• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제11권11호
• /
• pp.5491-5505
• /
• 2017

Use of the Gaussian inverse Wishart PHD (GIW-PHD) filter has demonstrated promise as an approach to track an unknown number of extended targets. However, the partitioning approaches used in the GIW-PHD filter, such as distance partition with sub-partition (DP-SP), prediction partition (PP) and expectation maximization partition (EMP), fails to provided accurate partition results when targets are spaced closely together and performing maneuvers. In order to improve the performance of a GIW-PHD filter, this paper presents a cooperation partitioning (CP) algorithm to solve the partitioning issue when targets are spaced closely together. In the GIW-PHD filter, the DP-SP is insensitive to target maneuvers but sensitive to the differences in target sizes, while EMP is the opposite. The proposed CP algorithm is a fusion approach of DP-SP and EMP, which employs EMP as a sub-partition approach after DP. Therefore, the CP algorithm will be sensitive to neither target maneuvers nor differences in target sizes. The simulation results show that the use of the proposed CP algorithm will improve the performance of the GIW-PHD filter when targets are spaced closely together.

• 한국멀티미디어학회논문지
• /
• 제17권9호
• /
• pp.1064-1069
• /
• 2014

In this paper, we propose a novel approach to improve the performance of a voice activity detection(VAD) which is based on the adaptive band-partitioning with the likelihood ratio(LR). The previous method based on the adaptive band-partitioning use the weights that are derived from the variance of the spectral. In our VAD algorithm, the weights are derived from LR, and then the weights are incorporated with the entropy. The proposed algorithm discriminates the voice activity by comparing the weighted entropy with the adaptive threshold. Experimental results show that the proposed algorithm yields better results compared to the conventional VAD algorithms. Especially, the proposed algorithm shows superior improvement in non-stationary noise environments.

• 한국CDE학회논문집
• /
• 제14권4호
• /
• pp.217-224
• /
• 2009

Most divide-and-conquer implementations for Delaunay triangulation utilize quad-edge or winged-edge data structure since triangles are frequently deleted and created during the merge process. How-ever, the proposed divide-and-conquer algorithm utilizes the array based data structure that is much simpler than the quad-edge data structure and requires less memory allocation. The proposed algorithm has two important features. Firstly, the information of space partitioning is represented as a permutation vector sequence in a vertices array, thus no additional data is required for the space partitioning. The permutation vector represents adaptively divided regions in two dimensions. The two-dimensional partitioning of the space is more efficient than one-dimensional partitioning in the merge process. Secondly, there is no deletion of edge in merge process and thus no bookkeeping of complex intermediate state for topology change is necessary. The algorithm is described in a compact manner with the proposed data structures and operators so that it can be easily implemented with computational efficiency.

• Computers and Concrete
• /
• 제23권5호
• /
• pp.311-320
• /
• 2019

The substructuring technique is one of the efficient methods for reducing computational effort and memory usage in the finite element method, especially in large-scale structures. Proper mesh partitioning plays a key role in the efficiency of the technique. In this study, new algorithms are proposed for mesh partitioning based on an element search technique. The computational cost function is optimized by aligning each element of the structure to a proper substructure. The genetic algorithm is employed to minimize the boundary nodes of the substructures. Since the boundary nodes have a vital performance on the mesh partitioning, different strategies are proposed for the few number of substructures and higher number ones. The mesh partitioning is optimized considering both computational and memory requirements. The efficiency and robustness of the proposed algorithms is demonstrated in numerous examples for different size of substructures.

• 융합신호처리학회논문지
• /
• 제4권4호
• /
• pp.7-14
• /
• 2003

EZW(Embedded Zerotree Wavelet) 알고리즘이 소개된 이래 일련의 내장형 웨이브렛 코딩 방법들이 제안되어져왔다. 이들의 하나의 공통된 특징은 EZW 알고리즘의 기본 아이디어를 근간으로 한다는 점이다. 특히 SPIHT(Set Partitioning in Hierarchy Trees) 알고리즘은 이들 중의 하나로서 산술 코더를 사용하지 않더라도 EZW와 같거나 혹은 더 나은 성능을 제공할 수 있기 때문에 널리 알려져 왔다. 본 연구에서는 내장형 영상코딩을 위한 재귀적 SPIHT(RSPIHT) 알고리즘을 제안하고 그 유효성을 실험적으로 가한다. 제안한 RSPIHT 알고리즘은 매우 단순하고 정형화된 형태를 지니면서 최악의 경우 시간복잡도 O(n)을 가진다. 실험영상들에 대해 T-layer 4 이상에서 SPIHT보다 평균 약 16.4%의 개선된 속도를 얻을 수 있었다. 압축률의 관점에서도 RSPIHT 알고리즘은 실험영상의 T-layer 7 이하에서는 SPIHT와 유사한 결과를 가지나 그보다 큰 T-layer에서는 개선된 결과를 보였다.

