• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.485-499
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• 2021

Although non-binary low-density parity-check (NB-LDPC) codes have better error-correction capability than that of binary LDPC codes, their decoding complexity is significantly higher. Therefore, it is crucial to reduce the decoding complexity of NB-LDPC while maintaining their error-correction capability to adopt them for various applications. The extended min-sum (EMS) algorithm is widely used for decoding NB-LDPC codes, and it reduces the complexity of check node (CN) operations via message truncation. Herein, we propose a low-cost CN processing method to reduce the complexity of CN operations, which take most of the decoding time. Unlike existing studies on low complexity CN operations, the proposed method employs quick selection algorithm, thereby reducing the hardware complexity and CN operation time. The experimental results show that the proposed selection-based CN operation is more than three times faster and achieves better error-correction performance than the conventional EMS algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.2
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• pp.140-145
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• 2013

This paper proposes the high speed LDPC decoder structure base on the DVB-S2. Firstly, We study the solution to avoid the memory conflict. For the high speed decoding process the decoder adapts the HSS(Horizontal Shuffle Scheduling) scheme. Secondly, for the high speed decoding algorithm normalized Min-Sum algorithm is adapted instead of Sum-Product algorithm. And the self corrected is a variant of the LDPC decoding that sets the reliability of a Mc${\rightarrow}$v message to 0 if there is an inconsistency between the signs of the current incoming messages Mv'${\rightarrow}$c and the sign of the previous incoming messages Moldv'${\rightarrow}$c This self-corrected algorithm avoids the propagation on unreliable information in the Tanner graph and thus, helps the convergence of the decoder.Start after striking space key 2 times. Lastly, and this paper propose the optimal hardware architecture supporting the high speed throughput.

• Korean Journal of Mathematics
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• v.16 no.3
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• pp.413-424
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• 2008

In [21], Th.M. Rassias proved that the norm defined over a real vector space V is induced by an inner product if and only if for a fixed integer $n{\geq}2$ $$n{\parallel}\frac{1}{n}\sum\limits_{i=1}^{n}x_i{\parallel}^2+\sum\limits_{i=1}^{n}{\parallel}x_i-\frac{1}{n}\sum\limits_{j=1}^{n}x_j{\parallel}^2=\sum\limits_{i=1}^{n}{\parallel}x_i{\parallel}^2$$ holds for all $x_1,{\dots},x_n{\in}V$. We consider the functional equation $$nf(\frac{1}{n}\sum\limits^n_{i=1}x_i)+\sum\limits_{i=1}^{n}f(x_i-\frac{1}{n}\sum\limits_{j=1}^{n}x_j)=\sum\limits_{i=1}^nf(x_i)$$ Using fixed point methods, we prove the generalized Hyers-Ulam stability of the functional equation $$(1)\;2f(\frac{x+y}{2})+f(\frac{x-y}{2})+f(\frac{y-x}{2})=f(x)+f(y)$$.

• Journal of the Chungcheong Mathematical Society
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• v.21 no.4
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• pp.455-466
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• 2008

In, [7], Th.M. Rassias proved that the norm defined over a real vector space V is induced by an inner product if and only if for a fixed integer $n{\geq}2$ $$n{\left\|{\frac{1}{n}}{\sum\limits_{i=1}^{n}}x_i{\left\|^2+{\sum\limits_{i=1}^{n}}\right\|}{x_i-{\frac{1}{n}}{\sum\limits_{j=1}^{n}x_j}}\right\|^2}={\sum\limits_{i=1}^{n}}{\parallel}x_i{\parallel}^2$$ holds for all $x_1,{\cdots},x_{n}{\in}V$. Let V,W be real vector spaces. It is shown that if a mapping $f:V{\rightarrow}W$ satisfies $$(0.1){\hspace{10}}nf{\left({\frac{1}{n}}{\sum\limits_{i=1}^{n}}x_i \right)}+{\sum\limits_{i=1}^{n}}f{\left({x_i-{\frac{1}{n}}{\sum\limits_{j=1}^{n}}x_i}\right)}\\{\hspace{140}}={\sum\limits_{i=1}^{n}}f(x_i)$$ for all $x_1$, ${\dots}$, $x_{n}{\in}V$ $$(0.2){\hspace{10}}2f\(\frac{x+y}{2}\)+f\(\frac{x-y}{2} \)+f\(\frac{y}{2}-x\)\\{\hspace{185}}=f(x)+f(y)$$ for all $x,y{\in}V$. Furthermore, we prove the generalized Hyers-Ulam stability of the functional equation (0.2) in real Banach spaces.

• Kyungpook Mathematical Journal
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• v.50 no.4
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• pp.465-472
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• 2010

In this paper, we consider two extreme sets of zero-term rank sum of fuzzy matrix pairs: $$\cal{z}_1(\cal{F})=\{(X,Y){\in}\cal{M}_{m,n}(\cal{F})^2{\mid}z(X+Y)=min\{z(X),z(Y)\}\};$$ $$\cal{z}_2(\cal{F})=\{(X,Y){\in}\cal{M}_{m,n}(\cal{F})^2{\mid}z(X+Y)=0\}$$. We characterize the linear operators that preserve these two extreme sets of zero-term rank sum of fuzzy matrix pairs.

• Bulletin of the Korean Mathematical Society
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• v.37 no.2
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• pp.209-215
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• 2000

Let X be a locally convex space. A series of clearcut characterizations for the boundedness of vector measure $\mu{\;}:{\;}\sum\rightarrow{\;}X$ is obtained, e.g., ${\mu}$ is bounded if and only if ${\mu}(A_j){\;}\rightarrow{\;}0$ weakly for every disjoint $\{A_j\}{\;}\subseteq{\;}\sum$ and if and only if $\{\frac{1}{j^j}{\mu}(A_j)\}^{\infty}_{j=1}$ is bounded for every disjoint $\{A_j\}{\;}\subseteq{\;}\sum$.

• Bulletin of the Korean Mathematical Society
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• v.59 no.6
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• pp.1339-1348
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• 2022

Let A = {a₁ < a₂ < ⋯} be a sequence of integers and let P(A) = {Σε_ia_i : a_i ∈ A, ε_i = 0 or 1, Σε_i < ∞}. Burr posed the following question: Determine conditions on integers sequence B that imply either the existence or the non-existence of A for which P(A) is the set of all non-negative integers not in B. In this paper, we focus on some problems of subset sum related to Burr's question.

• Korean Aquaculture
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• v.13 no.2
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• pp.32-37
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• 2001

• Korean Aquaculture
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• v.12 no.2
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• pp.23-28
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• 2000

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.8
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• pp.644-649
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• 2013

For effective DC-free coding in the optical storage systems, the Guided Scrambling algorithm is widely used. To reduce digital discrepancy of the coded sequence, functions of digital sum value (DSV) are used as criteria to choose the best candidate. Among these criteria, the minimum digital sum value (MDSV), minium squared weight (MSW), and minimum threshold overrun (MTO) are popular methods for effective DC-suppression. In this paper, we formulate integer programming models that are equivalent to MDSV, MSW, and MTO GS coding. Incorporating the MDSV integer programming model in MaxMin setting, we develop an integer programming model that computes the worst case MDSV bound given scrambling polynomial and control bit size. In the simulation, we compared the worst case MDSV bound for different scrambling polynomial and control bit sizes. We find that careful selection of scrambling polynomial and control bit size are important factor to guarantee the worst case MDSV performance.