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    A study on the system imbalance of the single-switch converter for the conductive common mode noise reduction
    (2007-01-01)
    Boonpirom, Nimit
    ;
    Prempraneerach, Yothin
    ;
    Paithoonwatanakij, Kitti
    ;
    Aunchaleevarapan, Kraison
    ;
    Nitta, Shuichi
    This paper reduces system imbalance by replacing the single-switch converter with a synchronized double-switch converter based on two active switches technique and hybrid balance technique, including active balance and passive balance for common mode noise reduction. The system balance is experimentally evaluated by the common mode rejection ratio (CMRR). Finally, examples show that the CMRR of the single-switch converter is improved from 1.67 dB to 32.04 dB when the double-converter with two active switches technique is applied and to 41.5 dB when the double-switch converter with hybrid balance technique is applied. Copyright © 2007 The Institute of Electronics, Information and Communication Engineers.
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    Automated Edge Detection by a Fuzzy Morphological Gradient
    (2003-01-01)
    Intajag, Sathit
    ;
    Paithoonwatanakij, Kitti
    Edge detection has been an essential step in image processing, and there has been much work undertaken to date. This paper inspects a fuzzy mathematical morphology in order to reach a higher-level of edge-image processing. The proposed scheme uses a fuzzy morphological gradient to detect object boundaries, when the boundaries are roughly defined as a curve or a surface separating homogeneous regions. The automatic edge detection algorithm consists of two major steps. First, a new version of anisotropic diffusion is proposed for edge detection and image restoration. All improvements of the new version use fuzzy mathematical morphology to preserve the edge accuracy and to restore the images to homogeneity. Second, the fuzzy morphological gradient operation detects the step edges between the homogeneous regions as object boundaries. This operation uses geometrical characteristics contained in the structuring element in order to extract the edge features in the set of edgeness, a set consisting of the quality values of the edge pixels. This set is prepared with fuzzy logic for decision and selection of authentic edge pixels. For experimental results, the proposed method has been tested successfully with both synthetic and real pictures.
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    Novel method for predicting PCB configurations for near-field and far-field radiated EMI using a neural network
    (2003-01-01)
    Aunchaleevarapan, Kraison
    ;
    Paithoonwatanakij, Kitti
    ;
    Khan-Ngern, Werachet
    ;
    Nitta, Shuichi
    The Neural Network (NN) is applied to recognize basic PCB configurations using its magnetic near-field spectra and radiated far-field emission. The learning process is accomplished by using the computed spectra of the radiated field from PCBs having different configurations. The anomaly is detected through the monitoring of the spectra's amplitude frequency by injecting a voltage pulse at the PCB configuration. The trained NN is then applied to the identification of PCB layouts from radiated emission measurements. The trained NN can identify all of those PCB configurations from the magnetic near-field spectra and the radiated far-field EMI. Moreover, the calculated results of the NN are compared with the actual far-field measurements and other models for evaluation. Finally, the NN used for predicting far-field emission from their magnetic near-field measurement is proposed. Experiments show that the NN can predict the far-field spectra from the magnetic near-field spectra.
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    Automated boundary extraction by gradient fuzzy gray-scale hit-or-miss transformation
    (2000-12-01)
    Intajag, Sathit
    ;
    Paithoonwatanakij, Kitti
    The fuzzy Gray-Scale Hit-or-Miss Transformation (GHMT) is a fuzzy morphology operator, which is a key for the feature extraction in the ambiguous information. In this paper, we propose a novel concept of gradient fuzzy GHMT that is employed for automatically extracting a boundary of the multi-scale pictures. The edge enhancement with a morphological anisotropic diffusion coefficient capability can smooth the noisy region while preserving the edge location. The gradient of the fuzzy GHMT utilizes a set of the structuring elements to detect the edge strength with a view to decrease the spurious edge and suppressed the noise. Results will be presenting both for the synthetic and the natural images in comparison with the others morphological edging detector.