A new adaptive neuro-fuzzy solution for optimization of the parameters in the digital holography setup

In this paper, a fuzzy interference and an adaptive neuro-fuzzy interference system models have been presented in order to accelerate designing of the digital holographic setup without experiment. The setting parameters of experimental holographic setup, which affect the quality of images obtained from reconstructed holograms, are predicted digitally by proposed models before the recording process. Hence, we reduce the required time for designing of digital holographic setup with optimization process. The adaptive neuro-fuzzy interference system model for the optimization of the digital holographic setup is first attempt in the literature. The accuracy of the proposed models is examined by comparing the presented models and actual calculated experimental root-mean-square values. As a result, the accuracy of the adaptive neuro-fuzzy interference system shows the better performance than the fuzzy interference system. Moreover, the design of experimental setup can be occurred numerically in a short time by using adaptive neuro-fuzzy interference system models.