ELECTRONIC INDUSTRIES
Year:2016 | Volume:7 | Issue:3|Papers Count:10

Polarimetric synthetic aperture radar (PolSAR) images contain so much information about the characteristics of the targets of the desired area with high resolution. Nowadays, using this data for terrain classification is known as a hot topic of interest for researchers. Recently, sparse representation-based technique as a powerful tool in the field of signal processing, has attracted a lot of attention. Therefore, in the first step, the structure of a sparse representation-based classifier is proposed. On the other hand, according to recent research results, ensemble classifier as an effective approach has more capabilities compare to single-classifiers. Therefore, in the next step, an ensemble classifier with Naïve Bayes combination rule is presented by using the sparse representation-based classifier and other diverse single-classifiers. Finally, an optimum ensemble classifier is proposed by using multiple objective particle swarm optimization (MOPSO) and considering accuracy and reliability as objective functions. The experimental results over a benchmark PolSAR image demonstrate the effectiveness of the proposed algorithms compared to the existing techniques.

CAESAR competition is a competition for the design of cryptographic authenticated encryption schemes with associated data (AEAD). NORX is one of the CEASAR candidates which has been selected for the second round of this completion also. In this paper, the first linear cryptanalysis of this scheme is presented using mixed integer linear programming (MILP). The analysis conducted in this paper has been done for the reduced round NORX8, NORX16, NORX32 and NORX64. Our best linear characteristics for these variants reduced to one round out of four rounds have biases 2-52, 2-47, 2-21 and 2-76 respectively. Due to the optimized answer for NORX8, this version of reduced NORX provides optimal security against linear attack.

In the past decades related-key attacks have been studied in theory and practice and invulnerability against related-key attacks as one of the security goals has been considered in the design of block ciphers. Cipher assessment against all kinds of attacks leads to identify their vulnerabilities and improving the cryptographic schemes. Related-key impossible boomerang attack is made of the combination of boomrang attack and related-key impossible differential attacks. The flexibility to choose key differences provides the possibility of attack on more rounds of block ciphers using this attack. Recently, SIMON family of Lightweight cipher has been designed securely and flexibly by NSA in ten versions for the proper functioning in limited hardware environments. SIMON key scheduler is proposed invulnerable to related-key attacks. In this paper related-key impossible boomerang attack on 20 rounds Simon32/64 lightweight cipher is presented.

In this paper, a new simple refractive index (RI) sensor based on plasmonic nanostructure D-shape fiber is proposed. In this structure, surface plasmon resonances are sensitive to the surrounding medium on the flat side of the D-shape fiber. In the proposed sensor, the sensitivity of 1025nm/RIU is obtained. The significance of the proposed sensor lies with its compact in size, robust and simple in structure, and high value of sensitivity. In addition, an important property of the designed structure is that the excitation of surface plasmon resonances in this type of fiber is simple. The proposed structure can be applicable to the identification of different bio-molecules or chemical materials.

Micro strip circular and square structural ring patch antenna because of most plasticity for receiving an transmitting the signals and also application to driver the active devices are used. An accurate modified wolfe model (MWM) is applied to compute the effective dynamic dielectric constant for determination of resonant frequency micro strip patch antenna circular and square ring without cover. The results obtained from (MWM) have been compared against the result of experimental and other theoretical methods which have very good agreement. Then accuracy of calculated resonant frequency by the (MWM) for dominant mode is about 0.5%. Moreover we calculate the supper strate effect on the resonant frequency dominant and higher order modes of circular and square ring, but the other methods dose not applicable for calculation of the supperstrate effects on the resonant frequency.

Loran-C is a positioning system based on TDOA. The third standard zero crossing point is used to detect Loran-C pulses in receiver. In practice, due to noise and interference, the location calculation of this point is in error. One of the most important and effective parameter to identify the third standard zero crossing point in Loran-C pulse is ECD estimated value. One of the methods for estimating the ECD is USCG transmitted pulse method which is based on the least squares error between the received and ideal signal. The disadvantage of this algorithm is that the estimation of ECD must be obtained through a numerical procedure which is not time-efficient. In this paper, two techniques have been proposed to optimize the USCG transmitted pulse method. In the first method, ECD measurement is obtained experimentally. The second method is the gradient steepest descent method which calculates step size intelligently. The results show that although the empirical method has enough accuracy, but it needs much time to do calculations, while the gradient steepest descent method, in additional small computation complexity, has high accuracy in ECD estimation.

Synthetic aperture radar (SAR) imaging widely used for remote sensing and military applications; because this kind of imaging is independent from the weather and has high resolution in day and night. In this paper, a new method based on fuzzy logic is proposed for the edge extraction of SAR images. Edge detection is one of the most important techniques used for data analysis and decision-making on the image for various applications. Edge detection is a scope of research in image processing and feature extraction. A serious problem concerning SAR images is that they are intrinsically disturbed by speckle noise. The existence of speckle noise, intensely impedes the interpretation and analysis of SAR images. So, traditional techniques can not provide good edge detection results for SAR images. The method, proposed in this manuscript, by optimization of the fuzzy inference system (FIS) i.e using proper kernels and membership functions, the edge extraction of SAR image is done. The inputs for FIS are image gradients (in both horizontal and vertical directions) and a heuristic self-tuning edge detector parameter which is shown by. This self-tuning parameter is variable for different images and by controlling the shape of Gaussian membership function leads to automatization of proposed algorithm. Finally, the proposed algorithm is compared with other edge detectors to demonstrate the superiority of the proposed method. In this work, in addition to structural similarity criterion, the Mean squared error (MSE) and Peak signal-to-noise ratio (PSNR) are used to numerical Analysis.

To have both high efficiency and linearity in power amplifiers linearization techniques should be used. One structure with the ability of cancelling the inherent limitations of the LINC linearization techniques is proposed in this article. The gain and phase imbalances in LINC technique has been compensated using optimization algorithms. According to the analysis a feedback path has been added in the conventional LINC transmitter that calibrates any phase and gain mismatches adaptively; using optimization algorithms. Many simulations have been performed to validate the structure functionality and extracted relations. In this paper M68749 power amplifier is used at 390MHz frequency with output power of 5 watt. Simulations show that power spectral density of proposed architecture has 40dB/Hz improvement in spreading to adjacent channels.

In this paper, a new composite artificial magnetic conductor (AMC) surface with magneto-dielectric substrate is presented for wide band radar cross section (RCS) reduction. It is shown that magneto-dielectric substrate can increase the in-phase reflection bandwidth of AMC structure. In this structure, the composite surface consists of two AMC types that operate at two different resonance frequencies. The phase difference between these two AMC types is tuned to be close to ±180 over a wide bandwidth so that the reflections from them cancel each other. The results show with this technique, RCS reduction more than 13 dB was achieved with a 93% bandwidth.