One of the requirements of Radar Antenna detectors is fast rotation of monopulse insurances, which different methods have been proposed in this field. One of the methods used in various weapon systems is the use of Space Feeding Antennas. In this type of array antennas, a ferrite phase Shifter is used, whose phase is controlled by a controller in the direction of rotation of the beam. The phase changers used in these antennas have advanced technology that is less discussed in the country. In this paper, the design and fabrication of a Dual Mode ferrite phase Shifter and a waveguide response for use in tracking radars in the Ku band at a center frequency of 16.35 GHz have been simulated using the Software CST STUDIO2018. In designing, the effect of various parameters such as ferrite length and ferrite bias rate on phase change has been investigated. By examining various parameters, the optimal mode for the phase shifter has been selected, and its results have been investigated in terms of passing loss and return loss and 360-degree phase change in the required range of tracking radars.

Watermarking is a novel approach to prevent unauthorized use of a digital media. By embedding the copyright information in the media, this solution will help protect its property rights. In this paper, a secure and robust method in color space of YCoCg-R is presented to prove the ownership of the media (copyright). The three-dimensional components of this color space are not well correlated, which can be effective in increasing the robustness. The proposed method uses a discrete cosine transform(DCT) and the relationship between its coefficients for embedding.When inserting bits of the cue, the complexity of the initial image blocks is used to select the target blocks and its average coefficients to select the adaptive insertion power, which also creates high resistance(robust), especially against JPEG compression. It also provides an optimal recursive linear transformation with a high branching for parsing and signal coding, and the component Y of color space, and a native linear feedback shift register (LFSR) for producing a suitable key sequence for Increasing the security of the proposed method, taking into account the contrast between the main labeling requirements, including the transparency, resilience, security and capacity of the proposed method, provide better results than other methods. To test the proposed design, standard RGB images (USP-SIPI images) with 512x512 pixels are used as cover images (hosts) using MATLAB2016 software and on a PC with Pentium-IV 3.2 GH processor and RAM 8G memory is implemented. The results show that the proposed algorithm has excellent transparency and resistance.

Supporting the highest bandwidth data rates among new generation of communication devices requires advanced clock management technology such as DL (Delay Line). By introducing object internet increase of the system clock frequency poses some challenges in generating and distributing of the clock with low uncertainty and power, as clocks determine the overall performance of the chip. The generated signal quality determines by several factors as frequency, phase, period, jitter and clock variations. Both analog and digital circuits have some limitations which make it impossible to achieve high quality clock. One of the proposed solutions for performance improvement of DLs is the utilization of both analog and digital circuits in one system. In this thesis a low jitter and wide operation range Mixed-Mode Delay Line presented. Body feed technique and proper bias circuit are used in the proposed multiphase Mixed Controlled Delay-Line (MMCDL) to widen applicable range of control voltage, allow rail-to-rail operation and overcome the nonlinearity of the conventional current starved delay element. Furthermore, two single ended current starved inverters are utilized in a differential structure to minimize the effect of the power supply and the substrate noise. In this way jitter and static phase error specifications are improved. The designed circuit is simulated in ADS software, using TSMC 0.18 um CMOS process at 1.8V supply voltage. Simulation outcomes indicate that the frequency range of the suggested DL is 80-920 MHz. The rms jitter and power dissipation of the designed circuit at 920 MHz are 3.7psec and 3.9 mW respectively.

The reflected sounds from the ultrasonic systems, which are being used to detect defects, are often affected due to the presence of noise. Reflections resulted from heterogeneous structures are commonly known as reverse distribution distortions. There are several methods to eliminate this noise. Wavelet conversion is one of the powerful and effective tools for noise cancellation. Mother''s wavelet compatibility with real signals on the one hand and less complexity of computations on the other hand make the wavelet conversion as an effective tool to be used. In this study, we used the wavelet transform method in order to eliminate the possible noise in ultrasound transducers. We applied a wavelet transform to eliminate noise in a defect identification system and, therefore, adapted the optimal algorithm for this purpose. Based on the simulation results and the utilized criteria of merit, the best results are obtained when the Meyer discrete mother wave, hard threshold and threshold level based on standard deviation are used. Our findings showed that the SNRE method, presented in this paper, improves the results considerably from 1 to 25 dB compared to conventional ultrasound noise reduction techniques depending on the percentage of recoil signal error amplitudes.

Today, brain signals can be confidently used as a strong biometric identifier to identify individuals due to the difficulty of forgery and theft. This study examines, compares and analyzes the results of the latest methods in the field of identification using brain waves. This article also answers the question of whether the development of new hybrid methods using components of existing methods can lead to better results for identifying individuals. In summary, the use of the same database, as well as the study of different states of mental activity when recording signals, as well as the creation of different combinations of units of existing methods, creates a comprehensive and principled comparison between existing algorithms and identifies strengths and They have become weak. The results show that none of the combined methods led to acceptable results and had a large classification error. It was also found that using the raw signal at CNN neural network input would have better results than feature input. On the other hand, changing the input mode when recording a signal from the user affects the performance of the SVM classifier and CNN neural network, while changing the input mode will not have a significant effect on the RF classifier.

Nowadays, photovoltaic systems have received a lot of attention due to their widespread application. One of the important applications of these systems is to provide energy for vital public service centers, security centers and law enforcement centers in critical situations. They are also used in centers located in mountains and hard-to-reach areas, road control centers and wireless relay stations. In this paper, a tracking photovoltaic system has been used instead of a fixed one to improve efficiency, naturally expected to increase system cost because of adding tracking equipment. In order to decrease the cost, smart tracking algorithm has been used which generates the sun path according to the location of the solar panel and local astronomical calendar, without using any sensor. First, the motor and the control unit of tracking system were analyzed in detail and were simulated using MATLAB. Then, the solar power curve, the received power curve, the generated power curve and the efficiency of both fixed and tracking systems were calculated. The results show that the tracking system is able to receive almost all the power from the sun’s rays which leads to efficiency of 20.02%, meanwhile the fixed system efficiency is 14.16%. Moreover, the economic analysis confirms that the cost-efficiency ratio of fixed and tracking systems are 1959 and 1785 dollar per unit efficiency, respectively, that represents a reduction in the cost of energy production in a smart tracking-based photovoltaic system.