• Title/Summary/Keyword: Music Algorithm

Search Result 349, Processing Time 0.027 seconds

A Study on Recommendation System Using Data Mining Techniques for Large-sized Music Contents (대용량 음악콘텐츠 환경에서의 데이터마이닝 기법을 활용한 추천시스템에 관한 연구)

  • Kim, Yong;Moon, Sung-Been
    • Journal of the Korean Society for information Management
    • /
    • v.24 no.2
    • /
    • pp.89-104
    • /
    • 2007
  • This research attempts to give a personalized recommendation framework in large-sized music contents environment. Despite of existing studios and commercial contents for recommendation systems, large online shopping malls are still looking for a recommendation system that can serve personalized recommendation and handle large data in real-time. This research utilizes data mining technologies and new pattern matching algorithm. A clustering technique is used to get dynamic user segmentations using user preference to contents categories. Then a sequential pattern mining technique is used to extract contents access patterns in the user segmentations. And the recommendation is given by our recommendation algorithm using user contents preference history and contents access patterns of the segment. In the framework, preprocessing and data transformation and transition are implemented on DBMS. The proposed system is implemented to show that the framework is feasible. In the experiment using real-world large data, personalized recommendation is given in almost real-time and shows acceptable correctness.

Direction-of-Arrival Estimation in Broadband Signal Processing : Rotation of Signal Subspace Approach (광대역 신호 처리에서의 도래각 추정 : Rotation of Signal Subspaces 방법)

  • Kim, Young-Soo
    • Journal of the Korean Institute of Telematics and Electronics
    • /
    • v.26 no.7
    • /
    • pp.166-175
    • /
    • 1989
  • In this paper, we present a method which is based on the concept of the rotation of subspaces. This method is highly related to the angle (or distance) between subspaces arising in many applications. An effective procedures is first derived for finding the optimal transformation matrix which rotates one subspace into another as closely as possible in the least squares sense , and then this algorithm is applied to the solution to general direction-of-arrival estimation problem of multiple broadband plane waves which may be a mixture of incoherent, partially coherent or coherent. In this typical application, the rotation of signal subspaces (ROSS) algorithm is effectively developed to achieve the high performance in the active systems for the case in which the noise field remains invariant with the measurement of the array spectral density matrix (or data matrix). It is not uncommon to observe this situation in sonar systems. The advantage of this techniques is not to require the preliminary processing and spatial prefiltering which is used in Wang-Kaveh's CSS focusing method. Furthermore, the array's geometry is not restricted. Simulation results are presented to illustrate the high performance achieved with this new approach relative to that obtained with Wang-Kaveh's CSS focusing method for incoherent sources and forward-backward spatial smoothed MUSIC for coherent sources including the signal eigenvector method (SEM).

  • PDF

Multistage Feature-based Classification Model (다단계 특징벡터 기반의 분류기 모델)

  • Song, Young-Soo;Park, Dong-Chul
    • Journal of the Institute of Electronics Engineers of Korea CI
    • /
    • v.46 no.1
    • /
    • pp.121-127
    • /
    • 2009
  • The Multistage Feature-based Classification Model(MFCM) is proposed in this paper. MFCM does not use whole feature vectors extracted from the original data at once to classify each data, but use only groups related to each feature vector to classify separately. In the training stage, the contribution rate calculated from each feature vector group is drew throughout the accuracy of each feature vector group and then, in the testing stage, the final classification result is obtained by applying weights corresponding to the contribution rate of each feature vector group. In this paper, the proposed MFCM algorithm is applied to the problem of music genre classification. The results demonstrate that the proposed MFCM outperforms conventional algorithms by 7% - 13% on average in terms of classification accuracy.

Stereo Sound Image Expansion Using Phase Difference and Sound Pressure Level Difference in Television (위상차와 음압 레벨차를 이용한 텔레비전에서의 스테레오 음상 확대)

  • 박해광;오제화
    • Proceedings of the IEEK Conference
    • /
    • 1998.10a
    • /
    • pp.1243-1246
    • /
    • 1998
  • Three-dimensional(3-D) sound is a technique for generating or recreating sounds so they are perceived as emanating from locations in a three-dimensional space. Three dimensional sound has the potential of increasing the feeling of realism in music or movie soundtracks. Three-dimensional sound effects depend on psychoacoustic spectral and phase cues being presented in a reproduced signal. In this paper we propose an effective algorithm for the sound image expansion in television system using stereo image enhancement techniques. Compared to the other techniques of three-dimensional sound, the proposed algorithm use only two speakers to enhance the sound image expansion, while maintaining the original sound characteristics.

  • PDF

Convolutional Neural Network Based Image Processing System

  • Kim, Hankil;Kim, Jinyoung;Jung, Hoekyung
    • Journal of information and communication convergence engineering
    • /
    • v.16 no.3
    • /
    • pp.160-165
    • /
    • 2018
  • This paper designed and developed the image processing system of integrating feature extraction and matching by using convolutional neural network (CNN), rather than relying on the simple method of processing feature extraction and matching separately in the image processing of conventional image recognition system. To implement it, the proposed system enables CNN to operate and analyze the performance of conventional image processing system. This system extracts the features of an image using CNN and then learns them by the neural network. The proposed system showed 84% accuracy of recognition. The proposed system is a model of recognizing learned images by deep learning. Therefore, it can run in batch and work easily under any platform (including embedded platform) that can read all kinds of files anytime. Also, it does not require the implementing of feature extraction algorithm and matching algorithm therefore it can save time and it is efficient. As a result, it can be widely used as an image recognition program.

