• Title/Summary/Keyword: Fixed-point Algorithm

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A Variable Latency Newton-Raphson's Floating Point Number Reciprocal Square Root Computation (가변 시간 뉴톤-랍손 부동소수점 역수 제곱근 계산기)

  • Kim Sung-Gi;Cho Gyeong-Yeon
    • The KIPS Transactions:PartA
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    • v.12A no.5 s.95
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    • pp.413-420
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    • 2005
  • The Newton-Raphson iterative algorithm for finding a floating point reciprocal square mot calculates it by performing a fixed number of multiplications. In this paper, a variable latency Newton-Raphson's reciprocal square root algorithm is proposed that performs multiplications a variable number of times until the error becomes smaller than a given value. To find the rediprocal square root of a floating point number F, the algorithm repeats the following operations: '$X_{i+1}=\frac{{X_i}(3-e_r-{FX_i}^2)}{2}$, $i\in{0,1,2,{\ldots}n-1}$' with the initial value is '$X_0=\frac{1}{\sqrt{F}}{\pm}e_0$'. The bits to the right of p fractional bits in intermediate multiplication results are truncated and this truncation error is less than '$e_r=2^{-p}$'. The value of p is 28 for the single precision floating point, and 58 for the double precision floating point. Let '$X_i=\frac{1}{\sqrt{F}}{\pm}e_i$, there is '$X_{i+1}=\frac{1}{\sqrt{F}}-e_{i+1}$, where '$e_{i+1}{<}\frac{3{\sqrt{F}}{{e_i}^2}}{2}{\mp}\frac{{Fe_i}^3}{2}+2e_r$'. If '$|\frac{\sqrt{3-e_r-{FX_i}^2}}{2}-1|<2^{\frac{\sqrt{-p}{2}}}$' is true, '$e_{i+1}<8e_r$' is less than the smallest number which is representable by floating point number. So, $X_{i+1}$ is approximate to '$\frac{1}{\sqrt{F}}$. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications Per an operation is derived from many reciprocal square root tables ($X_0=\frac{1}{\sqrt{F}}{\pm}e_0$) with varying sizes. The superiority of this algorithm is proved by comparing this average number with the fixed number of multiplications of the conventional algorithm. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a reciprocal square root unit. Also, it can be used to construct optimized approximate reciprocal square root tables. The results of this paper can be applied to many areas that utilize floating point numbers, such as digital signal processing, computer graphics, multimedia, scientific computing, etc.

A Variable Latency Newton-Raphson's Floating Point Number Reciprocal Computation (가변 시간 뉴톤-랍손 부동소수점 역수 계산기)

  • Kim Sung-Gi;Cho Gyeong-Yeon
    • The KIPS Transactions:PartA
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    • v.12A no.2 s.92
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    • pp.95-102
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    • 2005
  • The Newton-Raphson iterative algorithm for finding a floating point reciprocal which is widely used for a floating point division, calculates the reciprocal by performing a fixed number of multiplications. In this paper, a variable latency Newton-Raphson's reciprocal algorithm is proposed that performs multiplications a variable number of times until the error becomes smaller than a given value. To find the reciprocal of a floating point number F, the algorithm repeats the following operations: '$'X_{i+1}=X=X_i*(2-e_r-F*X_i),\;i\in\{0,\;1,\;2,...n-1\}'$ with the initial value $'X_0=\frac{1}{F}{\pm}e_0'$. The bits to the right of p fractional bits in intermediate multiplication results are truncated, and this truncation error is less than $'e_r=2^{-p}'$. The value of p is 27 for the single precision floating point, and 57 for the double precision floating point. Let $'X_i=\frac{1}{F}+e_i{'}$, these is $'X_{i+1}=\frac{1}{F}-e_{i+1},\;where\;{'}e_{i+1}, is less than the smallest number which is representable by floating point number. So, $X_{i+1}$ is approximate to $'\frac{1}{F}{'}$. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications per an operation is derived from many reciprocal tables $(X_0=\frac{1}{F}{\pm}e_0)$ with varying sizes. The superiority of this algorithm is proved by comparing this average number with the fixed number of multiplications of the conventional algorithm. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a reciprocal unit. Also, it can be used to construct optimized approximate reciprocal tables. The results of this paper can be applied to many areas that utilize floating point numbers, such as digital signal processing, computer graphics, multimedia scientific computing, etc.

