• Title/Summary/Keyword: neural network(NN)

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One Channel Five-Way Classification Algorithm For Automatically Classifying Speech

  • Lee, Kyo-Sik
    • The Journal of the Acoustical Society of Korea
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    • v.17 no.3E
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    • pp.12-21
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    • 1998
  • In this paper, we describe the one channel five-way, V/U/M/N/S (Voice/Unvoice/Nasal/Silent), classification algorithm for automatically classifying speech. The decision making process is viewed as a pattern viewed as a pattern recognition problem. Two aspects of the algorithm are developed: feature selection and classifier type. The feature selection procedure is studied for identifying a set of features to make V/U/M/N/S classification. The classifiers used are a vector quantization (VQ), a neural network(NN), and a decision tree method. Actual five sentences spoken by six speakers, three male and three female, are tested with proposed classifiers. From a set of measurement tests, the proposed classifiers show fairly good accuracy for V/U/M/N/S decision.

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Blotch Detection using Color and Shape feature (컬러와 형태 특징을 이용한 블로치 검출)

  • Kim, Byung-Geun;Kim, Kyung-Tai;Kim, Eun-Yi
    • 한국HCI학회:학술대회논문집
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    • 2009.02a
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    • pp.547-551
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    • 2009
  • In recent years, a film restoration has gained increasing attention by many researchers, to emergence of variety multimedia and to importance of video preservation. Blotch is the most frequent degradation in old film. This paper presents a blotch detection method using color and shape feature. The proposed method is two major modules: a SROD detector using impulsive feature and NN-based detector using shape feature. To assess the validity of the proposed method, the experiments have been performed on several old films.

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Time-Efficient, Repetitive Predictions of the Performance of PEMFCs Based on a Neural Network-Based, Reduced Order Model

  • Shin Dong-Il;Oh Tae-Hoon;Park Myong-Nam;Rengaswamy Raghunathan
    • Journal of the Korean Institute of Gas
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    • v.10 no.2 s.31
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    • pp.55-60
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    • 2006
  • Detailed modeling of PEMFCs has been getting considerable interest for predicting the fuel cell performance and also for use in various systems engineering activities. While CFD-based equipment models provide detailed analyses of the performance, they are very time-consuming to develop and run. The computations become quite complex when such models have to be embedded into the flowsheet-level optimization of fuel cell systems. In this paper, we present results about building and using NN-based reduced order models for quickly and repetitively predicting the flow of reactants in a PEMFC manifold.

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LMS기반의 신경회로망 알고리즘을 이용한 선박소음 능동소음제어를 위한 연구

  • Jang, Hyeon-Seok;Lee, Gwon-Sun
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2012.06a
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    • pp.257-259
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    • 2012
  • 친환경 시대로 나아가는 현재, 능동소음제어는 저주파소음을 줄이기 위한 좋은 방법이다. 또한 수동소음제어만으로 선박소음을 제어하기에는 물리적인 무게가 심각히 가중되어 한계를 가지게 된다. ANC 시스템은 이러한 문제를 해결해 줌과 더불어 다양하게 변화하는 환경소음까지 줄여주는 특성을 가지고 있다. 우리는 본 논문에서 선박의 환경소음을 줄이기 위하여 LMS 알고리즘과 신경회로망 알고리즘을 기반으로하는 ANC 시스템을 제안한다. 먼저 선박과 유사한 유도전동기의 소음을 측정하고 다음으로 ANC 시스템을 위한 LMS 구조를 구축한다. 그리고 소음의 비정치와 불확실성 때문에 단층 퍼셉트론 모델로 디자인된 신경회로망 알고리즘을 추가하여 실시간으로 소음을 줄이도록 하였다. 이 하이브리드 ANC 시스템은 최급강하기법의 방법으로 파라미터 값들이 온라인으로 실시간 추정되며, 제안된 ANC 시스템은 컴퓨터 시뮬레이션을 이용하여 그 성능을 분석하였다.

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A Study on Realization of Function Code for Fuzzy Control in the Continuous Casting Process of the Iron & Steel Works (제철소 연속주조 공정에서의 퍼지제어를 위한 기능코드의 구현 연구)

  • ;;;Zeungnam Bien
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.12
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    • pp.1545-1551
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    • 1995
  • As the modern industrial processes become more complex, it is getting more difficult to model and control the processes. Naturally, an advanced type of DCS(Distributed Control System) with higher level functions is being sought. Advanced DCS is a DCS with advanced functions such as fault diagnosis, GPC(Generalized Predictive Control), NN(Neural Network), and Fuzzy Control. In this thesis, we have studied a fuzzy control algorithm for realizing an advanced DCS. Its algorithm is implemented in a form of function code which is a process control language, being used by the industrial engineers. To verify the realized function code of the fuzzy control, the function code is applied to a continuous casting process of the Pohang Iron & Steel Works in Kwangyang. The rules of the fuzzy control were collected via interviews of the field operators and their operation documents. Finally under a real-time operating system environment, usability of the function code of the fuzzy control is shown via simulation for the continuous casting process.

