• Title/Summary/Keyword: transformation algorithm

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Coordinate Calibration of the ODVS using Delta-bar-Delta Neural Network (Delta-bar-Delta 알고리즘을 이용한 ODVS의 좌표 교정)

  • Kim Do-Hyeon;Park Young-Min;Cha Eui-Young
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.3
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    • pp.669-675
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    • 2005
  • This paper proposes coordinates transformation and calibration algorithm using 3D parabolic coordinate transformation and delta-bar-delta neural algorithm for the omni-directional image captured by catadioptric camera. Experimental results shows that the proposed algorithm has accuracy and confidence in coordinate transformation which is sensitive to environmental variables.

Low Sit Rate Image Coding using Neural Network (신경망을 이용한 저비트율 영상코딩)

  • 정연길;최승규;배철수
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2001.10a
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    • pp.579-582
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    • 2001
  • Vector Transformation is a new method unified vector quantization and coding. So far, codebook generation applied to coding was LBG algorithm. But using the advantage of SOFM(Self-Organizing Feature Map) based on neural network can improve a system's performance. In this paper, we generated VTC(Vector Transformation Coding) codebook applied with SOFM algorithm and compare the result for several coding rates with LBG algorithm. The problem of Vector quantization is complicated calculation and codebook generation. So, to solve this problem, we used neural network approach method.

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Sequential Adaptation Algorithm Based on Transformation Space Model for Speech Recognition (음성인식을 위한 변환 공간 모델에 근거한 순차 적응기법)

  • Kim, Dong-Kook;Chang, Joo-Hyuk;Kim, Nam-Soo
    • Speech Sciences
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    • v.11 no.4
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    • pp.75-88
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    • 2004
  • In this paper, we propose a new approach to sequential linear regression adaptation of continuous density hidden Markov models (CDHMMs) based on transformation space model (TSM). The proposed TSM which characterizes the a priori knowledge of the training speakers associated with maximum likelihood linear regression (MLLR) matrix parameters is effectively described in terms of the latent variable models. The TSM provides various sources of information such as the correlation information, the prior distribution, and the prior knowledge of the regression parameters that are very useful for rapid adaptation. The quasi-Bayes (QB) estimation algorithm is formulated to incrementally update the hyperparameters of the TSM and regression matrices simultaneously. Experimental results showed that the proposed TSM approach is better than that of the conventional quasi-Bayes linear regression (QBLR) algorithm for a small amount of adaptation data.

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Single Image Dehazing Using Linear Transformation of Saturation (채도의 선형 변환을 이용한 단일 영상 안개 제거)

  • Park, Taehee
    • IEMEK Journal of Embedded Systems and Applications
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    • v.14 no.4
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    • pp.197-205
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    • 2019
  • In this paper, an efficient single dehazing algorithm is proposed based on linear transformation by assuming that a linear relationship exists in saturation component between the haze image and haze-free image. First, we analyze the linearity of saturation channel, estimate the medium transmission map in terms of the saturation component. Then, the intensity of haze-free image is assumed by using CLAHE to enhance contrast of haze image. Experimental results demonstrate that proposed algorithm can naturally recover the image, especially can remove color distortion caused by conventional methods. Therefore, our approach is competitive with other state-of-the art single dehazing methods.

Transcoding Algorithm for SMV and G.729A Vocoders via Direct Parameter Transformation (G.729A와 SMV 음성부호화기를 위한 파라미터 직접 변환 방식의 상호부호화 알고리듬)

  • 장달원;서성호;이선일;유창동
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.6
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    • pp.71-83
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    • 2003
  • In this paper, a novel transcoding algorithm for the G.729A and the Selectable Mode Vocoder(SMV) vocoders via direct parameter transformation is proposed. In contrast to the conventional tandem transcoding algorithm, the proposed algorithm converts the parameters of one coder to the other without going through the decoding and encoding processes. In transcoder from SMV to G.729A, LSP conversion algorithm, pitch delay conversion algorithm and transcoding algorithm in lower rate are proposed, and in transcoder from G.729A to SMV, LSP conversion algorithm, pitch delay conversion algorithm and rate selection algorithm are proposed. Evaluation results show that while exhibiting better computational and delay characteristics, the proposed algorithm produces equivalent or Improved speech quality to that produced by the tandem transcoding algorithm.

Identification of Inrush and Internal Fault in Indirect Symmetrical Phase Shift Transformer Using Wavelet Transform

  • Bhasker, Shailendra Kumar;Tripathy, Manoj;Kumar, Vishal
    • Journal of Electrical Engineering and Technology
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    • v.12 no.5
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    • pp.1697-1708
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    • 2017
  • This paper proposes an algorithm for the differential protection of an Indirect Symmetrical Phase Shift Transformer (ISPST) by considering the different behaviors of the compensated differential current under internal fault and magnetizing inrush conditions. In this algorithm, a criterion function is defined which is based on the difference of amplitude of the wavelet transformation over a specific frequency band. The function has been used for the discrimination between three phase magnetizing inrush and internal fault condition and requires less than a quarter cycle after disturbance. This method is independent of any coefficient or threshold values of wavelet transformation. The merit of this algorithm is demonstrated by the simulation of different faults in series and excitation unit and magnetizing inrush with varying switching conditions on ISPST using PSCAD/EMTDC. Due to unavailability of in-field large interconnected transformers for such a large number of destructive tests, the results are further verified by Real Time Digital Simulator (RSCAD/RTDS). The proposed algorithm has been compared with the conventional harmonic restraint based method that justifies the application of wavelet transform for differential protection of ISPST. The proposed algorithm has also been verified for different rating of ISPSTs and satisfactory results were obtained.

