Loading [MathJax]/jax/output/CommonHTML/jax.js
  • Title/Summary/Keyword: 유클리드 거리

Search Result 155, Processing Time 0.023 seconds

Travelling Salesman Problem Based on Area Division and Connection Method (외판원 문제의 지역 분할-연결 기법)

  • Lee, Sang-Un
    • The Journal of the Institute of Internet, Broadcasting and Communication
    • /
    • v.15 no.3
    • /
    • pp.211-218
    • /
    • 2015
  • This paper introduces a 'divide-and-conquer' algorithm to the travelling salesman problem (TSP). Top 10n are selected beforehand from a pool of n(n-1) data which are sorted in the ascending order of each vertex's distance. The proposed algorithm then firstly selects partial paths that are interconnected with the shortest distance r1=d{vi,vj} of each vertex vi and assigns them as individual regions. For r2, it connects all inter-vertex edges within the region and inter-region edges are connected in accordance with the connection rule. Finally for r3, it connects only inter-region edges until one whole Hamiltonian cycle is constructed. When tested on TSP-1(n=26) and TSP-2(n=42) of real cities and on a randomly constructed TSP-3(n=50) of the Euclidean plane, the algorithm has obtained optimal solutions for the first two and an improved one from that of Valenzuela and Jones for the third. In contrast to the brute-force search algorithm which runs in n!, the proposed algorithm runs at most 10n times, with the time complexity of O(n2).

Photomosaic Algorithm with Adaptive Tilting and Block Matching (적응적 타일링 및 블록 매칭을 통한 포토 모자이크 알고리즘)

  • Seo, Sung-Jin;Kim, Ki-Wong;Kim, Sun-Myeng;Lee, Hae-Yeoun
    • The KIPS Transactions:PartB
    • /
    • v.19B no.1
    • /
    • pp.1-8
    • /
    • 2012
  • Mosaic is to make a big image by gathering lots of small materials having various colors. With advance of digital imaging techniques, photomosaic techniques using photos are widely used. In this paper, we presents an automatic photomosaic algorithm based on adaptive tiling and block matching. The proposed algorithm is composed of two processes: photo database generation and photomosaic generation. Photo database is a set of photos (or tiles) used for mosaic, where a tile is divided into 4×4 regions and the average RGB value of each region is the feature of the tile. Photomosaic generation is composed of 4 steps: feature extraction, adaptive tiling, block matching, and intensity adjustment. In feature extraction, the feature of each block is calculated after the image is splitted into the preset size of blocks. In adaptive tiling, the blocks having similar similarities are merged. Then, the blocks are compared with tiles in photo database by comparing euclidean distance as a similarity measure in block matching. Finally, in intensity adjustment, the intensity of the matched tile is replaced as that of the block to increase the similarity between the tile and the block. Also, a tile redundancy minimization scheme of adjacent blocks is applied to enhance the quality of mosaic photos. In comparison with Andrea mosaic software, the proposed algorithm outperforms in quantitative and qualitative analysis.

Trajectory Clustering in Road Network Environment (도로 네트워크 환경을 위한 궤적 클러스터링)

  • Bak, Ji-Haeng;Won, Jung-Im;Kim, Sang-Wook
    • The KIPS Transactions:PartD
    • /
    • v.16D no.3
    • /
    • pp.317-326
    • /
    • 2009
  • Recently, there have been many research efforts proposed on trajectory information. Most of them mainly focus their attention on those objects moving in Euclidean space. Many real-world applications such as telematics, however, deal with objects that move only over road networks, which are highly restricted for movement. Thus, the existing methods targeting Euclidean space cannot be directly applied to the road network space. This paper proposes a new clustering scheme for a large volume of trajectory information of objects moving over road networks. To the end, we first define a trajectory on a road network as a sequence of road segments a moving object has passed by. Next, we propose a similarity measurement scheme that judges the degree of similarity by considering the total length of matched road segments. Based on such similarity measurement, we propose a new clustering algorithm for trajectories by modifying and adjusting the FastMap and hierarchical clustering schemes. To evaluate the performance of the proposed clustering scheme, we also develop a trajectory generator considering the observation that most objects tend to move from the starting point to the destination point along their shortest path, and perform a variety of experiments using the trajectories thus generated. The performance result shows that our scheme has the accuracy of over 95% in comparison with that judged by human beings.

