• 제목/요약/키워드: Candidate Clustering

검색결과 83건 처리시간 0.027초

A Hybrid Multiuser Detection Algorithm for Outer Space DS-UWB Ad-hoc Network with Strong Narrowband Interference

  • Yin, Zhendong;Kuang, Yunsheng;Sun, Hongjian;Wu, Zhilu;Tang, Wenyan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제6권5호
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    • pp.1316-1332
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    • 2012
  • Formation flying is an important technology that enables high cost-effective organization of outer space aircrafts. The ad-hoc wireless network based on direct-sequence ultra-wideband (DS-UWB) techniques is seen as an effective means of establishing wireless communication links between aircrafts. In this paper, based on the theory of matched filter and error bits correction, a hybrid detection algorithm is proposed for realizing multiuser detection (MUD) when the DS-UWB technique is used in the ad-hoc wireless network. The matched filter is used to generate a candidate code set which may contain several error bits. The error bits are then recognized and corrected by an novel error-bit corrector, which consists of two steps: code mapping and clustering. In the former step, based on the modified optimum MUD decision function, a novel mapping function is presented that maps the output candidate codes into a feature space for differentiating the right and wrong codes. In the latter step, the codes are clustered into the right and wrong sets by using the K-means clustering approach. Additionally, in order to prevent some right codes being wrongly classified, a sign judgment method is proposed that reduces the bit error rate (BER) of the system. Compared with the traditional detection approaches, e.g., matched filter, minimum mean square error (MMSE) and decorrelation receiver (DEC), the proposed algorithm can considerably improve the BER performance of the system because of its high probability of recognizing wrong codes. Simulation results show that the proposed algorithm can almost achieve the BER performance of the optimum MUD (OMD). Furthermore, compared with OMD, the proposed algorithm has lower computational complexity, and its BER performance is less sensitive to the number of users.

유성음과 무성음의 경계를 이용한 연속 음성의 세그먼테이션 (Segmentation of continuous Korean Speech Based on Boundaries of Voiced and Unvoiced Sounds)

  • 유강주;신욱근
    • 한국정보처리학회논문지
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    • 제7권7호
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    • pp.2246-2253
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    • 2000
  • In this paper, we show that one can enhance the performance of blind segmentation of phoneme boundaries by adopting the knowledge of Korean syllabic structure and the regions of voiced/unvoiced sounds. eh proposed method consists of three processes : the process to extract candidate phoneme boundaries, the process to detect boundaries of voiced/unvoiced sounds, and the process to select final phoneme boundaries. The candidate phoneme boudaries are extracted by clustering method based on similarity between two adjacent clusters. The employed similarity measure in this a process is the ratio of the probability density of adjacent clusters. To detect he boundaries of voiced/unvoiced sounds, we first compute the power density spectrum of speech signal in 0∼400 Hz frequency band. Then the points where this paper density spectrum variation is greater than the threshold are chosen as the boundaries of voiced/unvoiced sounds. The final phoneme boundaries consist of all the candidate phoneme boundaries in voiced region and limited number of candidate phoneme boundaries in unvoiced region. The experimental result showed about 40% decrease of insertion rate compared to the blind segmentation method we adopted.

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클러스터를 이용한 손실된 움직임 벡터 복원 방법 (Recovery Method of missing Motion Vector using Cluster)

  • 손남례;이귀상
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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    • pp.2371-2374
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    • 2003
  • In transmitting compressed video bit-stream over Internet, packet loss causes error propagation in both spatial and temporal domain, which in turn leads to severe degradation in image qualify In this paper, a new approach for the recovery of lost or erroneous Motion Vector(MV)s by clustering the movements of neighboring blocks by their homogeneity is proposed. MVs of neighboring blocks are clustered according to ALA(Average Linkage Algorithm) clustering and a representative value for each cluster is determined to obtain the candidate MV set. By computing the distortion of the candidates, a MV with the minimum distortion is selected. Experimental results show that the proposed algorithm exhibits better performance in many cases than existing methods.

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차영상과 ART2 클러스터링을 이용한 스마트폰 기반의 FND 인식 기법 (Smartphone Based FND Recognition Method using sequential difference images and ART-II Clustering)

  • 구경모;차의영
    • 한국정보통신학회논문지
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    • 제16권7호
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    • pp.1377-1382
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    • 2012
  • 본 논문에서는 가전기기에 탑재 된 FND에 표시되는 부호화 된 코드를 스마트폰으로 촬영하여 이로부터 원문데이터를 추출하는 인식기법에 대해 제안한다. 제안하는 스마트폰 기반의 FND 인식 기법은 먼저 차영상을 이용하여 입력되는 영상에서 FND의 위치를 추정한 뒤 RGB값 클러스터링을 통해 Segment를 추출한다. 다음으로 기울어진 Segment에 대한 정규화 과정을 거친 뒤 상대적인 거리를 이용하여 각각의 Segment를 인식한다. 실험을 통해 실제 스마트폰에서 사용 시 속도와 인식률이 모두 양호함을 확인하였다.

온라인 과도안정도 평가를 위한 새로운 불안정모드 선정 알고리즘 (A New Algorithm for Unstable Mode Decision in the On-line Transient Stability Assessment)

  • 장동환;김정우;전영환
    • 전기학회논문지
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    • 제57권7호
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    • pp.1123-1128
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    • 2008
  • The necessity of online dynamic security assessment is getting apparent under Electricity Market environments, as operation of power system is exposed to more various operating conditions. For on-line dynamic security assessment, fast transient stability analysis tool is required for contingency selection. The TEF(Transient Energy Function) method is a good candidate for this purpose. The clustering of critical generators is crucial for the precise and fast calculation of energy margin. In this paper, we propose a new method for fast decision of mode of instability by using stability indices and energy margin. The method is a new version of our previous paper.[1] Case studies are showing very promising results.

