• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2680-2700
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• 2017

Finite field arithmetic over GF($2^m$) is used in a variety of applications such as cryptography, coding theory, computer algebra. It is mainly used in various cryptographic algorithms such as the Elliptic Curve Cryptography (ECC), Advanced Encryption Standard (AES), Twofish etc. The multiplication in a finite field is considered as highly complex and resource consuming operation in such applications. Many algorithms and architectures are proposed in the literature to obtain efficient multiplication operation in both hardware and software. In this paper, a modified serial multiplication algorithm with interleaved modular reduction is proposed, which allows for an efficient realization of a sequential polynomial basis multiplier. The proposed sequential multiplier supports multiplication of any two arbitrary finite field elements over GF($2^m$) for generic irreducible polynomials, therefore made versatile. Estimation of area and time complexities of the proposed sequential multiplier is performed and comparison with existing sequential multipliers is presented. The proposed sequential multiplier achieves 50% reduction in area-delay product over the best of existing sequential multipliers for m = 163, indicating an efficient design in terms of both area and delay. The Application Specific Integrated Circuit (ASIC) and the Field Programmable Gate Array (FPGA) implementation results indicate a significantly less power-delay and area-delay products of the proposed sequential multiplier over existing multipliers.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.741-744
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• 1999

In this paper, We represent a low complexity of parallel canonical basis multiplier for GF( q$^{n}$ ), ( q＞ 2). The Mastrovito multiplier is investigated and applied to multiplication in GF(q$^{n}$ ), GF(q$^{n}$ ) is different with GF(2$^{n}$ ), when MVL is applied to finite field. If q is larger than 2, inverse should be considered. Optimized irreducible polynomial can reduce number of operation. In this paper we describe a method for choosing optimized irreducible polynomial and modularizing recursive polynomial operation. A optimized irreducible polynomial is provided which perform modulo reduction with low complexity. As a result, multiplier for fields GF(q$^{n}$ ) with low gate counts. and low delays are constructed. The architectures are highly modular and thus well suited for VLSI implementation.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.6
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• pp.3-15
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• 2009

Recently, Wu proposed a three small classes of finite fields $F_{2^n}$ for low-complexity bit-parallel multipliers. The proposed multipliers have low-complexities compared with those based on the irreducible pentanomials. In this paper, we propose a new Repeated Polynomial(RP) for low-complexity bit-parallel multipliers over $F_{2^n}$. Also, three classes of Irreducible Repeated polynomials are considered which are denoted, respectively, by case 1, case 2 and case3. The proposed RP bit-parallel multiplier has lower complexities than ones based on pentanomials. If we consider finite fields that have neither a ESP nor a trinomial as an irreducible polynomial when $n\leq1,000$. Then, in Wu''s result, only 11 finite fields exist for three types of irreducible polynomials when $n\leq1,000$. However, in our result, there are 181, 232, and 443 finite fields of case 1, 2 and 3, respectively.

• ETRI Journal
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• v.26 no.3
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• pp.241-251
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• 2004

We propose two improved scalar multiplication methods on elliptic curves over $F_{{q}^{n}}$ $q= 2^{m}$ using Frobenius expansion. The scalar multiplication of elliptic curves defined over subfield $F_q$ can be sped up by Frobenius expansion. Previous methods are restricted to the case of a small m. However, when m is small, it is hard to find curves having good cryptographic properties. Our methods are suitable for curves defined over medium-sized fields, that is, $10{\leq}m{\leq}20$. These methods are variants of the conventional multiple-base binary (MBB) method combined with the window method. One of our methods is for a polynomial basis representation with software implementation, and the other is for a normal basis representation with hardware implementation. Our software experiment shows that it is about 10% faster than the MBB method, which also uses Frobenius expansion, and about 20% faster than the Montgomery method, which is the fastest general method in polynomial basis implementation.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.451-452
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• 2007

