• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.312-320
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• 2021

Increase in computational cost and exhaustive search can lead to more complexity and computational energy. Thus, there is need for effective and efficient scheme to reduce the complexity to achieve optimal energy utilization. This will improve the energy efficiency and enhance the proficiency in terms of the resources needed to achieve convergence. This paper primarily focuses on the development of hybrid swarm intelligence scheme for reducing the computational complexity in binary optimization. In order to reduce the complexity, both artificial bee colony (ABC) and particle swarm optimization (PSO) have been employed to effectively minimize the exhaustive search and increase convergence. First, a new approach using ABC and PSO has been proposed and developed to solve the binary optimization problem. Second, the scout for good quality food sources is accomplished through the deployment of PSO in order to optimally search and explore the best source. Extensive experimental simulations conducted have demonstrate that the proposed scheme outperforms the ABC approaches for reducing complexity and energy consumption in terms of convergence, search and error minimization performance measures.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.221-224
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• 2005

In this paper, we propose a fast video mixing method for reducing the computational complexity in the MCU (Multipoint Control Unit) used in the video conferencing. The conventional mixing method is based on the pixeldomain transcoder, of which computational complexity is linearly increased as the number of participants is increased. Basically the method requires N decoders and one huge encoder to mix the bitstreams from the N participants. To reduce the computational complexity, we propose a hybrid mixing method based on the bitstreamdomain and pixel-domain transcoding methods. The proposed method reduces the computational complexity about 45% at the improved quality, compared with the conventional mixing method based on the pixel-domain transcoders.

• ETRI Journal
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• v.27 no.5
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• pp.639-642
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• 2005

This paper proposes two kinds of complexity-reduced algorithms for a low density parity check (LDPC) decoder. First, sequential decoding using a partial group is proposed. It has the same hardware complexity and requires a fewer number of iterations with little performance loss. The amount of performance loss can be determined by the designer, based on a tradeoff with the desired reduction in complexity. Second, an early detection method for reducing the computational complexity is proposed. Using a confidence criterion, some bit nodes and check node edges are detected early on during decoding. Once the edges are detected, no further iteration is required; thus early detection reduces the computational complexity.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1187-1190
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• 1998

In this paper we propose a new efficient generalized sidelobe canceller(GSC) algorithm, using the efficient frequency domain LMS algorithm, which has much less weights to update. We only update part of all the weights according to magnitude of each frequency bin. So, the new proposed GSC algorithm, which is called censored GSC(C-GSC), can greatly reduce the computational complexity.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.45-48
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• 2005

In this paper, we propose a new fast running FIR filter structure that improves the convergence speed of adaptive signal processing and reduces the computational complexity. The proposed filter is applied to wavelet based adaptive algorithm. Actually we compared the performance of the proposed algorithm with other algorithm using computer simulation of adaptive noise canceler based on synthesis speech. As the result, We know the proposed algorithm is prefer than the existent algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1109-1122
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• 1996

Generally, moving images contain the various components in motions, which reange from a static object and background to a fast moving object. To extract the accurate motion parameters, we must consider the various motions. That requires a wide search egion in motion estimation. The wide search, however, causes a high computational complexity. If we have a few knowledge about the motion direction and magnitude before motion estimation, we can determine the search location and search window size using the already-known information about the motion. In this paper, we present a local adaptive motion estimation approach that predicts a block motion based on spatio-temporal neighborhood blocks and adaptively defines the search location and search window size. This paper presents a technique for reducing computational complexity, while having high accuracy in motion estimation. The proposed algorithm is introduced the forward and backward projection techniques. The search windeo size for a block is adaptively determined by previous motion vectors and prediction errors. Simulations show significant improvements in the qualities of the motion compensated images and in the reduction of the computational complexity.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.54-60
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• 2021

Monte-Carlo GO is a computer GO program that is sufficiently competent without using knowledge expressions of IGO. Although it is computationally intensive, the computational complexity can be reduced by properly pruning the IGO game tree. Here, I achieve this by using a potential model based on the knowledge expressions of IGO. The potential model treats GO stones as potentials. A specific potential distribution on the GO board results from a unique arrangement of stones on the board. Pruning using the potential model categorizes legal moves into effective and ineffective moves in accordance with the potential threshold. Here, certain pruning strategies based on potentials and potential gradients are experimentally evaluated. For different-sized boards, including an official-sized board, the effects of pruning strategies are evaluated in terms of their robustness. I successfully demonstrate pruning using a potential model to reduce the computational complexity of GO as well as the robustness of this effect across different-sized boards.

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.637-645
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• 2006

An adaptive algorithm for reducing the hardware complexity is presented. This paper proposes a simplified LMS algorithm for the adaptive system and analyzes its convergence characteristics mathematically. An objective of the proposed algorithm is to reduce the hardware complexity. In order to test the performances, it is applied to the echo canceller, and a program is described. The results from simulations show that the echo canceller adopting the proposed algorithm achieves almost the same performances as one adopting the NLMS algorithm. If an echo canceller is implemented with this algorithm, its computation quantities are reduced to the half as many as the one that is implemented with the LMS algorithm, without so much degradation of performances.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.10 s.101
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• pp.965-972
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• 2005

In this paper, we first review LDPC codes in general and a belief propagation algorithm that works in logarithm domain. LDPC codes, which is chosen for second generation digital video broadcasting standard, are required a large number of computation due to large size of coded block and iteration. Therefore, we presented two kinds of low computational algorithm for LDPC codes. First, sequential decoding with partial group is proposed. It has same H/W complexity, and fewer number of iteration's are required at same performance in comparison with conventional decoder algerian. Secondly, early detection method for reducing the computational complexity is proposed. Using a confidence criterion, some bit nodes and check node edges are detected early on during decoding. Through the simulation, we knew that the iteration number are reduced by half using subset algorithm and computational complexity of early detected method is about $50\%$ offs in case of check node update, $99\%$ offs in case of check node update compared to conventional scheme.

• Journal of applied mathematics & informatics
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• v.31 no.5_6
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• pp.785-794
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• 2013

Soon after Lee and O'Sullivan proposed a new interpolation algorithm for algebraic soft-decision decoding of Reed-Solomon codes, there have been some attempts to apply a coordinate transformation technique to the new algorithm, with a remarkable complexity reducing effect. In this paper, a conceptually simple way of applying the transformation technique to the interpolation algorithm is proposed.