STRONG CONVERGENCE OF AN ITERATIVE ALGORITHM FOR SYSTEMS OF VARIATIONAL INEQUALITIES AND FIXED POINT PROBLEMS IN q-UNIFORMLY SMOOTH BANACH SPACES

  • Jeong, Jae Ug
    • Korean Journal of Mathematics
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    • v.20 no.2
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    • pp.225-237
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    • 2012
  • In this paper, we introduce a new iterative scheme to investigate the problem of nding a common element of nonexpansive mappings and the set of solutions of generalized variational inequalities for a $k$-strict pseudo-contraction by relaxed extra-gradient methods. Strong convergence theorems are established in $q$-uniformly smooth Banach spaces.

Precision servo control of a computer hard disk (컴퓨터 하드 디스크의 정밀 서보 제어)

  • 전도영
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.286-289
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    • 1996
  • Two servo control algorithms are suggested to reduce the tracking error of a computer hard disk drive. One is the repetitive control to reduce the repeatable tracking error which is not explicitly taken into account in the design of a conventional controller. This algorithm was successfully applied to a commercial disk using a fixed point DSP. The other is the multi-rate sampling control which generates the control output between each sampling times since the sampling time of hard disk drives is limited. These algorithms were shown effectively to reduce tracking errors.

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Feature Extraction of Object Images by Using ICA-basis of Fixed-Point Algorithm (고정점 알고리즘의 ICA-basis에 의한 물체영상의 특징추출)

  • 조용현;홍성준
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.10a
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    • pp.90-93
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    • 2004
  • 본 논문에서는 고정점 알고리즘의 독립성분분석을 이용한 물체영상의 특징추출을 제안하였다. 여기서 고정점 알고리즘은 뉴우턴법에 기초한 것으로 빠른 특징추출성능을 얻기 위함이고, 독립성분분석의 이용은 통계적으로 독립인 기저영상을 효과적으로 추출하기 위함이다. 제안된 기법을 Image*after사에서 제공하는 352$\times$264 픽셀의 10개 물체영상을 대상으로 실험한 결과, 빠르면서도 정확한 복원성능과 PCA보다도 개선된 특징 추출성능이 있음을 확인하였다.

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SYSTEM OF GENERALIZED NONLINEAR REGULARIZED NONCONVEX VARIATIONAL INEQUALITIES

  • Salahuddin, Salahuddin
    • Korean Journal of Mathematics
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    • v.24 no.2
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    • pp.181-198
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    • 2016
  • In this work, we suggest a new system of generalized nonlinear regularized nonconvex variational inequalities in a real Hilbert space and establish an equivalence relation between this system and fixed point problems. By using the equivalence relation we suggest a new perturbed projection iterative algorithms with mixed errors for finding a solution set of system of generalized nonlinear regularized nonconvex variational inequalities.

ITERATIVE ALGORITHMS WITH ERRORS FOR NONEXPANSIVE MAPPINGS IN BANACH SPACES

  • Jung, Jong-Soo
    • Bulletin of the Korean Mathematical Society
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    • v.43 no.4
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    • pp.771-790
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    • 2006
  • The iterative algorithms with errors for nonexpansive mappings are investigated in Banach spaces. Strong convergence theorems for these algorithms are obtained. Our results improve the corresponding results in [5, 13-15, 23, 27-29, 32] as well as those in [1, 16, 19, 26] in framework of a Hilbert space.

A Study on the Estimation of Lane position using difference of Intensity (Intensity차를 이용한 차선의 위치 검출에 관한 연구)

  • 손경희;송현승;노도환
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.403-403
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    • 2000
  • Generally estimation of driving direction uses the way which uses lane detection and vanishing point in autonomous-driving system. Especially we use Sub-window for decreasing Process time when we detect lane, but fixed sub-window can not detect lane because of some factors in road image. So we suggest algorithm using one-dimension line scan method to detect an exact position of lane.

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THE NIELSEN NUMBER ON ASPHERICAL WEDGE

  • Kim, Seung Won
    • Journal of the Chungcheong Mathematical Society
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    • v.21 no.4
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    • pp.533-541
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    • 2008
  • Let X be a finite polyhedron that is of the homotopy type of the wedge of the torus and the surface with boundary. Let $f:X{\rightarrow}X$ be a self-map of X. In this paper, we prove that if the induced endomorphism of ${\pi}_1(X)$ is K-reduced, then there is an algorithm for computing the Nielsen number N(f).

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