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Calibration of Scanner at Color Inspection of printed Texture (직물의 색상검사에서 스캐너의 편차 보정)

  • 정병묵;조지승;박무진
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2002.10a
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    • pp.383-386
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    • 2002
  • It is very important to inspect color of printed texture in the textile process. To distinguish the color of the printed texture, RGB color values obtained from a scanner must be transformed to the standard colorimetric system used in the textile industry. It is XYZ color system that is defined by CIE(Commission Internationale do 1Eclairage). The mapping from RGB to XYZ color values is not simple and the scanner has even a positional deviation of RGB colors. In this paper an automatic color inspection method using a general scanning machine is presented. We used a U(neural network) model to map RGB to XYZ and compensate the positional error. In the real experiments, this inspection system shows to get very exact XYZ values from the traditional scanner regardless of the measuring position.

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A Study on the Load Frequency Control of 2-Area Power System Using Neural Network PID Controller (신경회로망 PID 제어기를 이용한 전력계통의 부하주파수제어에 관한 연구)

  • Chong, H.H.;Kim, S.H.;Joo, S.M.;Kim, K.H.;Yoo, J.Y.
    • Proceedings of the KIEE Conference
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    • 1997.07c
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    • pp.1021-1024
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    • 1997
  • This paper has presented a method for self-tuning tile PID controller using a BP method of multilayered NNs. The proposed controller employ input signal as a learning signal of PID control. The proposed controller is applied to load-frequency control of power system and it is investigated a dynamic characteristic. The simulation results shows that proposed NN STPID controller has the good dynamics responses against load disturbances.

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The Normalization and Statistical Distril in Partial Discharge Quantities and Patter (PD패턴과 방전량의 통계적 분포 및 정규화)

  • Lim, Jang-Seob;Lee, Jin;Kim, Duck-Keun
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 1999.05a
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    • pp.161-164
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    • 1999
  • Estimation system of aging diagnosis using partial discharge(PD) is being highlighted as a research area for the residual lifetime pridiction of industrial equipment. But the application of PD requires complicated analysis method as expert system because the PD has complex progressing forms according to external stress. In this paper, it has been investigated the statistical distribution to express the 2D PD patterns of the diagnosis system using neural network(NN).

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A Study on Realization method of Fuzzy Control Algorithm for DCS (DCS에 퍼지제어 알고리즘 구현방법에 관한 연구)

  • Hur, Yone-Gi;Bien, Zeung-Nam
    • Proceedings of the KIEE Conference
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    • 1995.07b
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    • pp.995-998
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    • 1995
  • As the modern industrial processes become more complex, it is getting more difficult to model and control the processes. Naturally, an advanced type of DCS(Distributed Control System) with higher level functions is being sought Advanced DCS is a DCS with advanced functions such as fault diagnosis, GPC(Generalized Predictive Control), NN(Neural Network), and Fuzzy Control. In this thesis, we have studied a fuzzy control algorithm for realizing an advanced DCS. Its algorithm is implemented in a form of function code which is a process control language, being used by the industrial engineers. To verify the realized function code of the fuzzy control, the function code is applied to a continuous casting process of the Pohang Iron & Steel Works in Kwangyang. The rules of the fuzzy control were collected via interviews of the field operators and their operation documents. Finally, usability of the function code of the fuzzy control is shown via simulation for the continuous casting process model.

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Comparison of Classification Rate Between BP and ANFIS with FCM Clustering Method on Off-line PD Model of Stator Coil

  • Park Seong-Hee;Lim Kee-Joe;Kang Seong-Hwa;Seo Jeong-Min;Kim Young-Geun
    • KIEE International Transactions on Electrophysics and Applications
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    • v.5C no.3
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    • pp.138-142
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    • 2005
  • In this paper, we compared recognition rates between NN(neural networks) and clustering method as a scheme of off-line PD(partial discharge) diagnosis which occurs at the stator coil of traction motor. To acquire PD data, three defective models are made. PD data for classification were acquired from PD detector. And then statistical distributions are calculated to classify model discharge sources. These statistical distributions were applied as input data of two classification tools, BP(Back propagation algorithm) and ANFIS(adaptive network based fuzzy inference system) pre-processed FCM(fuzzy c-means) clustering method. So, classification rate of BP were somewhat higher than ANFIS. But other items of ANFIS were better than BP; learning time, parameter number, simplicity of algorithm.