An indoor localization approach using RSSI and LQI based on IEEE 802.15.4 (IEEE 802.15.4기반 RSSI와 LQI를 이용한 실내 위치추정 기법)

  • Kim, Jung-Ha;Kim, Hyun-Jun;Kim, Jong-Su;Lee, Sung-Geun;Seo, Dong-Hoan
    • Journal of Advanced Marine Engineering and Technology
    • /
    • v.38 no.1
    • /
    • pp.92-98
    • /
    • 2014
  • Recently, Fingerprint approach using RSSI based on WLAN has been many studied in order to construct low-cost indoor localization systems. Because this technique is relatively evaluated non-precise positioning technique compared with the positioning of Ultra-Wide-Band(UWB), the performance of the Fingerprint based on WLAN should be continuously improved to implement various indoor location. Therefore, this paper presents a Fingerprint approach which can improve the performance of localization by using RSSI and LQI contained IEEE 802.15.4 standard. The advantages of these techniques are that the characteristics of each location is created more clearly by utilizing RSSI and LQI and Fingerprint technique is improved by using the modified Euclidean distance method. The experimental results which are applied in NLOS indoor environment with various obstacles show that the accuracy of localization is improved to 22% compared to conventional Fingerprint.

Detection of Epileptic Seizure Based on Peak Using Sequential Increment Method (점증적 증가를 이용한 첨점 기반의 간질 검출)

  • Lee, Sang-Hong
    • Journal of Digital Convergence
    • /
    • v.13 no.10
    • /
    • pp.287-293
    • /
    • 2015
  • This study proposed signal processing techniques and neural network with weighted fuzzy membership functions(NEWFM) to detect epileptic seizure from EEG signals. This study used wavelet transform(WT), sequential increment method, and phase space reconstruction(PSR) as signal processing techniques. In the first step of signal processing techniques, wavelet coefficients were extracted from EEG signals using the WT. In the second step, sequential increment method was used to extract peaks from the wavelet coefficients. In the third step, 3D diagram was produced from the extracted peaks using the PSR. The Euclidean distances and statistical methods were used to extract 16 features used as inputs for NEWFM. The proposed methodology shows that accuracy, specificity, and sensitivity are 97.5%, 100%, 95% with 16 features, respectively.

3D Face Recognition using Longitudinal Section and Transection (종단면과 횡단면을 이용한 3차원 얼굴 인식)

  • 이영학;박건우;이태홍
    • Journal of KIISE:Software and Applications
    • /
    • v.30 no.9
    • /
    • pp.885-893
    • /
    • 2003
  • In this paper, a new practical implementation of a person verification system using features of longitudinal section and transection and other facial, rotation compensated 3D face image, is proposed. The approach works by finding the nose tip that has a protrusion shape on the face. In feature recognition of 3D face image, one has to take into consideration the orientated frontal posture to normalize. Next, the special points in regions, such as nose, eyes and mouth are detected. The depth of nose, the area of nose and the volume of nose based both on the 3 longitudinal section and a transection are calculated. The eye interval and mouth width are also computed. Finally, the 12 features on the face were extracted. The Ll measure for comparing two feature vectors were used, because it is simple and robust. In the experimental results, proposed method achieves recognition rate of 95.5% for the longitudinal section and transection.

Construction of Theme Melody Index by Transforming Melody to Time-series Data for Content-based Music Information Retrieval (내용기반 음악정보 검색을 위한 선율의 시계열 데이터 변환을 이용한 주제선율색인 구성)

  • Ha, Jin-Seok;Ku, Kyong-I;Park, Jae-Hyun;Kim, Yoo-Sung
    • The KIPS Transactions:PartD
    • /
    • v.10D no.3
    • /
    • pp.547-558
    • /
    • 2003
  • From the viewpoint of that music melody has the similar features to time-series data, music melody is transformed to a time-series data with normalization and corrections and the similarity between melodies is defined as the Euclidean distance between the transformed time-series data. Then, based the similarity between melodies of a music object, melodies are clustered and the representative of each cluster is extracted as one of theme melodies for the music. To construct the theme melody index, a theme melody is represented as a point of the multidimensional metric space of M-tree. For retrieval of user's query melody, the query melody is also transformed into a time-series data by the same way of indexing phase. To retrieve the similar melodies to the query melody given by user from the theme melody index the range query search algorithm is used. By the implementation of the prototype system using the proposed theme melody index we show the effectiveness of the proposed methods.