The Welding Process Control Using Neural Network Algorithm (Neural Network 알고리즘을 이용한 용접공정제어)

  • Cho Man Ho;Yang Sang Min
    • Journal of the Korean Society for Precision Engineering
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    • v.21 no.12
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    • pp.84-91
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    • 2004
  • A CCD camera with a laser stripe was applied to realize the automatic weld seam tracking in GMAW. It takes relatively long time to process image on-line control using the basic Hough transformation, but it has a tendency of robustness over the noises such as spatter and arc tight. For this reason, it was complemented with adaptive Hough transformation to have an on-line processing ability for scanning specific weld points. The adaptive Hough transformation was used to extract laser stripes and to obtain specific weld points. The 3-dimensional information obtained from the vision system made it possible to generate the weld torch path and to obtain the information such as width and depth of weld line. In this study, a neural network based on the generalized delta rule algorithm was adapted for the process control of GMA, such as welding speed, arc voltage and wire feeding speed.

Walking Assistance System for Sight Impaired People Based on a Multimodal Information Transformation Technique (멀티모달 정보변환을 통한 시각장애우 보행 보조 시스템)

  • Yu, Jae-Hyoung;Han, Young-Joon;Hahn, Hern-Soo
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.5
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    • pp.465-472
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    • 2009
  • This paper proposes a multimodal information transformation system that converts the image information to the voice information to provide the sight impaired people with walking area and obstacles, which are extracted by an acquired image from a single CCD camera. Using a chain-code line detection algorithm, the walking area is found from the vanishing point and boundary of a sidewalk on the edge image. And obstacles are detected by Gabor filter of extracting vertical lines on the walking area. The proposed system expresses the voice information of pre-defined sentences, consisting of template words which mean walking area and obstacles. The multi-modal information transformation system serves the useful voice information to the sight impaired that intend to reach their destination. The experiments of the proposed algorithm has been implemented on the indoor and outdoor environments, and verified its superiority to exactly provide walking parameters sentences.

Fast triangle flip bat algorithm based on curve strategy and rank transformation to improve DV-Hop performance

  • Cai, Xingjuan;Geng, Shaojin;Wang, Penghong;Wang, Lei;Wu, Qidi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.12
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    • pp.5785-5804
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    • 2019
  • The information of localization is a fundamental requirement in wireless sensor network (WSN). The method of distance vector-hop (DV-Hop), a range-free localization algorithm, can locate the ordinary nodes by utilizing the connectivity and multi-hop transmission. However, the error of the estimated distance between the beacon nodes and ordinary nodes is too large. In order to enhance the positioning precision of DV-Hop, fast triangle flip bat algorithm, which is based on curve strategy and rank transformation (FTBA-TCR) is proposed. The rank is introduced to directly select individuals in the population of each generation, which arranges all individuals according to their merits and a threshold is set to get the better solution. To test the algorithm performance, the CEC2013 test suite is used to check out the algorithm's performance. Meanwhile, there are four other algorithms are compared with the proposed algorithm. The results show that our algorithm is greater than other algorithms. And this algorithm is used to enhance the performance of DV-Hop algorithm. The results show that the proposed algorithm receives the lower average localization error and the best performance by comparing with the other algorithms.

A Generalized Subspace Approach for Enhancing Speech Corrupted by Colored Noise Using Whitening Transformation (유색 잡음에 오염된 음성의 향상을 위한 백색 변환을 이용한 일반화 부공간 접근)

  • Lee, Jeong-Wook;Son, Kyung-Sik;Park, Jang-Sik;Kim, Hyun-Tae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.8
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    • pp.1665-1674
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    • 2011
  • In this paper, we proposed an algorithm for speech enhancement of speeches corrupted by colored noise. When there is no correlation between colored noise and speech signal, the colored noise turns into white noise through whitening transformation. This transformed signal has been applied to the generalized subspace approach for speech enhancement. The speech spectral distortion, produced by the whitening transformation as pre-processing, has been restored by using the inverse whitening transformation as post-processing of the proposed algorithm. The performance of the proposed algorithm for speech enhancement has been confirmed by computer simulation. The colored noises used in this experiment were car noise and multi-talker babble. It is confirmed that the proposed algorithm shows better performance from SNR and SSD viewpoint over the previous approach with the data from the AURORA and TIMIT data base.