대용량 온라인 한자 인식을 위한 클러스터링 거리계산 척도 (Distance Measures in HMM Clustering for Large-scale On-line Chinese Character Recognition)

  • 김광섭;하진영
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제36권9호
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    • pp.683-690
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    • 2009
  • 은닉 마코프 모델(Hidden Markov Model: HMM)에 기반을 둔 온라인 한자 인식에서 클래스의 수가 대용량일 경우에는 인식에 걸리는 시간 증가가 좋은 인식 시스템을 구현하는데 있어서의 걸림돌이 된다. 본 논문에서는 이러한 인식 속도 문제를 해결하고자 HMM을 클러스터링하여 인식 속도를 개선하는 방법과 이에 적합한 효율적인 HMM 간의 거리계산법을 제안한다. 유니코드 한 중 일 통합한자로 정의된 총 20,902개의 한자에 대한 온라인 한자 인식 시스템을 구축하는 실험에서 약 2배 정도로 인식속도가 향상됨을 확인할 수 있었고 클러스터링을 하지 않았을 때보다 0.9%의 인식률만 하락한 95.37%의 10순위 인식률을 달성했다.

새로운 지도 경쟁 학습 알고리즘의 개발과 전력계통 과도안정도 해석에의 적용 (A New Supervised Competitive Learning Algorithm and Its Application to Power System Transient Stability Analysis)

  • 박영문;조홍식;김광원
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 하계학술대회 논문집 B
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    • pp.591-593
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    • 1995
  • Artificial neural network based pattern recognition method is one of the most probable candidate for on-line power system transient stability analysis. Especially, Kohonen layer is an adequate neural network for the purpose. Each node of Kehonen layer competes on the basis of which of them has its clustering center closest to an input vector. This paper discusses Kohonen's LVQ(Learning Victor Quantization) and points out a defection of the algorithm when applied to the transient stability analysis. Only the clustering centers located near the decision boundary of the stability region is needed for the stability criterion and the centers far from the decision boundary are redundant. This paper presents a new algorithm ratted boundary searching algorithm II which assigns only the points that are near the boundary in an input space to nodes or Kohonen layer as their clustering centers. This algorithm is demonstrated with satisfaction using 4-generator 6-bus sample power system.

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프레임간 히스토그램 차이를 이용한 개선된 대표프레임 추출 알고리즘 (An Improved key Frame Selection Algorithm Based on Histogram Difference Between Frames)

  • 정지현;전승철;박성한
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2000년도 추계종합학술대회 논문집(3)
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    • pp.137-140
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    • 2000
  • In this paper, we propose as new algorithm for the selection of key frames in a given video. For the selected key frames to be well defined, the selected key frames need to spread out on the whole temporal domain of the given video and guaranteed not to be duplicate. For this purpose, we take the first frame of each shot of the video as the candidate key frame to represent the video. To reduce the overall processing time, we eliminate some candidate key frames which are visually indistinct in the histogram difference. The key frames are then selected using a clustering processing based on the singly linked hierarchical tree. To make the selected key frames be distributed evenly on the whole video, the deviation and time difference between the selected key frames are used. The simulation results demonstrate that our method provides the better performance compared with previous methods.

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A new structural reliability analysis method based on PC-Kriging and adaptive sampling region

  • Yu, Zhenliang;Sun, Zhili;Guo, Fanyi;Cao, Runan;Wang, Jian
    • Structural Engineering and Mechanics
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    • 제82권3호
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    • pp.271-282
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    • 2022
  • The active learning surrogate model based on adaptive sampling strategy is increasingly popular in reliability analysis. However, most of the existing sampling strategies adopt the trial and error method to determine the size of the Monte Carlo (MC) candidate sample pool which satisfies the requirement of variation coefficient of failure probability. It will lead to a reduction in the calculation efficiency of reliability analysis. To avoid this defect, a new method for determining the optimal size of the MC candidate sample pool is proposed, and a new structural reliability analysis method combining polynomial chaos-based Kriging model (PC-Kriging) with adaptive sampling region is also proposed (PCK-ASR). Firstly, based on the lower limit of the confidence interval, a new method for estimating the optimal size of the MC candidate sample pool is proposed. Secondly, based on the upper limit of the confidence interval, an adaptive sampling region strategy similar to the radial centralized sampling method is developed. Then, the k-means++ clustering technique and the learning function LIF are used to complete the adaptive design of experiments (DoE). Finally, the effectiveness and accuracy of the PCK-ASR method are verified by three numerical examples and one practical engineering example.

Theoretical Investigation of Edge-modified Zigzag Graphene Nanoribbons by Scandium Metal with Pyridine-like Defects: A Potential Hydrogen Storage Material

  • Mananghaya, Michael
    • Bulletin of the Korean Chemical Society
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    • 제35권1호
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    • pp.253-256
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    • 2014
  • Functionalization of zigzag graphene nanoribbon (ZGNR) segment containing 120 C atoms with pyridine (3NV-ZGNR) defects was investigated on the basis of density-functional theory (DFT) calculations, results show that edge-modified ZGNRs by Sc can adsorb multiple hydrogen molecules in a quasi-molecular fashion, thereby can be a potential candidate for hydrogen storage. The stability of Sc functionalization is dictated by a strong binding energy, suggesting a reduction of clustering of metal atoms over the metal-decorated ZGNR.