An Index Interpolation-based Subsequence Matching Algorithm supporting Normalization Transform in Time-Series Databases (시계열 데이터베이스에서 인덱스 보간법을 기반으로 정규화 변환을 지원하는 서브시퀀스 매칭 알고리즘)

  • No, Ung-Gi;Kim, Sang-Uk;Hwang, Gyu-Yeong
    • Journal of KIISE:Databases
    • /
    • v.28 no.2
    • /
    • pp.217-232
    • /
    • 2001
  • 본 논문에서는 시계열 데이터베이스에서 정규화 변환을 지원하는 서브시퀀스 매칭 알고리즘을 제안한다. 정규화 변환을 시계열 데이터 간의 절대적인 유클리드 거리에 관계 없이, 구성하는 값들의 상대적인 변화 추이가 유사한 패턴을 갖는 시계열 데이터를 검색하는 데에 유용하다. 기존의 서브시퀀스 매칭 알고리즘을 확장 없이 정규화 변환 서브시퀀스 매칭에 단순히 응용할 경우, 질의 결과로 반환되어야 할 서부시퀀스를 모두 찾아내지 못하는 착오 기각이 발생한다. 또한, 정규화 변환을 지원하는 기존의 전체 매칭 알고리즘의 경우, 모든 가능한 질의 시퀀스 길이 각각에 대하여 하나씩의 인덱스를 생성하여야 하므로, 저장 공간 및 데이터 시퀀스 삽입/삭제의 부담이 매우 심각하다. 본 논문에서는 인덱스 보간법을 이용하여 문제를 해결한다. 인덱스 보간법은 인덱스가 요구되는 모든 경우 중에서 적당한 간격의 일부에 대해서만 생성된 인덱스를 이용하며, 인덱스가 필요한 모든 경우에 대한 탐색을 수행하는 기법이다. 제안된 알고리즘은 몇 개의 질의 시퀀스 길이에 대해서만 각각 인덱스를 생성한 후, 이를 이용하여 모든 가능한 길이의 질의 시퀀스에 대해서 탐색을 수행한다. 이때, 착오 기각이 발생하지 않음을 증명한다. 제안된 알고리즘은 질의 시에 주어진 질의 시퀀스의 길이에 따라 생성되어 있는 인덱스 중에서 가장 적절한 것을 선택하여 탐색을 수행한다. 이때, 생성되어 있는 인덱스의 개수가 많을수록 탐색 성능이 향상된다. 필요에 따라 인덱스의 개수를 변화함으로써 탐색 성능과 저장 공간 간의 비율을 유연하게 조정할 수 있다. 질의 시퀀스의 길이 256 ~ 512중 다섯 개의 길이에 대해 인덱스를 생성하여 실험한 결과, 탐색 결과 선택률이 102일 때 제안된 알고리즘의 탐색 성능이 순차 검색에 비하여 평균 2.40배, 선택률이 105일 때 평균 14.6배 개선되었다. 제안된 알고리즘의 탐색 성능은 탐색 결과 선택률이 작아질수록 더욱 향상되므로, 실제 데이터베이스 응용에서의 효용성이 높다고 판단된다.

  • PDF

Analyzing and classifying emotional flow of story in emotion dimension space (정서 차원 공간에서 소설의 지배 정서 분석 및 분류)

  • Rhee, Shin-Young;Ham, Jun-Seok;Ko, Il-Ju
    • Korean Journal of Cognitive Science
    • /
    • v.22 no.3
    • /
    • pp.299-326
    • /
    • 2011
  • The text such as stories, blogs, chat, message and reviews have the overall emotional flow. It can be classified to the text having similar emotional flow if we compare the similarity between texts, and it can be used such as recommendations and opinion collection. In this paper, we extract emotion terms from the text sequentially and analysis emotion terms in the pleasantness-unpleasantness and activation dimension in order to identify the emotional flow of the text. To analyze the 'dominant emotion' which is the overall emotional flow in the text, we add the time dimension as sequential flow of the text, and analyze the emotional flow in three dimensional space: pleasantness-unpleasantness, activation and time. Also, we suggested that a classification method to compute similarity of the emotional flow in the text using the Euclidean distance in three dimensional space. With the proposed method, we analyze the dominant emotion in korean modern short stories and classify them to similar dominant emotion.

  • PDF

Performance of an ML Modulation Classification of QAM Signals with Single-Sample Observation (단일표본관측을 이용한 직교진폭변조 신호의 치운 변조분류 성능)

  • Kang Seog Geun
    • The KIPS Transactions:PartC
    • /
    • v.12C no.1 s.97
    • /
    • pp.63-68
    • /
    • 2005
  • In this paper, performance of a maximum-likelihood modulation classification for quadrature amplitude modulation (QAM) is studied. Unlike previous works, the relative classification performance with respect to the available modulations and performance limit with single-sample observation are presented. For those purposes, all constellations are set to have the same minimum Euclidean distance between symbols so that a smaller constellation is a subset of the larger ones. And only one sample of received waveform is used for multiple hypothesis test. As a result, classification performance is improved with increase in signal-to-noise ratio in all the experiments. Especially, when the true modulation format used in the transmitter is 4 QAM, almost perfect classification can be achieved without any additional information or observation samples. Though the possibility of false classification due to the symbols shared by subset constellations always exists, correct classification ratio of 80% can be obtained with the single-sample observation when the true modulation formats are 16 and 64 QAM.