• 한국멀티미디어학회논문지
• /
• 제13권5호
• /
• pp.763-770
• /
• 2010

본 논문은 무리 짓기에서 공간분할 방법의 성능을 개선하는 알고리즘을 제안한다. 무리 짓기에서 여러 특성중의 하나는 두 에이전트가 공간적으로 가깝게 있다면 많은 공동 이웃들을 공유한다는 것이다. 본 논문은 이 특성을 적용하여 공간분할 방법을 개선한다. 기존의 공간분할 방법이 한 번에 하나의 에이전트에 대한 k개의 가장 가까운 이웃 에이전트들을 찾는 것에 반하여, 제안하는 방법은 에이전트들이 공간적으로 가까이 있다면 그들에 대하여 동시에 k개의 가장 가까운 이웃 에이전트들을 계산한다. 제안된 알고리즘은 구현되었으며, 그것의 성능은 기존의 공간분할 방법과 실험적으로 비교되었다. 비교의 결과로부터 제안하는 알고리즘이 기존의 방법을 평균적으로 33%정도 개선한다는 것을 알 수 있었다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제6권4호
• /
• pp.1188-1202
• /
• 2012

In this paper, we propose a new multi-scale connected coherence tree algorithm (MCCTA) by improving the connected coherence tree algorithm (CCTA). In contrast to many multi-scale image processing algorithms, MCCTA works on multiple scales space of an image and can adaptively change the parameters to capture the coarse and fine level details. Furthermore, we design a Multi-scale Connected Coherence Tree algorithm plus Spectral graph partitioning (MCCTSGP) by combining MCCTA and Spectral graph partitioning in to a new framework. Specifically, the graph nodes are the regions produced by CCTA and the image pixels, and the weights are the affinities between nodes. Then we run a spectral graph partitioning algorithm to partition on the graph which can consider the information both from pixels and regions to improve the quality of segments for providing image segmentation. The experimental results on Berkeley image database demonstrate the accuracy of our algorithm as compared to existing popular methods.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2003년도 하계종합학술대회 논문집 II
• /
• pp.823-826
• /
• 2003

FPGA-based logic emulator with lane gate capacity generally comprises a large number of FPGAs connected in mesh or crossbar topology. However, gate utilization of FPGAs and speed of emulation are limited by the number of signal pins among FPGAs and the interconnection architecture of the logic emulator. The time-multiplexing of interconnection wires is required for multi-FPGA system incorporating several state-of-the-art FPGAs. This paper proposes a circuit partitioning algorithm called SCATOMi(SCheduling driven Algorithm for TOMi)for multi-FPGA system incorporating four to eight FPGAs where FPGAs are interconnected through TOMi(Time-multiplexed, Off-chip, Multicasting interconnection). SCATOMi improves the performance of TOMi architecture by limiting the number of inter-FPGA signal transfers on the critical path and considering the scheduling of inter-FPGA signal transfers. The performance of the partitioning result of SCATOMi is 5.5 times faster than traditional partitioning algorithms. Architecture comparison show that the pin count is reduced to 15.2%-81.3% while the critical path delay is reduced to 46.1%-67.6% compared to traditional architectures.

• 한국정보과학회논문지:데이타베이스
• /
• 제28권3호
• /
• pp.315-323
• /
• 2001

사용자의 질의 요청을 보다 빨리 지원하고 시스템 전체 처리량을 증가시키기 위한 하나의 방법으로 데이터 스키마의 수직 분할 문제가 많이 연구되어 왔다. 수직 분할의 대표적인 응 용 예로는 중앙 집중 시스템에서의 파일 분할, 분산 데이터베이스에서의 데이터 분산, 메모 리 계층사이의 데이터 분할 등이 있다. 일반적으로 수직 분할 알고리즘은 모든 유용한 단편 들의 생성과 임의 분할 지원 등의 두가지 기능을 효율적으로 지원할 수 있어야 한다. 그러 나, 기존의 제안된 방법들은 대부분 첫 번째 기능에 중점을 두고 있어 임의 분할 기능을 지 원하는데 많은 제한이 있다. 그리고 수직 분할 알고리즘에서 데이터 속성들이 포함될 단편 을 결정할 때 기본적으로 모호성 문제를 가지고 있기 때문에 이에 대한 효과적인 처리가 필 요하다. 본 논문에서는 퍼지 이론에 기반한 효율적인 수직 $\alpha$-분할 알고리즘을 제안한다. 이 방법은 퍼지 그래프 이론을 바탕으로 수직 분할에서의 모호성 문제를 해결하여 복잡한 수학적 계산 없이 모든 유용한 단편들을 생성할 수 있다. 또한, 범용 임의 분할 기능도 효과 적으로 지원할 수 있다.

• ETRI Journal
• /
• 제24권6호
• /
• pp.473-476
• /
• 2002

This letter proposes an efficient kernel-based partitioning algorithm for reducing area and power dissipation in combinational circuit designs using don't-care sets. The proposed algorithm decreases power dissipation by partitioning a given circuit using a kernel extracted from the logic. The proposed algorithm also reduces the area overhead by minimizing duplicated gates in the partitioned sub-circuits. The partitioned subcircuits are further optimized utilizing observability don't-care sets. Experimental results for the MCNC benchmarks show that the proposed algorithm synthesizes circuits that on the average consume 22.5% less power and have 12.7% less area than circuits generated by previous algorithms based on a precomputation scheme.