• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.2
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• pp.428-431
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• 2007

A floating-point number system is used to represent a wide range of real numbers using finite number of bits. The standard the IEEE adopted in 1987 divides the range of real numbers into intervals of [$2^E,2^{E+1}$), where E is an Integer represented with finite bits, and defines equally spaced equal counts of discrete numbers in each interval. Since the numbers are defined discretely, not only the number representation itself includes errors but in floating-point arithmetic some strange behaviors are observed which cannot be agreed with the real world arithmetic. In this paper errors with floating-point number representation, those with arithmetic operations, and those due to order of arithmetic operations are analyzed theoretically with help of and verification with the results of some MATLAB program executions.

• Journal of Applied Reliability
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• v.14 no.2
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• pp.103-107
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• 2014

An algorithm to get network reliability, where each link has probability of fuzzy number, is proposed. Decomposition method and fuzzy numbers arithmetic are applied to the algorithm. Pivot link is chosen one by one from start node recursively at time of decomposition, and arithmetic of fuzzy complementary numbers is included at the same time. No criteria of pivot link selection and the recursive calculation make the algorithm simple.

• School Mathematics
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• v.5 no.2
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• pp.167-189
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• 2003

Mental arithmetic has recently gained a higher profile in primary school mathematics. The study aims to reflect didactical background of mental arithmetic in number and operations curriculum for primary school mathematics. In order to attain these purposes, the present paper describes the meaning of mathematical literacy and didactical background of mental arithmetic on which have been laid emphasis in relation to mathematical literacy in many countries. Also it shows current suggestions for mental arithmetic instruction in Everyday Mathematics Project in USA, Numeracy Number Project in Great Britain, TAL project based on Realistic Mathematics Education in the Netherlands, and mathe 2000 project in German in order to gain practical ideas for teaching mental arithmetic. Furthermore, it discusses mental strategies of students and didactical models for improving mental arithmetic instruction based on the results of many researches. Under these theoretical foundations, it is analyzed how mental arithmetic is developed in our number and operations curriculum, focused on mental strategies and didactical models. Finally, implications for improving our mental arithmetic instruction are discussed.

• Journal for History of Mathematics
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• v.12 no.2
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• pp.47-54
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• 1999

We introduce some historical facts on number theory, especially prime numbers and modular arithmetic. And then, with the viewpoint of computer arithmetic, residue number systems are considered as an alternate to positional number systems so that high performance and high speed computation can be achieved in a specified domain such as cryptography and digital signal processing.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.1-4
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• 2002

There have been several tipical methods being used to measure the fuzziness (entropy) of fuzzy sets. Pedrycz is the original motivation of this paper. This paper studies the entropy variation on the fuzzy numbers with arithmetic operations(addition, subtraction, multiplication) and the relationship between entropy and information energy. It is shown that through the arithmetic operations, the entropy of the resultant fuzzy number has the arithmetic relation with the entropy of each original fuzzy number. Moreover, the information energy variation on the fuzzy numbers is also discussed. The results generalize earlier results of Pedrycz [FSS 64(1994) 21-30] and Wang and Chiu [FSS 103(1999) 443-455].

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.12
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• pp.1928-1934
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• 1993

This paper presents a fast algorithm of integer discrete cosine transform(IDCT) allowing VLSI implementation by integer arithmetic. The proposed fast algorithm has been developed using Chen`s matrix decomposition in DCT, and requires less number of arithmetic operations compared to the IDCT. In the presented algorithm, the number of addition number is the same as the one of Chen`s algorithm if DCT, and the number of multiplication if the same as that in DCT at N=8 but drastically decreasing when N is above 8. In addition, the drawbacks of DCT such as performance degradation at the finite length arithmetic could be overcome by the IDCT.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.429-438
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• 2006

Neural Networks(NNs) are applied for solving a wide variety of nonlinear problems in several areas, such as image processing, pattern recognition etc. Although NN can be simulated by using software, many potential NN applications required real-time processing. Thus they need to be implemented as hardware. The hardware implementation of multi-layer perceptrons(MLPs) in several kind of NNs usually uses a fixed-point arithmetic due to a simple logic operation and a shorter processing time compared to the floating-point arithmetic. However, the fixed-point arithmetic-based MLP has a drawback which is not able to apply the MLP software that use floating-point arithmetic. We propose a design method for MLPs which has the floating-point arithmetic-based fully-pipelining architecture. It has a processing speed that is proportional to the number of the hidden nodes. The number of input and output nodes of MLPs are generally constrained by given problems, but the number of hidden nodes can be optimized by user experiences. Thus our design method is using optimized number of hidden nodes in order to improve the processing speed, especially in field of a repeated processing such as image processing, pattern recognition, etc.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.1
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• pp.147-156
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• 1998

In this paper, an arithmetic processor using multi-valued logic is designed. For implementing of multi-valued logic circuits, we use current-mode CMOS circuits and design encoder which change binary voltage-mode signals to multi-valued current-mode signals and decoder which change results of arithmetic to binary voltage-mode signals. To reduce the number of partial product we use 4-radix SD number partial product generation algorithm that is an extension of the modified Booth's algorithm. We demonstrate the effectiveness of the proposed arithmetic circuits through SPICE simulation and Hardware emulation using FPGA chip.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2876-2878
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• 1999

There have been several tipical methods being used to measure the fuzziness (entropy) of fuzzy sets. Pedrycz is the original motivation of this paper. This paper studies the entropy variation on the fuzzy numbers with arithmetic operations(addition, subtraction, multiplication). It is shown that through the arithmetic operations, the entropy of the resultant fuzzy number has the arithmetic relation with the entropy of each original fuzzy number. This paper generalize earlier results of Pedrycz [FSS 64(1994) 21-30] and Wang and Chiu [FSS 103(1999) 443-455].

• The Mathematical Education
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• v.40 no.2
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• pp.335-343
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• 2001

Algebra is important part of mathematics education. Recent days, many mathematics educators emphasize on real world situation. Form real situation, pupils make sense of concepts, and mathematize it by reflective thinking. After that they formalize the concepts in abstract. For example, operation in numbers develops these course. Operation in natural number is an arithmetic, but operation on real number is algebra. Transition from arithmetic to algebra has the cutting point in representing the concepts to mathematics sign system. In this note, we see the cognitive tendency of 10th grade about operation of real number, their cutting point of transition from arithmetic to algebra, and show some methods of helping pupils.