• The Journal of the Acoustical Society of Korea
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• v.8 no.4
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• pp.44-52
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• 1989

The UCERSS (Unit Circle Eigendecomposition Rational Signal Subspace) algorithm has extended MUSIC (MUltiple Signal Classification ) by using eigendecomposition on the unit circle in order to estimate incident angles of multiple wide band signals. The purpose of this thesis is to further extend the UCERSS to be able to estimate the direction of arrivals of multiple wide band signals in very low SNR . The wide band ESPRIT (Estimation of Signal Parameter via Rotational Invariance Technique) uses covariance difference matrices to reduce noise components. In this paper the wide band ESPRIT which combines the ideas of UCERSS and ESPRIT Is proposed. Computer simulation results Indicate that the performances of the proposed approaches are superior to those of the UCERSS in very low SNR.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.12
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• pp.1359-1369
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• 2007

This paper describes the technique of satellite direction finding and main beam steering of the adaptive array antenna system which is used for mobile TT&C(Tracking Telemetry&Command) system. To be able to control the satellite on mobile vehicle while moving, the relative directional information of the satellite to the mobile vehicle is necessary to make main beam to the direction of satellite. To do this MUSIC, which is one of the super-resolution algorithm of wave direction finding, is used and then the performance analysis and quantization problem of phase shifter are addressed. This paper is valuable in the respect of showing feasibility of designing the moble TT&C using adative array antenna system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.8
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• pp.1414-1419
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• 2000

In this paper, we propose a resolution enhancement method for estimating direction-of-arrival (DOA) of narrowband incoherent signals incident on a general array. The resolution of DOA algorithm is dependent on the aperture size of antenna array. But it is very impractical to increase the physical size of antenna array in real environment. Therefore we propose the method that increases the aperture size by virtually expanding the sensor spacing of original antenna array and then construct the steering matrix of the virtual array using the proper transformation matrix. Superior resolution capabilities achieved with this method are shown by simulation results in comparison with the standard MUSIC for incoherent signals incident on a uniform circular array.

• Korea Science and Art Forum
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• v.37 no.3
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• pp.125-134
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• 2019

This study was conducted to organize a program to classify and analyze the characteristics of images for the automation of background music selection in the video content production process. The results and contents of the study are as follows: video characteristics are selected as subject category, emotion, pixel motion speed, color, and character material. Subject categories and feelings were extracted using Microsoft's Azure Video Indexer, Pixel Movement Speed was an Optional flow, Color was an Image Histogram for Image, and character materials was CNN(Convolutional Neural Network). The results of this study are significant in that video analysis was conducted to match background music in the recent content production process of 'Internet One-person Broadcasting Creators'.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.435-441
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• 2017

Detecting an inter-harmonic accurately is not easy work, because it has small magnitude, and its frequency which can be observed is not an integer multiple of fundamental frequency. In this paper, a new method using filter bank system and adaptive predictor is proposed. Filter bank system decomposes input signal to sub bands. In adaptive predictor, inter-harmonic is detected with decomposed sub band signal as input, and error signal as output. In this scheme, input-output characteristic of adaptive predictor is notch filter, as predicted harmonic is canceled in error signal, so detecting an inter-harmonic can be possible. Magnitude and frequency of detected inter-harmonic is estimated by recursive algorithm. The performances of proposed method are evaluated to sinusoidal signal model synthesized with harmonics and inter-harmonics. And validity of the method is proved as comparing the inter-harmonic detection results to MUSIC and ESPRIT.

• Journal of the Korean Society for information Management
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• v.24 no.2
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• pp.89-104
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• 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.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.7
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• pp.166-175
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• 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).

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.1
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• pp.121-127
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• 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.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1243-1246
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• 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.

• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.160-165
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• 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.