• Title/Summary/Keyword: MUSIC algorithm

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Emotion-based music visualization using LED lighting control system (LED조명 시스템을 이용한 음악 감성 시각화에 대한 연구)

  • Nguyen, Van Loi;Kim, Donglim;Lim, Younghwan
    • Journal of Korea Game Society
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    • v.17 no.3
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    • pp.45-52
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    • 2017
  • This paper proposes a new strategy of emotion-based music visualization. Emotional LED lighting control system is suggested to help audiences enhance the musical experience. In the system, emotion in music is recognized by a proposed algorithm using a dimensional approach. The algorithm used a method of music emotion variation detection to overcome some weaknesses of Thayer's model in detecting emotion in a one-second music segment. In addition, IRI color model is combined with Thayer's model to determine LED light colors corresponding to 36 different music emotions. They are represented on LED lighting control system through colors and animations. The accuracy of music emotion visualization achieved to over 60%.

A Similarity Computation Algorithm Based on the Pitch and Rhythm of Music Melody (선율의 음높이와 리듬 정보를 이용한 음악의 유사도 계산 알고리즘)

  • Mo, Jong-Sik;Kim, So-Young;Ku, Kyong-I;Han, Chang-Ho;Kim, Yoo-Sung
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.12
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    • pp.3762-3774
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    • 2000
  • The advances of computer hardware and information processing technologies raise the needs of multimedia information retrieval systems. Up to date. multimedia information systems have been developed for text information and image information. Nowadays. the multimedia information systems for video and audio information. especially for musical information have been grown up more and more. In recent music information retrieval systems. not only the information retrieval based on meta-information such like composer and title but also the content-based information retrieval is supported. The content-based information retrieval in music information retrieval systems utilize the similarity value between the user query and the music information stored in music database. In tbis paper. hence. we developed a similarity computation algorithm in which the pitches and lengths of each corresponding pair of notes are used as the fundamental factors for similarity computation between musical information. We also make an experiment of the proposed algorithm to validate its appropriateness. From the experimental results. the proposed similarity computation algorithm is shown to be able to correctly check whether two music files are analogous to each other or not based on melodies.

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Compressive Sensing-Based L1-SVD DOA Estimation (압축센싱기법 기반 L1-SVD 도래각 추정)

  • Cho, Yunseong;Paik, Ji-Woong;Lee, Joon-Ho;Ko, Yo Han;Cho, Sung-Woo
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.27 no.4
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    • pp.388-394
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    • 2016
  • There have been many studies on the direction-of-arrival(DOA) estimation algorithm using antenna arrays. Beamforming, Capon's method, maximum likelihood, MUSIC algorithms are the main algorithms for the DOA estimation. Recently, compressive sensing-based DOA estimation algorithm exploiting the sparsity of the incident signals has attracted much attention in the signal processing community. In this paper, the performance of the L1-SVD algorithm, which is based on fitting of the data matrix, is compared with that of the MUSIC algorithm.

Score Image Retrieval to Inaccurate OMR performance

  • Kim, Haekwang
    • Journal of Broadcast Engineering
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    • v.26 no.7
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    • pp.838-843
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    • 2021
  • This paper presents an algorithm for effective retrieval of score information to an input score image. The originality of the proposed algorithm is that it is designed to be robust to recognition errors by an OMR (Optical Music Recognition), while existing methods such as pitch histogram requires error induced OMR result be corrected before retrieval process. This approach helps people to retrieve score without training on music score for error correction. OMR takes a score image as input, recognizes musical symbols, and produces structural symbolic notation of the score as output, for example, in MusicXML format. Among the musical symbols on a score, it is observed that filled noteheads are rarely detected with errors with its simple black filled round shape for OMR processing. Barlines that separate measures also strong to OMR errors with its long uniform length vertical line characteristic. The proposed algorithm consists of a descriptor for a score and a similarity measure between a query score and a reference score. The descriptor is based on note-count, the number of filled noteheads in a measure. Each part of a score is represented by a sequence of note-count numbers. The descriptor is an n-gram sequence of the note-count sequence. Simulation results show that the proposed algorithm works successfully to a certain degree in score image-based retrieval for an erroneous OMR output.

Determining Key Features of Recognition Korean Traditional Music Using Spectrogram

  • Kim Jae Chun;Kwak Kyung Sup
    • The Journal of the Acoustical Society of Korea
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    • v.24 no.2E
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    • pp.67-70
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    • 2005
  • To realize a traditional music recognition system, some characteristics pertinent to Far East Asian music should be found. Using Spectrogram, some distinct attributes of Korean traditional music are surveyed. Frequency distribution, beat cycle and frequency energy intensity within samples have distinct characteristics of their own. Experiment is done for pre-experimentation to realize Korean traditional music recognition system. Using characteristics of Korean traditional music, $94.5\%$ of classification accuracy is acquired. As Korea, Japan and China have the same musical roots, both in instruments and playing style, analyzing Korean traditional music can be helpful in the understanding of Far East Asian traditional music.

