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Publisher: SpringerSubject: Artificial neural network

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    Article
    Citation - WoS: 12
    Citation - Scopus: 19
    Artificial Neural Network Channel Estimation Based on Levenberg-Marquardt for Ofdm Systems
    (Springer, 2009) Ciflikli, Cebrail; Ozsahin, A. Tuncay; Yapici, A. Cagri
    The many advantages responsible for the widespread application of orthogonal frequency division multiplexing (OFDM) systems are limited by the multipath fading. In OFDM systems, channel estimation is carried out by transmitting pilot symbols generally. In this paper, we propose an artificial neural network (ANN) channel estimation technique based on levenberg-marquardt training algorithm as an alternative to pilot based channel estimation technique for OFDM systems over Rayleigh fading channels. In proposed technique, there are no pilot symbols which added to OFDM. Therefore, this technique is more bandwidth efficient compared to pilot-based channel estimation techniques. Also, this technique is making full use of the learning property of neural network. By using this feature, there is no need of any matrix computation and the proposed technique is less complex than the pilot based techniques. Simulation results show that ANN based channel estimator gives better results compared to the pilot based channel estimator for OFDM systems over Rayleigh fading channel.
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    Article
    Citation - WoS: 6
    Citation - Scopus: 6
    Comparison of Different Calibration Techniques of Laser Induced Breakdown Spectroscopy in Bakery Products: on Nacl Measurement
    (Springer, 2021) Bilge, Gonca; Eseller, Kemal Efe; Berberoglu, Halil; Sezer, Banu; Tamer, Ugur; Boyaci, Ismail Hakki
    Laser induced breakdown spectroscopy (LIBS) is a rapid optical spectroscopy technique for elemental determination, which has been used for quantitative analysis in many fields. However, the calibration involving atomic emission intensity and sample concentration, is still a challenge due to physical-chemical matrix effect of samples and fluctuations of experimental parameters. To overcome these problems, various chemometric data analysis techniques have been combined with LIBS technique. In this study, LIBS was used to show its potential as a routine analysis for Na measurements in bakery products. A series of standard bread samples containing various concentrations of NaCl (0.025%-3.5%) was prepared to compare different calibration techniques. Standard calibration curve (SCC), artificial neural network (ANN) and partial least square (PLS) techniques were used as calibration strategies. Among them, PLS was found to be more efficient for predicting the Na concentrations in bakery products with an increase in coefficient of determination value from 0.961 to 0.999 for standard bread samples and from 0.788 to 0.943 for commercial products.