본 논문에서는 다항식 기반 Radial Basis Function(RBF)신경회로망(Polynomial based Radial Basis Function Neural Networks)을 설계하고 이를 2-클래스 패턴 분류 문제에 응용하여 그 성능을 분석한다. 제안된 다항식기반 RBF 신경회로망은 입력층, 은닉층, 출력 층으로 이루어진다. 입력층은 입력 벡터의 값들을 은닉 층으로 전달하는 기능을 수행하고 은닉층은 Fuzzy c-means 클러스터링을 통하여 뉴런의 출력 값으로 내보낸다. 은닉층과 출력층사이의 연결가중치는 상수, 선형식 또는 이차식으로 이루어지며 경사 하강법에 의해 학습된다. Networks의 최종 출력은 연결가중치와 은닉층 출력의 곱에 의해 퍼지추론의 결과로서 얻어진다. 제안된 다항식기반 RBF 신경회로망은 각기 다른 4종류의 2-클래스 분류 문제에 적용 및 평가되어 분류기로써의 성능을 분석한다.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1015-1027
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• 2009

Many problems of confounding and identifiability for polynomial models in an experimental design can be solved using methods of algebraic geometry. The theory of $Gr\ddot{o}bner$ basis is used to characterize the design. In addition, a fractional factorial design can be uniquely represented by a polynomial indicator function. $Gr\ddot{o}bner$ bases and indicator functions are powerful computational tools to deal with ideals of fractions based on each different theoretical aspects. The problem posed here is to give how to move from one representation to the other. For a given fractional factorial design, the indicator function can be computed from the generating equations in the $Gr\ddot{o}bner$ basis. The theory is tested using some fractional factorial designs aided by a modern computational algebra package CoCoA.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.3
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• pp.41-48
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• 2004

Finite field multiplication and division are important arithmetic operation in error-correcting codes and cryptosystems. The elements of the finite field GF($2^m$) are represented by bases with a primitive polynomial of degree m over GF(2). We can be easily realized for multiplication or computing multiplicative inverse in GF($2^m$) based on a normal basis representation. The number of product terms of logic function determines a complexity of the Messay-Omura multiplier. A normal basis exists for every finite field. It is not easy to find the optimal normal element for a given primitive polynomial. In this paper, the generating method of normal basis is investigated. The normal bases whose product terms are less than other bases for multiplication in GF($2^m$) are found. For each primitive polynomial, a list of normal elements and number of product terms are presented.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.4
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• pp.544-553
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• 2013

In this paper, we propose the pattern classifier of Radial Basis Function Neural Networks(RBFNNs) for diagnosis of 3-phase partial discharge. Conventional methods map the partial discharge/noise data on 3-PARD map, and decide whether the partial discharge occurs or not from 3-phase or neutral point. However, it is decided based on his own subjective knowledge of skilled experter. In order to solve these problems, the mapping of data as well as the classification of phases are considered by using the general 3-PARD map and PA method, and the identification of phases occurring partial discharge/noise discharge is done. In the sequel, the type of partial discharge occurring on arbitrary random phase is classified and identified by fuzzy clustering-based polynomial Radial Basis Function Neural Networks(RBFNN) classifier. And by identifying the learning rate, momentum coefficient, and fuzzification coefficient of FCM fuzzy clustering with the aid of PSO algorithm, the RBFNN classifier is optimized. The virtual simulated data and the experimental data acquired from practical field are used for performance estimation of 3-phase partial discharge pattern classifier.

• Bulletin of the Korean Mathematical Society
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• v.54 no.1
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• pp.1-15
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• 2017

Kanenobu has given infinite families of knots with the same HOMFLY polynomial invariant but distinct Alexander module structure. In this paper, we give a recursive formula for the Khovanov cohomology of all Kanenobu knots K(p, q), where p and q are integers. The result implies that the rank of the Khovanov cohomology of K(p, q) is an invariant of p + q. Our computation uses only the basic long exact sequence in knot homology and some results on homologically thin knots.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.3
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• pp.145-151
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• 2003

This study focuses on the hardware implementation of fast and low-complexity multiplier over GF(2$^{m}$ ). Finite field multiplication can be realized in two steps: polynomial multiplication and modular reduction using the irreducible polynomial and we will treat both operation, separately. Polynomial multiplicative operation in this Paper is based on the Permestzi's algorithm, and irreducible polynomial is defined AOP. The realization of the proposed GF(2$^{m}$ ) multipleker-based multiplier scheme is compared to existing multiplier designs in terms of circuit complexity and operation delay time. Proposed multiplier obtained have low circuit complexity and delay time, and the interconnections of the circuit are regular, well-suited for VLSI realization.