Performance analysis of DoA estimation algorithm using a circular array antenna (원형 배열 안테나의 DoA 추정 알고리즘 성능 분석)

  • Lim, Seung-Gag;Kang, Dae-Soo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.9 no.2
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    • pp.395-400
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    • 2008
  • This paper relates to the performance analysis of DoA estimation algorithm in 2-dimensional circular array antenna for the receiving of GPS signal which is used for the performance improvement by elimination of jammer signal. By performing the spatial filtering after the DoA estimation in array antenna, the quality of receiving signal can improve by the nulling of jammer signal from the undesired direction and the forming of beam from the desired direction. In this paper, the MUSIC and MinNorm algorithm used for DoA estimation were applied after fixing the angle and power of jammer signal in 4 element and 7 element circular array antenna. In order to performance analysis, the estimation result and estimation error were computed by computer simulation. As a result, the MUSIC and MinNorm were fairly good in azimuth and elevation angle estimation of DoA in case of good signal to noise ratio and the MUSIC has better performance compared to MinNorm in case of poor signal to noise ratio.

A Study on Calculation of RCS Using MUSIC Algorithm (MUSIC 알고리즘에 의한 레이더 반사단면적 계산법에 관한 연구)

  • Pang Tian Ting;Jeong Jung-Sik;Park Sung-Hyeon;Nam Taek-Kun;Yim Jeong-Bin;Aim Young-sup
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2005.10a
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    • pp.43-46
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    • 2005
  • The detectability of radar depends on RCS(radar cross section). The RCS for complex radar targets may be only approximately calculated by using low-frequency or high-frequency scattering methods, while the RCS for simple rob targets can be exactly obtained by applying an eigen-function method. However, the conventional methods for calculation of RCS are computationally complex. We propose an approximation method for RCS calculation by MUSIC algorithm In this research, it is assumed toot the radar target is considered as a ring of scatterers. The amplitudes of scatterers may be statistically distributed. As the result, the radar signal model is proposed to use MUSIC, and the RCS is calculated by a simple linear algebraic method.

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Automatic Music Summarization Using Similarity Measure Based on Multi-Level Vector Quantization (다중레벨 벡터양자화 기반의 유사도를 이용한 자동 음악요약)

  • Kim, Sung-Tak;Kim, Sang-Ho;Kim, Hoi-Rin
    • The Journal of the Acoustical Society of Korea
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    • v.26 no.2E
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    • pp.39-43
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    • 2007
  • Music summarization refers to a technique which automatically extracts the most important and representative segments in music content. In this paper, we propose and evaluate a technique which provides the repeated part in music content as music summary. For extracting a repeated segment in music content, the proposed algorithm uses the weighted sum of similarity measures based on multi-level vector quantization for fixed-length summary or optimal-length summary. For similarity measures, count-based similarity measure and distance-based similarity measure are proposed. The number of the same codeword and the Mahalanobis distance of features which have same codeword at the same position in segments are used for count-based and distance-based similarity measure, respectively. Fixed-length music summary is evaluated by measuring the overlapping ratio between hand-made repeated parts and automatically generated ones. Optimal-length music summary is evaluated by calculating how much automatically generated music summary includes repeated parts of the music content. From experiments we observed that optimal-length summary could capture the repeated parts in music content more effectively in terms of summary length than fixed-length summary.

An ICA-Based Subspace Scanning Algorithm to Enhance Spatial Resolution of EEG/MEG Source Localization (뇌파/뇌자도 전류원 국지화의 공간분해능 향상을 위한 독립성분분석 기반의 부분공간 탐색 알고리즘)

  • Jung, Young-Jin;Kwon, Ki-Woon;Im, Chang-Hwan
    • Journal of Biomedical Engineering Research
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    • v.31 no.6
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    • pp.456-463
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    • 2010
  • In the present study, we proposed a new subspace scanning algorithm to enhance the spatial resolution of electroencephalography (EEG) and magnetoencephalography(MEG) source localization. Subspace scanning algorithms, represented by the multiple signal classification (MUSIC) algorithm and the first principal vector (FINE) algorithm, have been widely used to localize asynchronous multiple dipolar sources in human cerebral cortex. The conventional MUSIC algorithm used principal component analysis (PCA) to extract the noise vector subspace, thereby having difficulty in discriminating two or more closely-spaced cortical sources. The FINE algorithm addressed the problem by using only a part of the noise vector subspace, but there was no golden rule to determine the number of noise vectors. In the present work, we estimated a non-orthogonal signal vector set using independent component analysis (ICA) instead of using PCA and performed the source scanning process in the signal vector subspace, not in the noise vector subspace. Realistic 2D and 3D computer simulations, which compared the spatial resolutions of various algorithms under different noise levels, showed that the proposed ICA-MUSIC algorithm has the highest spatial resolution, suggesting that it can be a useful tool for practical EEG/MEG source localization.

Partial Field Decompositon Using Beamforming Method Under Reflective Condition (반사면이 존재하는 환경에서 빔포밍 방법을 이용한 부분 음장 재구성)

  • 선종천;강연준
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2003.11a
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    • pp.730-734
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    • 2003
  • A beamforming method is a kind of spatial filter that focus the amy's signal capturing abilities in a desired direction. In this paper, we detect the location of a source under reflective condition using the multi-dimensional MUSIC algorithm then, we can iud the image source locations from the experimental geometry, and we reconstruct the partial fields for direct wave and reflected wave by using Adaptive nulling algorithm. Numerical simulations are performed to verify its performance under various conditions.

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