• Title/Summary/Keyword: pattern recognition

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Syntatic Pattern recognition of the ECG (심전도 신호의 신택틱 패턴인식)

  • Nam, Seung-Woo;Lee, Byung-Cha;Sin, Kun-Su;Lee, Jae-Jun;Lee, Myung-Hoo
    • Proceedings of the KOSOMBE Conference
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    • v.1991 no.11
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    • pp.129-132
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    • 1991
  • This paper describes the ECG pattern recognition using the syntatic pattern recognition algorithm. The algorithm uses the BNF rule wi th the semantic evaluation which has the structural Information of the ECG. This algorithm is constructed with (1) removing the baseline drift by the Cubic spline function and exract the significant point by the line-approximation algorithm, (2) syntatic peak recognition algorithm with the extracted significant point, (3) produce the token which is used pattern recognition, (4) pattern recognition of the ECG by the syntatic pattern recognition algorithm, (5) extract the parameter with the pattern recognized ECG signal.

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Smart pattern recognition of structural systems

  • Hassan, Maguid H.M.
    • Smart Structures and Systems
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    • v.6 no.1
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    • pp.39-56
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    • 2010
  • Structural Control relies, with a great deal, on the ability of the control algorithm to identify the current state of the system, at any given point in time. When such algorithms are designed to perform in a smart manner, several smart technologies/devices are called upon to perform tasks that involve pattern recognition and control. Smart pattern recognition is proposed to replace/enhance traditional state identification techniques, which require the extensive manipulation of intricate mathematical equations. Smart pattern recognition techniques attempt to emulate the behavior of the human brain when performing abstract pattern identification. Since these techniques are largely heuristic in nature, it is reasonable to ensure their reliability under real life situations. In this paper, a neural network pattern recognition scheme is explored. The pattern identification of three structural systems is considered. The first is a single bay three-story frame. Both the second and the third models are variations on benchmark problems, previously published for control strategy evaluation purposes. A Neural Network was developed and trained to identify the deformed shape of structural systems under earthquake excitation. The network was trained, for each individual model system, then tested under the effect of a different set of earthquake records. The proposed smart pattern identification scheme is considered an integral component of a Smart Structural System. The Reliability assessment of such component represents an important stage in the evaluation of an overall reliability measure of Smart Structural Systems. Several studies are currently underway aiming at the identification of a reliability measure for such smart pattern recognition technique.

Chemometric Tool of Chromatographic Pattern Recognition for the Analysis of Complex Mixtures

  • Park, Man-Ki;Park, Jeong-Hill;Cho, Jung-Hwan;Kim, Na-Young;Kang, Jong-Seong
    • Archives of Pharmacal Research
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    • v.15 no.4
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    • pp.376-378
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    • 1992
  • A chemical tool was developed for the analysis of complex mixtures such as crude drugs by the method of pattern recognition. Pattern recognition was accomplished by a multiple reference peak identification method and three kinds of outlier statistics. This tool was tested on the analysis of synthetic mixtures.

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A Study of ECG Pattern Classification of Using Syntactic Pattern Recognition (신택틱 패턴 인식 알고리즘에 의한 심전도 신호의 패턴 분류에 관한 연구)

  • 남승우;이명호
    • Journal of Biomedical Engineering Research
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    • v.12 no.4
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    • pp.267-276
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    • 1991
  • This paper describes syntactic pattern recognition algorithm for pattern recognition and diagnostic parameter extraction of ECG signal. ECG signal which is represented linguistic string is evaluated by pattern grammar and its interpreter-LALR(1) parser for pattern recognition. The proposed pattern grammar performs syntactic analysis and semantic evaluation simultaneously. The performance of proposed algorithm has been evaluated using CSE database.

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A Study on the Pattern Recognition Using Support Vector Fuzzy Inference System (Support Vector Fuzzy Inference System을 이용한 Pattern Recognition 에 관한 연구)

  • 김용균;정은화
    • Proceedings of the Korea Multimedia Society Conference
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    • 2003.05b
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    • pp.374-379
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    • 2003
  • 본 논문에서는 pattern recognition을 위하여 support vector fuzzy inference system을 제안하였다 Fuzzy inference system의 structure와 parameter를 identification 하기 위하여 Support vector machine을 이용하였으며 에러 최소화 기법으로는 gradient descent 방법을 사용하였다. 제안된 SVFIS 방법의 성능을 파악하고자 COIL 이미지를 이용한 3차원 물체 인식 실험을 수행하였다.