Implementation of Non-Contact Gesture Recognition System Using Proximity-based Sensors

  • Lee, Kwangjae
    • Journal of the Semiconductor & Display Technology
    • /
    • v.19 no.3
    • /
    • pp.106-111
    • /
    • 2020
  • In this paper, we propose the non-contact gesture recognition system and algorithm using proximity-based sensors. The system uses four IR receiving photodiode embedded on a single chip and an IR LED for small area. The goal of this paper is to use the proposed algorithm to solve the problem associated with bringing the four IR receivers close to each other and to implement a gesture sensor capable of recognizing eight directional gestures from a distance of 10cm and above. The proposed system was implemented on a FPGA board using Verilog HDL with Android host board. As a result of the implementation, a 2-D swipe gesture of fingers and palms of 3cm and 15cm width was recognized, and a recognition rate of more than 97% was achieved under various conditions. The proposed system is a low-power and non-contact HMI system that recognizes a simple but accurate motion. It can be used as an auxiliary interface to use simple functions such as calls, music, and games for portable devices using batteries.

Feature Selection for Multi-Class Genre Classification using Gaussian Mixture Model (Gaussian Mixture Model을 이용한 다중 범주 분류를 위한 특징벡터 선택 알고리즘)

  • Moon, Sun-Kuk;Choi, Tack-Sung;Park, Young-Cheol;Youn, Dae-Hee
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.32 no.10C
    • /
    • pp.965-974
    • /
    • 2007
  • In this paper, we proposed the feature selection algorithm for multi-class genre classification. In our proposed algorithm, we developed GMM separation score based on Gaussian mixture model for measuring separability between two genres. Additionally, we improved feature subset selection algorithm based on sequential forward selection for multi-class genre classification. Instead of setting criterion as entire genre separability measures, we set criterion as worst genre separability measure for each sequential selection step. In order to assess the performance proposed algorithm, we extracted various features which represent characteristics such as timbre, rhythm, pitch and so on. Then, we investigate classification performance by GMM classifier and k-NN classifier for selected features using conventional algorithm and proposed algorithm. Proposed algorithm showed improved performance in classification accuracy up to 10 percent for classification experiments of low dimension feature vector especially.

The Study of Bio Emotion Cognition follow Stress Index Number by Multiplex SVM Algorithm (다중 SVM 알고리즘을 이용한 스트레스 지수에 따른 생체 감성 인식에 관한 연구)

  • Kim, Tae-Yeun;Seo, Dae-Woong;Bae, Sang-Hyun
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
    • /
    • v.5 no.1
    • /
    • pp.45-51
    • /
    • 2012
  • In this paper, it's a system which recognize the user's emotions after obtaining the biological informations(pulse sensor, blood pressure sensor, blood sugar sensor etc.) about user's bio informations through wireless sensors in accordance of previously collected informations about user's stress index and classification the Colors & Music. This system collects the inputs, saves in the database and finally, classifies emotions according to the stress quotient by using multiple SVM(Support Vector Machine) algorithm. The experiment of multiple SVM algorithm was conducted by using 2,000 data sets. The experiment has approximately 87.7% accuracy.

Uniform DFT Polyphase Filterbank based DF Method for Frequency Hopping Signal Direction Finding (주파수 도약신호 방탐을 위한 균등 디지털주파수변환 폴리페이즈 필터뱅크 기반 방탐기술)

  • Lee, Young-Jin;Kwon, Hyuk-Ja
    • Journal of the Institute of Electronics and Information Engineers
    • /
    • v.54 no.3
    • /
    • pp.119-128
    • /
    • 2017
  • In this paper, the wideband direction finding algorithm and system design method for short duration signal such as frequency hopping or burst signal is presented. The polyphase filterbank that it is possible for the near perfect reconstruction was used as a pre-processing and in each subband power measurement was performed to determine whether the presence of a signal and finally general direction finding algorithm was performed. In addition, various experiments was performed using Matlab Simulink and collected data from wideband receiver to verification of the proposed algorithm.

A novel harmony search based optimization of reinforced concrete biaxially loaded columns

  • Nigdeli, Sinan Melih;Bekdas, Gebrail;Kim, Sanghun;Geem, Zong Woo
    • Structural Engineering and Mechanics
    • /
    • v.54 no.6
    • /
    • pp.1097-1109
    • /
    • 2015
  • A novel optimization approach for reinforced concrete (RC) biaxially loaded columns is proposed. Since there are several design constraints and influences, a new computation methodology using iterative analyses for several stages is proposed. In the proposed methodology random iterations are combined with music inspired metaheuristic algorithm called harmony search by modifying the classical rules of the employed algorithm for the problem. Differently from previous approaches, a detailed and practical optimum reinforcement design is done in addition to optimization of dimensions. The main objective of the optimization is the total material cost and the optimization is important for RC members since steel and concrete are very different materials in cost and properties. The methodology was applied for 12 cases of flexural moment combinations. Also, the optimum results are found by using 3 different axial forces for all cases. According to the results, the proposed method is effective to find a detailed optimum result with different number of bars and various sizes which can be only found by 2000 trial of an engineer. Thus, the cost economy is provided by using optimum bars with different sizes.