Şaban Özer

Bio: Şaban Özer is an academic researcher from Erciyes University. The author has contributed to research in topics: Nonlinear system & System identification. The author has an hindex of 8, co-authored 28 publications receiving 270 citations.

System identification using Hammerstein model optimized with differential evolution algorithm

Abstract: This paper aims to improve Hammerstein model for system identification area. Hammerstein model block structure is formed by cascade of linear and nonlinear parts. In literature, memoryless polynomial nonlinear (MPN) model for nonlinear part and finite impulse response (FIR) model or infinite impulse response (IIR) model for linear part are mostly preferred for Hammerstein models. In this study, a Hammerstein model is presented which is obtained by cascade form of a nonlinear second order volterra (SOV) and a linear FIR model. In addition, proposed Hammerstein model is optimized with differential evolution algorithm (DEA). In simulations, different types of systems are identified by proposed Hammerstein model. Also, performance of the proposed model is compared with different model performances. In conclusion it can be said that the main benefit of this study is that simulation results reveal the effectiveness and robustness of the proposed model.

Fuzzy associative memories for the computation of the bandwidth of rectangular microstrip antennas with thin and thick substrates

Abstract: A method based on fuzzy associative memories for calculating the bandwidth of electrically thin and thick rectangular microstrip patch antennas is presented. The design parameters of the fuzzy associative memories are optimally determined by using the classical, modified and improved tabu search algorithms. The theoretical bandwidth results obtained by using the fuzzy associative memories are in very good agreement with the experimental results available in the literature.

Computation of the resonant frequency of electrically thin and thick rectangular microstrip antennas with the use of fuzzy inference systems

Abstract: A new method for calculating the resonant frequency of electrically thin and thick rectangular microstrip antennas, based on the fuzzy inference systems, is presented. The optimum design parameters of the fuzzy inference systems are determined by using the classical, modified, and improved tabu search algorithms. The calculated resonant frequency results are in very good agreement with the experimental results reported elsewhere. Q 2000 John Wiley & Sons, Inc. Int J RF and Microwave CAE 10: 108]119, 2000.

A novel clonal selection algorithm based fragile watermarking method

Abstract: In this paper, a novel fragile watermarking method based on clonal selection algorithm (CSA), CLONALG, is presented. In Discrete Cosine Transform (DCT) based fragile watermarking techniques, there occurs some degree of rounding errors because of the conversion of real numbers into integers in the process of transformation of image from frequency domain to spatial domain. In this paper, the rounding errors caused by this transformation process are corrected by using CLONALG. Simulation results show that extracted watermark is obtained exactly the same as embedded watermark and optimum watermarked image transparency is achieved. In addition, the performance comparison of CLONALG and genetic algorithm (GA) based methods is realized.

A proposed secure multiple watermarking technique based on DWT, DCT and SVD for application in medicine

Abstract: In this paper, an algorithm for multiple watermarking based on discrete wavelet transforms (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) has been proposed for healthcare applications. For identity authentication purpose, the proposed method uses three watermarks in the form of medical Lump image watermark, the doctor signature/identification code and diagnostic information of the patient as the text watermarks. In order to improve the robustness performance of the image watermark, Back Propagation Neural Network (BPNN) is applied to the extracted image watermark to reduce the noise effects on the watermarked image. The security of the image watermark is also enhanced by using Arnold transform before embedding into the cover. Further, the symptom and signature text watermarks are also encoded by lossless arithmetic compression technique and Hamming error correction code respectively. The compressed and encoded text watermark is then embedded into the cover image. Experimental results are obtained by varying the gain factor, different sizes of text watermarks and the different cover image modalities. The results are provided to illustrate that the proposed method is able to withstand a different of signal processing attacks and has been found to be giving excellent performance for robustness, imperceptibility, capacity and security simultaneously. The robustness performance of the method is also compared with other reported techniques. Finally, the visual quality of the watermarked image is evaluated by the subjective method also. This shows that the visual quality of the watermarked images is acceptable for diagnosis at different gain factors. Therefore the proposed method may find potential application in prevention of patient identity theft in healthcare applications.

Block-based discrete wavelet transform-singular value decomposition image watermarking scheme using human visual system characteristics

Abstract: Digital watermarking has been suggested as a way to achieve digital protection. The aim of digital watermarking is to insert the secret data into the image without significantly affecting the visual quality. This study presents a robust block-based image watermarking scheme based on the singular value decomposition (SVD) and human visual system in the discrete wavelet transform (DWT) domain. The proposed method is considered to be a block-based scheme that utilises the entropy and edge entropy as HVS characteristics for the selection of significant blocks to embed the watermark, which is a binary watermark logo. The blocks of the lowest entropy values and edge entropy values are selected as the best regions to insert the watermark. After the first level of DWT decomposition, the SVD is performed on the low-low sub-band to modify several elements in its U matrix according to predefined conditions. The experimental results of the proposed scheme showed high imperceptibility and high robustness against all image processing attacks and several geometrical attacks using examples of standard and real images. Furthermore, the proposed scheme outperformed several previous schemes in terms of imperceptibility and robustness. The security issue is improved by encrypting a portion of the important information using Advanced Standard Encryption a key size of 192-bits (AES-192).