Zehra Sarac

Optimization of digital holographic setup by a fuzzy logic prediction system

We optimize digital holographic setup parameters via fuzzy logic prediction system.The required time for optimization is prevented by using proposed system.The normalized root mean square values are predicted without experimental study. In this study, the optimization of the digital holography setup is achieved by a using fuzzy logic prediction system. In fact, when this optimization process is experimentally performed, some parameters are changed in the setup. These parameters affect directly the obtained image quality after a reconstruction process, which is determined by normalized root mean square. The aim of this study is to achieve the optimization of digital holographic setup by using both experimental and fuzzy logic prediction systems. Furthermore, the required time during the experimental optimization can be lowered by using a numerical method like the fuzzy logic prediction system. Here, the experimental optimization results and the optimization results obtained by the fuzzy logic prediction system are compared. It is offered that the designed experimental system can be optimized by using an artificial intelligent tool. The applied fuzzy logic prediction model is used the first time for optimization of hologram recording setup. As a result, it is reached a conclusion that the optimization of digital holographic setup can be numerically performed by the fuzzy logic prediction system. Moreover, while digital holographic setup is experimentally designed, the required time for optimization is reduced, as well.

Image reconstruction from phase hologram obtained by using single phase information

In this study, it is aimed to obtain the real time image of the object, whose off-axis hologram recording is saved on CCD camera, from digital phase hologram. For creating the phase hologram, the phase information of the hologram recording on CCD camera is obtained. When the phase information is obtained, the Fourier transform algorithm and continuous wavelet transform methods are used. Finally, the using methods in this study are compared in terms of obtaining real time image having a high image quality and minimum power loss.

Resonance analysis of a solid state controlled Tesla transformer

A Tesla transformer is a source that can generate high voltage with high frequency. It is also known a resonance system becomes two air cored coils. Classic Tesla transformer system consists of a high voltage generator which is usually a Neon Sign Transformer (NST), high voltage capacitor and spark gap electrodes. This paper presents mathematical analysis of the equivalent circuit, measure/calculation of its parameters, reasons of resonance, examine of resonance frequencies and a simple solid state driver with a low voltage in the primary side for a Tesla transformer.

Optical signal processing of interference fringes by Hartley transform method

In this paper, the processing of interference fringes is achieved by Hartley transform method. The experimental and simulated interference fringe patterns are used for the signal analysis. Phase results are presented. These are compared with phase obtained by Fourier transform method. Disadvantages and advantages of Hartley transform method used for the evaluation of interference fringe patterns are given.

Prediction of wind speed with non-linear autoregressive (NAR) neural networks

In this study, the wind speed prediction model is created that gives a minimum error for different hidden layer neuron numbers and delay step numbers. Using the one-minute time series, the prediction of the next wind speed is performed with the NAR neural network model. The predicted values of wind speed obtained are compared with predicted values of wind speed obtained with filter methods. For different window functions and lengths, wind speed prediction is made using filters with different weight coefficients. For the number of hidden layer neurons is 14 and the number of delay steps is 10, MAE, MSE and RMSE values are calculated as 0.0315, 0.0019, 0.0445, respectively, with NAR neural network. It is seen that the proposed method for the wind speed dataset has a higher prediction performance than thefilter methods.

Classification of power quality disturbances with S-transform and artificial neural networks method

In this study, classification of 11 different Power Quality (PQ) disturbances with Artificial Neural Networks (ANN) has been done by using the attributes obtained with S-Transform. It was aimed to achieve accurate and high classification performance in noisy environment by using the least number of attributes representing PQ disturbances. The most suitable ones from the attributes were selected by Sequential Forward Selection (SFS) method. The performance of models with different hidden layer neuron numbers tested at different noise levels (40 dB, 30 dB and 20 dB) by using the selected attributes. In this study, it was found that for the most appropriate number of attributes and optimal model parameters, performance in noisy environment (20 dB) and overall performance were 99.0%.

The fast optimization of digital holography system

In digital holography applications, the position of the object, which is in the system, substantially affects the quality and clarity of three dimensional reconstructed image obtained from hologram. Therefore, obtaining a good three dimensional image by locating the image to be reconstructed in the correct position in the system, can sometimes take a long time. The usage of artificial intelligence algorithms instead of capturing the best images by recording the image several times and reduction of this time would be wise. For the first time in this study by using the classification method approach used in artificial neural networks, which is an artificial intelligence methods, the best image is obtained with optimization via software, not on the digital holographic system. The three important features that affected the system, while the holographic setup is constructing, are examined for 142 different situations and the results of these situations are classified into 5 different classes. After classification by using artificial neural networks, the random values are taken for the test process of the trained system and the performance of the system is determined.

A reconfigurable microwave photonic filter based on four wave mixing in a silicon nanophotonic waveguide

We describe the design and characterization of a silicon nanophotonic waveguide (SNW) and its use in a reconfigurable microwave photonic filter (MPF). The SNW is dispersion tailored for efficient on-chip four-wave-mixing. We use the onchip four-wave-mixing to increase the number of taps in our multiple tap delay line MPF. The tap levels are controlled by a programmable filter. Using a 12 mm long SNW reduces the footprint by five orders of magnitude compared to silica highly nonlinear fiber while only requiring approximately two times more input power.

Optical reconstruction of three-dimensional object from digital holograms using phase information calculated by continuous wavelet transform

We propose to record digital Fourier hologram of a 3D diffused object and to reconstruct numerically and optically by using phase-only information. This phase-only information is obtained by using 1D-Continuous Wavelet Transform (1DCWT) from the intensity of digital Fourier Hologram. 3D object image is obtained by numerical reconstruction on computer and optical reconstruction by using a phase-modulated liquid crystal spatial light modulator (SLM). Numerical and experimental results are presented.

Effect of filtering on processing of thermal lens fringes by single sideband modulation technique

This paper proposes the use of single sideband modulation technique with Gaussian and band pass filters for the analysis of the thermal lens fringe to obtain the map of the refractive index change.. Maps of the refractive index and phase change are achieved by using single side band modulation technique with Gaussian and band pass filters. Consequently, it is seen that single side band modulation technique with Gaussian filter shows more accurate results.