연구)

  • 김상태;박종원
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.3
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    • pp.437-447
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    • 2003
  • We propose the methods to design the finite impulse response (FIR) and the infinite impulse response (IIR) lattice filters using Schur algorithm through the spectral factorization of the covariance matrix by circulant matrix factorization (CMF). Circulant matrix factorization is also very powerful tool used fur spectral factorization of the covariance polynomial in matrix domain to obtain the minimum phase polynomial without the polynomial root finding problem. Schur algorithm is the method for a fast Cholesky factorization of Toeplitz matrix, which easily determines the lattice filter parameters. Examples for the case of the FIR Inter and for the case of the IIR filter are included, and performance of our method check by comparing of our method and another methods (polynomial root finding and cepstral deconvolution).

Development of Predictive Growth Model of Listeria monocytogenes Using Mathematical Quantitative Assessment Model (수학적 정량평가모델을 이용한 Listeria monocytogenes의 성장 예측모델의 개발)

  • Moon, Sung-Yang;Woo, Gun-Jo;Shin, Il-Shik
    • Korean Journal of Food Science and Technology
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    • v.37 no.2
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    • pp.194-198
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    • 2005
  • Growth curves of Listeria monocytogenes in modified surimi-based imitation crab (MIC) broth were obtained by measuring cell concentration in MIC broth at different culture conditions [initial cell numbers, $1.0{\times}10^{2},\;1.0{\times}10^{3}\;and\;1.0{\times}10^{4}$, colony forming unit (CFU)/mL; temperature, 15, 20, 25, 37, and $40^{\circ}C$] and applied to Gompertz model to determine microbial growth indicators, maximum specific growth rate constant (k), lag time (LT), and generation time (GT). Maximum specific growth rate of L. monocytogenes increased rapidly with increasing temperature and reached maximum at $37^{\circ}C$, whereas LT and GT decreased with increasing temperature and reached minimum at $37^{\circ}C$. Initial cell number had no effect on k, LT, and GT (p > 0.05). Polynomial and square root models were developed to express combined effects of temperature and initial cell number using Gauss-Newton Algorism. Relative coefficients of experimental k and predicted k of polynomial and square root models were 0.92 and 0.95, respectively, based on response surface model. Results indicate L. monocytogenes growth was mainly affected by temperature and square root model was more effective than polynomial model for growth prediction.

The Parametric Sensitivity Analyses of linear System Relative to the Characteristic Ratios of Coefficient(II) : K-Polynomial Case (계수의 특성비에 대한 선형계의 파라미터적 감도해석(II) : K-다항식의 경우)

  • 김영철;김근식
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.4
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    • pp.295-303
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    • 2004
  • Previously it has been shown that the all pole systems resulting good time responses can be characterized by so called K-polynomial. The polynomial is defined in terms of the principal characteristic ratio $\alpha_1$ and the generalized time constant $\tau$ . In this paper, Part II presents several sensitivity analyses of such systems with respect to $\alpha_1$ and $\tau$ changes. We first deal with the root sensitivity to the perturbation of $\alpha_1$ . By way of determining the unnormalized function sensitivity, both time response sensitivity and frequency response sensitivity are derived. Finally, the root sensitivity relative to $\tau$ change is also analyzed. These results provide some useful insight and background theory when we select of and l to compose a reference model of which denominator is a K-polynomial, which is illustrated by examples.

ON LINEAR PERTURBATIONS AND ABSOLUTE ROOT BOUND FUNCTIONALS

  • Kim, Jin-Hwan;Park, Young-Kou
    • The Pure and Applied Mathematics
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    • v.10 no.1
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    • pp.37-47
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    • 2003
  • We will show that any linear perturbation of polynomials that introduces bounded perturbations into the roots of polynomial is some linear combination of the derivatives of a polynomial. And we will derive an absolute root bound functional which is in some sense better than the other known absolute root bound functionals.

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Design of FIR/IIR Lattice Filters using the Circulant Matrix Factorization (Circulant Matrix Factorization을 이용한 FIR/IIR Lattice 필터의 설계)

  • Kim Sang-Tae;Lim Yong-Kon
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.41 no.1
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    • pp.35-44
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    • 2004
  • We Propose the methods to design the finite impulse response (FIR) and the infinite impulse response (IIR) lattice filters using Schur algorithm through the spectral factorization of the covariance matrix by circulant matrix factorization (CMF). Circulant matrix factorization is also very powerful tool used for spectral factorization of the covariance polynomial in matrix domain to obtain the minimum phase polynomial without the polynomial root finding problem. Schur algorithm is the method for a fast Cholesky factorization of Toeplitz matrix, which easily determines the lattice filter parameters. Examples for the case of the FIR filter and for the case of the In filter are included, and performance of our method check by comparing of our method and another methods (polynomial root finding and cepstral deconvolution).

