Lerkvaranyu, Somkiat

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Lerkvaranyu, Somkiat
Alternative Name
Lerkvaranyu, S.
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Email
somkiat.le@kmitl.ac.th

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    Wide-band CMOS precision rectifier circuit
    (2008-12-01)
    Kumngern, Montree
    ;
    Lerkvaranyu, Somkiat
    ;
    Dejhan, Kobchai
    A wide-band precision CMOS rectifier, which is very suitable for integrated circuit implementation, is presented. The proposed circuit consists of a voltage-to-current converter, two precision rectifiers and four current-to-voltage converters that performs positive half-wave, negative half-wave, positive full-wave and a negative full-wave rectifications into a single circuit. The precision current-mode rectifier with operating in class-AB is employed to provide the high-frequency capability of the circuit. The circuit exhibits a very versatility, high operating frequency and good temperature stability The proposed configuration is very suitable for integrated circuit implementation both CMOS and bipolar technologies. The simulation results in CMOS technology demonstrate the performance of the proposed circuit. © 2008 IEEE.
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    M-QAM demodulation in an OFDM system with RBF neural network
    (2004-12-01)
    Lerkvaranyu, Somkiat
    ;
    Dejhan, Kobchai
    ;
    Miyanaga, Yoshikazu
    This paper proposes a method which improves the M-QAM demodulation in the orthogonal frequency division multiplexing (OFDM). The OFDM has several advantages, i.e., the possibility of a simple equalization of the received signal. However, the disadvantages are also considered as the phase ambiguity due to intercarrier-interference (ICI) which causes the significant degradation on the performance of an OFDM system. The proposed method is a radial basis function (RBF) neural network which learns the characteristic of M-QAM signal constellation before reconstructing the correct signal constellation under noisy circumstances. The hybrid learning process is used to train the RBF network. The hidden layer is trained by the hard c means clustering. The supervised learning with given input-output pairs are used to train the output layer. This paper assumes an additive white Gaussian noise (AWGN) channel. The simulation results of the random symbol generations show that the probability of errors closes to ideal with the proposed method. OFDM, QAM demodulation, Self-organized clustering.
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    Atmospheric boundary layer observation by ground-based lidar at KMITL, Thailand (13° N, 100° E)
    (2001-01-01)
    Lerkvaranyu, Somkiat
    ;
    Dejhan, Kobchai
    ;
    Cheevasuvit, Fusak
    ;
    Itabe, Toshikasu
    ;
    Mizutani, Kohei
    Tropospheric aerosols effects on climate in directly through various cloud formation, the lidar has been used to study the composition of many particles mixing in the atmosphere including to study the aerosol and cloud. Currently, it has many types of lidar systems depending on the purpose of measurements. In this report, the ground-based lidar system was established at King Mongkut's Institute of Technology Ladkrabang (KMITL), THAILAND to study and measure the aerosol in boundary layer and cirrus clouds in the tropopause region. The aerosol measurement is in the form of scattering ratio whereas the signal depolarization has been applied to identify layers of cirrus clouds. The lidar system consists of laser source (Nd:YAG) with second harmonic wavelength, 28 cm Schmidt-Cassegrain telescope, photomultiplier tube (PMT) and data acquisition system.
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    Automatic indexing system for atmospheric laser radar data
    (2002-01-01)
    Lerkvaranyu, S.
    ;
    Miyanaga, Y.
    ;
    Dejhan, K.
    ;
    Cheevasuvit, F.
    ;
    Mizutani, K.
    The purpose of this paper is to design a new method for an automatic indexing system with unsupervised conditions. In this paper, the method of a self-organizing clustering network is adopted. It is used to classify and index a large amount of real atmospheric laser radar data. Initially, the parameters of each cluster will start with random initial values and are adapted with the algorithm. In this paper, six groups are clustered from the given data. It is also shown that some of these indicate quite important atmospheric condition characteristics.