• The Journal of the Acoustical Society of Korea
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• v.26 no.5
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• pp.207-213
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• 2007

In this research, we propose an efficient Speech/Music discrimination method that uses spectrum analysis and neural network. The proposed method extracts the duration feature parameter(MSDF) from a spectral peak track by analyzing the spectrum, and it was used as a feature for Speech/Music discriminator combined with the MFSC. The neural network was used as a Speech/Music discriminator, and we have reformed various experiments to evaluate the proposed method according to the training pattern selection, size and neural network architecture. From the results of Speech/Music discrimination, we found performance improvement and stability according to the training pattern selection and model composition in comparison to previous method. The MSDF and MFSC are used as a feature parameter which is over 50 seconds of training pattern, a discrimination rate of 94.97% for speech and 92.38% for music. Finally, we have achieved performance improvement 1.25% for speech and 1.69% for music compares to the use of MFSC.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.805-807
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• 2018

본 논문은 인공 대역 확장에서 스펙트럼 포락선 확장 시 발생하는 스펙트럼 왜곡을 줄이는 개선된 조합 매핑(Improved combined mapping) 알고리즘을 제안한다. 벡터양자화를 기반으로 하는 코드북 매핑(Codebook mapping)과 스펙트럼 포락선(Spectrum Envelope)의 선형 의존도를 이용한 선형 매핑(Linear mapping)을 사용하여 각각 확장된 광대역 LSP(Line Spectrum Pair)를 추론하고, 연판정(Soft-decision)을 통해 최적화된 LSP를 추론한다. 제안된 알고리즘으로 합성된 음성신호의 스펙트럼 왜곡(Spectrum Distortion)이 기존 조합매핑으로 얻은 음성 신호의 스펙트럼 왜곡보다 더 적은 왜곡을 갖는 결과를 나타내었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7B
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• pp.1001-1008
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• 2010

In this paper, we propose the dynamic spectrum allocation (DSA) algorithm using spectrum sharing method considering the long-term priority between NOs and service classes for the maritime communication system environment where a ship locates at either near shore (or land) or off-shore. It was shown that the proposed algorithm using spectrum sharing with priorities could deliver better satisfaction ratio (SR) than the fixed allocation schemes, in the context of provision of required bandwidth (or spectrum) for each users. Therefore, we conclude that the proposed DSA with priorities could apply to the maritime communication environment and exploit the under-used (or unused, idle) spectrum of terrestrial communication networks.

• Science of Emotion and Sensibility
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• v.16 no.3
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• pp.409-416
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• 2013

Attention is one of important cognitive functions in human affecting on the selectional concentration of relevant events and ignorance of irrelevant events. The discrimination of attentional and inattentional status is the first step to manage human's attentional capability using computer assisted device. In this paper, we newly combine the non-linear recurrence pattern analysis and spectrum analysis to effectively extract features(total number of 13) from the electroencephalographic signal used in the input to classifiers. The performance of diverse types of attention-inattention classifiers, including supporting vector machine, back-propagation algorithm, linear discrimination, gradient decent, and logistic regression classifiers were evaluated. Among them, the support vector machine classifier shows the best performance with the classification accuracy of 81 %. The use of spectral band feature set alone(accuracy of 76 %) shows better performance than that of non-linear recurrence pattern feature set alone(accuracy of 67 %). The support vector machine classifier with hybrid combination of non-linear and spectral analysis can be used in later designing attention-related devices.