Development of Predictive Growth Model of Vibrio parahaemolyticus Using Mathematical Quantitative Model (수학적 정량평가모델을 이용한 Vibrio parahaemolyticus의 성장 예측모델의 개발)

  • Moon, Sung-Yang;Chang, Tae-Eun;Woo, Gun-Jo;Shin, Il-Shik
    • Korean Journal of Food Science and Technology
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    • v.36 no.2
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    • pp.349-354
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    • 2004
  • Predictive growth model of Vibrio parahaemolyticus in modified surimi-based imitation crab broth was investigated. Growth curves of V. parahaemolyticus were obtained by measuring cell concentration in culture broth under different conditions ($Initial\;cell\;level,\;1{\times}10^{2},\;1{\times}10^{3},\;and\;1{\times}10^{4}\;colony\;forming\;unit\;(CFU)/mL$; temperature, 15, 25 37, and $40^{\circ}C$; pH 6, 7, and 8) and applying them to Gompertz model. Microbial growth indicators, maximum specific growth rate (k), lag time (LT), and generation time (GT), were calculated from Gompertz model. Maximum specific growth rate (k) of V. parahaemolyticus increased with increasing temperature, reaching maximum rate at $37^{\circ}C$. LT and GT were also the shortest at $37^{\circ}C$. pH and initial cell number did not influence k, LT, and GT values significantly (p>0.05). Polynomial model, $k=a{\cdot}\exp(-0.5{\cdot}((T-T_{max}/b)^{2}+((pH-pH_{max)/c^{2}))$, and square root model, ${\sqrt{k}\;0.06(T-9.55)[1-\exp(0.07(T-49.98))]$, were developed to express combination effects of temperature and pH under each initial cell number using Gauss-Newton Algorism of Sigma plot 7.0 (SPSS Inc.). Relative coefficients between experimental k and k Predicted by polynomial model were 0.966, 0.979, and 0.965, respectively, at initial cell numbers of $1{\times}10^{2},\;1{\times}10^{3},\;and\;1{\times}10^{4}CFU/mL$, while that between experimental k and k Predicted by square root model was 0.977. Results revealed growth of V. parahaemolyticus was mainly affected by temperature, and square root model showing effect of temperature was more credible than polynomial model for prediction of V. parahaemolyticus growth.

Development of Predictive Growth Model of Imitation Crab Sticks Putrefactive Bacteria Using Mathematical Quantitative Assessment Model (수학적 정량평가모델을 이용한 게맛살 부패균의 성장 예측모델의 개발)

  • Moon, Sung-Yang;Paek, Jang-Mi;Shin, Il-Shik
    • Korean Journal of Food Science and Technology
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    • v.37 no.6
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    • pp.1012-1017
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    • 2005
  • Predictive growth model of putrefactive bacteria of surimi-based imitation crab in the modified surimi-based imitation crab (MIC) broth was investigated. The growth curves of putrefactive bacteria were obtained by measuring cell number in MIC broth under different conditions (Initial cell number, $1.0{\times}10^2,\;1.0{\times}10^3$ and $1.0{\times}10^4$ colony forming unit (CFU)/mL; temperature, $15^{\circ}C,\;20^{\circ}C\;and\;25^{\circ}C$) and applied them to Gompertz model. The microbial growth indicators, maximum specific growth rate constant (k), lag time (LT) and generation time (GT), were calculated from Gompertz model. Maximum specific growth rate (k) of putrefactive bacteria was become fast with rising temperature and fastest at $25^{\circ}C$. LT and GT were become short with rising temperature and shortest at $25^{\circ}C$. There were not significant differences in k, LT and GT by initial cell number (p>0.05). Polynomial model, $k=-0.2160+0.0241T-0.0199A_0$, and square root model, $\sqrt{k}=0.02669$ (T-3.5689), were developed to express the combination effects of temperature and initial cell number, The relative coefficient of experimental k and predicted k of polynomial model was 0.87 from response surface model. The relative coefficient of experimental k and predicted k of square root model was 0.88. From above results, we found that the growth of putrefactive bacteria was mainly affected by temperature and the square root model was more credible than the polynomial model for the prediction of the growth of putrefactive bacteria.