نشریه مهندسی برق
سال پنجاه و یکم شماره 4 (پیاپی 98، زمستان 1400)

Temporal aberration is an important challenge in pulse-shaping process based on temporal imaging system. Temporal imaging is based upon the duality between spatial and temporal Fourier optics which, in turn, emanates from the similarity of the differential equations governing the diffraction of paraxial beams and dispersion of narrow-band pulses.  In this paper, the temporal implementation of spatial double-Gaussian lens  is proposed based on space-time duality and the concept of  time-lens. Inspired from other spatial optical systems which have been implemented in time, a temporal implementation of double-Gaussian lens with reduced aberation is proposed. The obtained image is improved in quality and aberration content  with 40 percent, compared to a conventional temporal imaging system.

This paper presents a time-domain comparator with low supply voltage and low power consumption for using in circuits that comparator’s input common-mode voltages swing is 0 to half supply voltage. To design the time-domain comparator, a delay element with a very high delay-voltage gain is proposed. The purpose of designing this comparator is to achieve high delay-voltage gain, which leads to an increase in the accuracy of the comparator, as well as a significant reduction in power consumption and occupied area compared to conventional time-domain comparators. This time-domain comparator utilizes subthreshold concept and also uses the bulk-voltage of transistor as a comparator input. The proposed comparator is simulated in 0.18µm TSMC technology at 1V supply voltage, which according to the intended application, the supply voltage can be reduced to about 0.4V. The simulation results show that with supply voltage of 1V the proposed comparator consumes 250nW at the clock frequency of 2.5MHz. The figure of merit of 0.1µW/MHz indicates the high performance of the proposed comparator. Based on the Monte Carlo simulation, the offset voltage of this comparator is obtained 2.8mV.

In this paper, a new approach for improving the linearity characteristics of GaN power amplifiers is presented. The method is based on the injection of the second harmonic signal to the input of the power amplifier through a forward path. The effect of the second harmonic injection on the linearity characteristics of the power amplifier is studied using two-tone theory and simulations. An active three-port linearizing circuit with the ability to generate a second harmonic signal with adjustable amplitude and phase has been proposed to implement this method. Further, the paper method has been evaluated for improving the linearity of two 10-watt power amplifiers with different nonlinear characteristics. As a concept, the proposed circuit is also fabricated and used for linearizing the GaN power amplifier. It has been shown that by injecting the second harmonic signal and properly adjusting its amplitude and phase, in addition to improving the linearity characteristics, including third-order intermodulation (IMD3), adjacent channel power ratio (ACPR), and AM-PM characteristic, the 1-dB compression point is also increased.

A flight control system (FCS) as an example of nonlinear systems should be stabilizing the airplane in healthy and faulty modes with the desired performance. In this paper, first, the nonlinear model of the flight system (FS) is linearized in predefined operating points, and the airplane’s healthy and faulty modes convert to a multi-model system. To eliminate the undesired effect of multi-modeling and the controller robustness that usually causes to mask the faults in FSs, the problem of integrated design of FCS based on active fault detection (AFD) is formulated. The proposed problem concluded to design the optimal auxiliary signal of AFD and a static, fixed, and full-order controller with the capability in reduced-order design. The FCS guarantees to stabilize all of the healthy and faulty models and to satisfy the performance constraints. In the following, to solve the formulated problem, a numerical solution based on the genetic algorithm is proposed. To evaluate the proposed method, two full-order and reduced-ordered controllers are designed for an aircraft in the case of actuator degradation conditions. The simulation results show the ability of the proposed method to meet the control objectives and design the auxiliary signal for AFD.

The SCADA system is a vital system that monitors and controls industrial processes. In these systems, a cyber attack occurs by infiltrating the communication channels between sensors, actuators and servers. In recent years, cyber-attacks have created problems for industrial control systems. A cyber attack has a function similar to a fault in terms of system malfunction. Having instantaneous network parameters such as latency, packet loss, and network traffic can probably make the difference between a fault and a cyber attack. The purpose of this initial research is to detect and then isolate the fault from the cyber attack of the SCADA system using different networks. To do this, a fluid passage system with a controller is modeled. A fault detection filter (BFDF) was designed, which detects various anomalies of the system, If at the time of detection of the anomaly by the filter, the network parameters also show abnormal conditions, a cyber attack is detected. The simulations were performed in Omnet ++ software. The research results showed the effectiveness of this method in distinguishing between fault and cyber attack.

Different types of contact, including contact between node pairs, any-contact of nodes, and contacts of the entire network, are used to characterize social relations in mobile social networks. Different modes of routing, from the point of view of message delivery semantics, encompass unicasting, multicasting, any-casting, and broadcasting. Studies have shown that using probability distribution functions of contact data, which is mainly assumed to be homogeneous for nodes, improves the performance of these networks. However, there exists an important challenge in studies on distributions. A lot of works apply the distribution of one type of contact to other types. Hence in routing applications, it causes to use of the distribution of one type of contact for any mode of routing. This study provides a complete solution to model each type of homogeneous contact data distribution and to use them in different modes of routing. We propose a routing algorithm that uses this new model. Results show that our solution improves the average latency of comparing methods Epidemic, TCCB, and DR about 3.5-times, 30%, and 45%, respectively. It achieves a delivery rate of about 5% and 6%, and average latency about 6% and 8% better than that of DR and TCCB, respectively.

Multi-label classification aims at assigning more than one label to each instance. Many real-world multi-label classification tasks are high dimensional, leading to reduced performance of traditional classifiers. Feature selection is a common approach to tackle this issue by choosing prominent features. Multi-label feature selection is an NP-hard approach, and so far, some swarm intelligence-based strategies and have been proposed to find a near optimal solution within a reasonable time. In this paper, a hybrid intelligence algorithm based on the binary algorithm of particle swarm optimization and a novel local search strategy has been proposed to select a set of prominent features. To this aim, features are divided into two categories based on the extension rate and the relationship between the output and the local search strategy to increase the convergence speed. The first group features have more similarity to class and less similarity to other features, and the second is redundant and less relevant features. Accordingly, a local operator is added to the particle swarm optimization algorithm to reduce redundant features and keep relevant ones among each solution. The aim of this operator leads to enhance the convergence speed of the proposed algorithm compared to other algorithms presented in this field. Evaluation of the proposed solution and the proposed statistical test shows that the proposed approach improves different classification criteria of multi-label classification and outperforms other methods in most cases. Also in cases where achieving higher accuracy is more important than time, it is more appropriate to use this method.