• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1129-1132
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• 1998

This paper presents a design of special hardware developed for enhancing the floating-point power operations which are actively used at the lighting stage to calculate the specular term in 3D graphics geometry engines. The power operation takes just 4 cycles in our floating-point multiplier while it takes about 100-200 cycles in conventional floating-point units. Although an approximation algorithm is employed in the power operation to reduce the hardware complexity required, the error of power value from the developed floatingpoint multiplier is so minimal that no difference can be found by human eyes.

• Journal of applied mathematics & informatics
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• v.4 no.1
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• pp.211-222
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• 1997

In this paper we present a probabilistic approach for the estimation of realistic error bounds appearing in the execution of basic algebraic floating point operations. Experimental results are carried out for the extended product the extended sum the inner product of random normalised numbers the product of random normalised ma-trices and the solution of lower triangular systems The ordinary and probabilistic bounds are calculated for all the above processes and gen-erally in all the executed examples the probabilistic bounds are much more realistic.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.47-50
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• 2001

Nowadays ARM7 core is used in many fields such as PDA systems because of the low power and low cost. It is a general-purpose processor, designed for both efficient digital signal processing and controller operations. But the advent of the wireless communication creates a need for high computational performance for signal processing. And then This paper has been designed a floating-point multiplier compatible to IEEE-754 single precision format for ARMTTDMI performance improvement.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.1
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• pp.45-51
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• 2018

In this paper, a tentative Kth order Newton-Raphson's floating point number Nth root algorithm for K order convergence rate in one iteration is proposed by applying Taylor series to the Newton-Raphson root algorithm. Using the proposed algorithm, $F^{-1/N}$ and $F^{-(N-1)/N}$ can be computed from iterative multiplications without division. It also predicts the error of the algorithm iteration and iterates only until the predicted error becomes smaller than the specified value. 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 floating point number Nth root unit.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.778-780
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• 1999

Arithmetic unit speed depends strongly on the algorithms employed to realize the basic arithmetic operations.(add, subtract multiply, and divide) and on the logic design. Recent advances in VLSI have increased the feasibility of hardware implementation of floating point arithmetic units and microprocessors require a powerful floating-point processing unit as a standard option. This paper describes the design of floating-point multiplier for IEEE 754-1985 Single-Precision operation. Booth encoding algorithm method to reduce partial products and a Wallace tree of 4-2 CSA is adopted in fraction multiplication part to generate the $32{\times}32$ single-precision product. New scheme of rounding and sticky-bit generation is adopted to reduce area and timing. Also there is a true sign generator in this design. This multiplier have been implemented in a ALTERA FLEX EPF10K70RC240-4.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.3
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• pp.24-30
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• 1995

The process of conventional floating-point additio $n_traction operation consists of alignment, additio $n_traction, normalization, and rounding stage. Because rounding stage needs an incrementor or adder, it occupies much time and chip area. In addition, it needs additional time and hardware for renormalization which occurs in overflow due to rounding In this paper, floating-point adde $r_tractor performing rounding and additio $n_traction in parallel is presented by using the feature of additio $n_traction and carry select adder used in additio $n_tracting stage. Proposed floating point adde $r_tractor doesn't need time and incrementor nor adder for rounding. Also, renormalization doesn't occur since rounding is performed prior to normalization.to normalization.

• Journal of Korea Multimedia Society
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• v.22 no.9
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• pp.1029-1035
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• 2019

In this paper, a tentative Kth order Goldschmidt floating point number Nth root algorithm for K order convergence rate in one iteration is proposed by applying Taylor series to the Goldschmidt square root algorithm. Using the proposed algorithm, Nth root and Nth inverse root can be computed from iterative multiplications without division. It also predicts the error of the algorithm iteration. It iterates until the predicted error becomes smaller than the specified value. 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 floating point number Nth root unit.

• Journal of the Korean Society of Systems Engineering
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• v.17 no.2
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• pp.37-48
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• 2021

Improving the plant protection system against unforeseen changes/transients during operation is essential to maintain plant safety. Under this condition, it requires rapid and accurate signal processing. The use of an Intellectual Property (IP) core for floating point calculations for Safety Critical MMIS can make numerical computations easier and more precise, improving system accuracy. It can represent and manipulate rational numbers as well as a much broader range of values with dynamic range in nuclear power plant. Systems engineering approach (SE) is used through the development process, it helps to reduce complexity and avoid omissions and invalid assumptions as delivers a better understanding of the stakeholders needs. For the implementation on the FPGA target board, the 32-bit floating-point arithmetic with IEEE-754 standards has designed using Simulink model in Matlab for all operations of addition, subtraction, multiplication and division and VHDL code generated.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.10
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• pp.72-81
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• 2011

In this paper, we proposed and designed a novel floating point converter which supports single and double precisions of IEEE754 standard. The proposed convertor supports conversions between floating point number single/double precision and signed fixed point number(32bits/64bits) as well as conversions between signed integer(32bits/64bits) and floating point number single/double precision and conversions between floating point number single and double precisions. We defined a new internal format to convert various input types into one type so that overflow checking could be conducted easily according to range of output types. The internal format is similar to the extended format of floating point double precision defined in IEEE754 2008 standard. This standard specifies that minimum exponent bit-width of the extended format of floating point double precision is 15bits, but 11bits are enough to implement the proposed converting unit. Also, we optimized rounding stage of the convertor unit so that we could make it possible to operate rounding and represent correct negative numbers using an incrementer instead an adder. We designed single cycle data path and 5 cycles data path. After describing the HDL model for two data paths of the convertor, we synthesized them with TSMC 180nm technology library using Synopsys design compiler. Cell area of synthesis result occupies 12,886 gates(2 input NAND gate), and maximum operating frequency is 411MHz.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.8
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• pp.1593-1600
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• 2009

There are two major algorithms to find a square root of floating point number, one is the Newton_Raphson algorithm and GoldSchmidt algorithm which calculate it approximately by iterating multiplications and the other is SRT algorithm which calculates it exactly by iterating subtractions. This paper proposes an exact floating point square root algorithm using only multiplication. At first an approximate inverse square root is calculated by Newton_Raphson algorithm, and then an exact square root algorithm by reducing an error in it and a compensation algorithm of it are proposed. The proposed algorithm is verified to calculate all of numbers in a single precision floating point number and 1 billion random numbers in a double precision floating point number. The proposed algorithm requires only the multipliers without another hardware, so it can be widely used in an embedded system and mobile production which requires an efact square root of floating point number.