• Journal of Korea Multimedia Society
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• v.3 no.3
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• pp.241-252
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• 2000

In this paper, a translation, rotation and scale invariant system for the recognition of closed 2-D images using the bispectrum of a contour sequence and a weighted fuzzy classifier is derived and compared with the recognition process using one of the competitive neural algorithm, called a LVQ( Loaming Vector Quantization). The bispectrum based on third order cumulants is applied to the contour sequences of an image to extract fifteen feature vectors for each planar image. These bispectral feature vectors, which are invariant to shape translation, rotation and scale transformation, can be used to the represent two-dimensional planar images and are fed into a weighted fuzzy classifier. The experimental processes with eight different shapes of aircraft images are presented to illustrate a relatively high performance of the proposed recognition system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.6
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• pp.686-698
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• 1989

In this paper, The new algorithm of spectrum moment for format frequency estimation is proposed. The second oder and the third order spectrum moment, which reflect variance and skewness of a spectrum pattern, respectively, is utilized to adjust the frequency region for estimation precision of format frequency. As the results. the F1-F2 diagram reported 8 Korean vowels for man and woman and that we found articulation method of vowel and vowel, vowel and consonant.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.451-454
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• 2007

본 논문은 한국 원자력 연구소 중성자 스펙트럼 패턴을 분류하는 시스템에 신경망(Neural Networks)을 적용하였다. 중성자 스펙트럼 분석시 3개의 신경망을 하나로 결합하여 각 신경망의 인식률을 확인하였다. 신경망1은 폭발물 판별을, 신경망2는 폭발물의 종류를, 신경망3은 비 폭발물 종류를 구별하도록 시스템을 설계하였다. 중성자 스펙트럼을 통해 실험한 결과 신경망1은 83.48%를, 신경망2는 84.6%를, 신경망3은 91.67%의 인식률을 얻어 본 논문에서 제안한 시스템의 우수성을 입증하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.3-6
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• 2007

현재 우리나라는 원자력 발전에 대한 의존도가 매우 높고 그 기술 또한 우수하다. 그러나 중성자 스펙트럼을 사용하여 폭발물 탐지를 위한 시스템 개발 기술은 미흡한 실정이다. 본 논문은 신경망(Neural Networks)을 한국 원자력 연구소 중성자 스펙트럼 패턴을 분류하는 시스템에 적용하였다. 데이터 획득방법을 달리하여 두 개의 신경망을 구현하였고 그 결과를 분석하여 보았다. 먼저 폭발물에 다량 포함되어 있는 C(Carbon), N(Nitrogen), O(Oxygen) 3개의 물질을 중심으로 중성자 스펙트럼을 분석하였다. 다른 하나는 중성자 스펙트럼을 전체 영역으로 획득한 데이터를 바탕으로 신경망을 구현하여 인식률을 확인하였다. 실험결과 전자의 경우 62.5%의 인식률을, 후자의 경우 신경망은 83.48%의 인식률을 나타내었다.

• Journal of the Korean Vacuum Society
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• v.3 no.2
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• pp.212-219
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• 1994

Hot wall epitaxy법에 의하여 GaAs(100)aus 위에 ZnS-ZnSe 초격자를 성장하였다. ZnS-ZnSe 초격자의 주기는 x-선 회절 패턴에 의하여 확인되었고 이것은 변형을 고려하고 계산된 이론적인 패턴과 비교되었다. 경계면에 평행한 ZnS와 ZnSe의 변형의 비는 ZnSe에 대하여 ZnS의 두께기 증가할수록 감 소되었다. ZnS-ZnSe 초격자의 photoluminescence(PL)는 고에너지 영역의 예리한 스펙트럼과 저에너지 영역의 폭이 넓은 스펙트럼으로 구성되어있다. PL의 광자에너지는 Kronig-Penney 모델을 사용하여 계 산된 이론적인 에너지 값과 비교한 결과 type I의 초격자임을 알았다.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.47-54
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• 2005

In the most of speaker recognition system, speaker's characteristics is extracted from acoustic parameter by speech analysis and we make speaker's reference pattern. Parameters used in speaker recognition system are desirable expressing speaker's characteristics fully and being a few difference whenever it is spoken. Therefore we su99est following to solve this problem. This paper is proposed to use strong spectrum characteristic in non-noise circumstance and prosodic information in noise circumstance. In a stage of making code book, we make the number of data we need to combine spectrum characteristic and Prosodic information. We decide acceptance or rejection comparing test pattern and each model distance. As a result, we obtained more improved recognition rate than we use spectrum and prosodic information especially we obtained stational recognition rate in noise circumstance.