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Affine-Invariant Image normalization for Log-Polar Images using Momentums

  • Son, Young-Ho;You, Bum-Jae;Oh, Sang-Rok;Park, Gwi-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1140-1145
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    • 2003
  • Image normalization is one of the important areas in pattern recognition. Also, log-polar images are useful in the sense that their image data size is reduced dramatically comparing with conventional images and it is possible to develop faster pattern recognition algorithms. Especially, the log-polar image is very similar with the structure of human eyes. However, there are almost no researches on pattern recognition using the log-polar images while a number of researches on visual tracking have been executed. We propose an image normalization technique of log-polar images using momentums applicable for affine-invariant pattern recognition. We handle basic distortions of an image including translation, rotation, scaling, and skew of a log-polar image. The algorithm is experimented in a PC-based real-time vision system successfully.

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Color Pattern Recognition with Recombined Single Input Channel Joint Transform Correlator

  • Jeong, Man-Ho
    • Journal of the Optical Society of Korea
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    • v.15 no.2
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    • pp.140-145
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    • 2011
  • Joint transform correlator (JTC) is a well known tool for color pattern recognition for a color image. Color images have red, green and blue components, thus in conventional JTC, three input channels of these color components are necessary for color pattern recognition. This paper proposes a new technique of color pattern recognition by decomposing the color image into three color components and recombining those components into a single gray image in the input plane. This new technique needs single input channel and single output CCD camera, thus a simple JTC can be used. We present various kinds of simulated results to show that our newly proposed technique can accurately recognize and discriminate color differences.

Comparison of invariant pattern recognition algorithms (불변 패턴인식 알고리즘의 비교연구)

  • 강대성
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.8
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    • pp.30-41
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    • 1996
  • This paper presents a comparative study of four pattern recognition algorithms which are invariant to translations, rotations, and scale changes of the input object; namely, object shape features (OSF), geometrica fourier mellin transform (GFMT), moment invariants (MI), and centered polar exponential transform (CPET). Pattern description is obviously one of the most important aspects of pattern recognition, which is useful to describe the object shape independently of translation, rotation, or size. We first discuss problems that arise in the conventional invariant pattern recognition algorithms, or size. We first discuss problems that arise in the coventional invariant pattern recognition algorithms, then we analyze their performance using the same criterion. Computer simulations with several distorted images show that the CPET algorithm yields better performance than the other ones.

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A study on the method for distinguishing general from science-inclined learners by using Pattern Recognition (패턴인식을 이용한 과학영재 판별 도구에 관한 연구)

  • Bang, Seung-Jin;Choi, Jung-Oh;Kim, Hyouk
    • Communications of Mathematical Education
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    • v.20 no.4 s.28
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    • pp.551-559
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    • 2006
  • Pattern Recognition measures the ability of learners to distinguish between two sets of shapes or figures. Locating similar patterns on either side of the presented problem determines a learner's capacity or aptitude for science over general studies. At Ajou University's Institute for Scientifically Enabled Youth, we conducted research using a sample composed of middle school students with general and scientific backgrounds. The result proved that Pattern Recognition measures a different creative talent other than problem solving. In our opinion, Pattern Recognition would be a method better suited to elementary learners over those in middle or high school.

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Development and Characterization of Pattern Recognition Algorithm for Defects in Semiconductor Packages

  • Kim, Jae-Yeol;Yoon, Sung-Un;Kim, Chang-Hyun
    • International Journal of Precision Engineering and Manufacturing
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    • v.5 no.3
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    • pp.11-18
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    • 2004
  • In this paper, the classification of artificial defects in semiconductor packages is studied by using pattern recognition technology. For this purpose, the pattern recognition algorithm includes the user made MATLAB code. And preprocess is made of the image process and self-organizing map, which is the input of the back-propagation neural network and the dimensionality reduction method, The image process steps are data acquisition, equalization, binary and edge detection. Image process and self-organizing map are compared to the preprocess method. Also the pattern recognition technology is applied to classify two kinds of defects in semiconductor packages: cracks and delaminations.