Sharif Digital Repository

A major problem in a multiple output converter structure is the different power flow via its various outputs. This problem leads to unwanted input DC-link voltage. This paper studies full bridge based DC-DC converters with multiple outputs. The effect of power flow variation is studied and a regenerative converter topology which controls the DC-link voltage by space voltage vector modulation technique is proposed. The proposed converter has a fast response to control the DC-link voltage in an acceptable band. Simulation and experimental results are presented to verify the analytical studies. © 2018 IEEE  

Nanosecond pulsed-power generators have many applications in industries. As the rise time and fall time of conventional semiconductor switches are usually more than a few nanoseconds, it is necessary to employ special switches or new pulse generating methods to achieve nanosecond pulses. A common method for producing narrow pulse voltage waveforms is using the reverse recovery process of diodes. In this method, a super fast recovery diode is used as an opening switch in an inductor current path. A drift step recovery diode can form a rapid cut-off current front; Hence this method can be an effective solution to generate narrow pulses. This paper describes an investigation about the effect of... 

The lack of turn-off ability makes the spark gap-based Marx generator uncontrollable in terminating the output pulse. In addition, there are some limitations for rise time and voltage gain improvements in the conventional critically-damped Marx design. In this paper, an efficient over-damped design of Marx circuit is proposed, which leads to a shorter rise time as well as a larger voltage gain. A chopping magnetic switch is employed to achieve the desired values of the fall time and full width at half maximum (FWHM). Moreover, adding a DC bias circuit to the magnetic switch provides the ability to adjust the pulse FWHM parameter. Therefore, an output pulse with a shorter rise time, larger... 

Waveform design for target identification and classification in multiple-input multiple-output (MIMO) radar systems has been studied in several recent works. In previous works, optimal signals for an estimation algorithm are found assuming that only signal- independent noise exists. This work extends previous research by studying the case where clutter is also present. We develop a procedure to design the optimal waveform which minimizes estimation error at the output of the minimum mean squared error (MMSE) estimators in two scenarios. In the first one different transmit antennas see uncorrelated aspects of the target, and we consider the correlated target aspects in the second one.... 

Waveform design for Target identification and classification in MIMO radar systems has been studied in several recent works. While the previous works considered signal independent noise and found optimal signals for an e stimation algorithm, here we extend the results to the case where clutter is also present and then we will find the optimum waveform for several estimators differing in the assumptions on the given statistics. Several different approaches to the optimal waveform design are proposed, including minimizing the error of MMSE estimator, minimizing the maximum error of the covariance shaping least square (CSLS) estimator and minimizing the MSE error of scaled least square (SLS)... 

Waveform design for Target identification and classification in MIMO radar systems has been studied in several recent works. While the previous works considered signal independent noise and found optimal signals, here we extend the results to the case where clutter is also present and then we will find the optimum waveform for MMSE estimator. Choosing optimal waveform for MMSE estimator leads to the Semidefinite programming (SDP) problem, a convex optimization problem which can be efficiently solved through numerical methods. Explicit solution is developed for this SDP problem in two cases .In the first case, target and clutter covariance matrices are jointly diagonalizable and in the second... 

Dimension reduction techniques for text documents can be used for in the preprocessing phrase of blog mining, but these techniques can be more effective if they deal with the nature of the blogs properly. In this paper we propose a novel algorithm called PostRank using shallow approach to identify theme of the blog or blog representative words in order to reduce the dimensions of blogs. PostRank uses a graph-based syntactic representation of the weblog by taking into account some structural features of weblog. At the first step it models the blog as a complete graph and assumes the theme of the blog as a query applied to a search engine like Google and each post as a search result. It tries... 

Waveform design for target identification and classification in MIMO radar systems has been studied in several recent works. While the previous works assumed that the noise was independent of the transmission signals, here we extend the results to the signal dependent noise (clutter). We consider two scenarios. In the first scenario it is assumed that different transmit antennas see uncorrelated aspects of the target. In the second scenario, we consider the correlated target. As clutter is dependent to signal, target estimation error cannot vanish only by increasing the transmission power. It can be shown that in the second scenario, MIMO radar receiver can nullify the clutter subspace.... 

This paper studies simultaneous lot sizing and scheduling problem in a job shop environment over a finite number of periods. The machines are flexible such that the production manager is able to change their working speeds. Also, the production schedule of the items over machines should be in consistence with technological precedence relationships. The problem is formulated as an integer linear program. Then, a number of valid inequalities are developed based on the problem structures. The proposed valid inequalities are added to the problem formulation in a "cut and branch" manner to accelerate the search process by common solvers. Finally, performance of the valid inequalities is... 

A thermo-elastic analysis coupled with a phase change model is employed to evaluate thermal stresses as well as progress of austenite decomposition after hot strip rolling operations. The thermo-mechanical finite element analysis is utilized to assess the distributions of temperature and thermal stresses during cooling while at the same time, a model based on the additivity rule is used to determine the rate of austenite to ferrite decomposition. The proposed model is applicable to multi-pass rolling schedules while the effects of different process parameters including the rolling speed and cooling configuration of the run-out table can be taken into account. In order to verify the... 

After several decades of work by several talented researchers, estimation of the origin–destination matrix using traffic data has remained very challenging. This paper presents a set of innovative methods for estimation of the origin–destination matrix of large-scale networks, using vehicle counts on links, partial path data obtained from an automated vehicle identification system, and combinations of both data. These innovative methods are used to solve three origin–destination matrix estimation models. The first model is an extension of Spiess’s model which uses vehicle count data while the second model is an extension of Jamali’s model and it uses partial path data. The third model is a... 

Fractional-pixel accuracy Motion Estimation (ME) has been shown to result in higher quality reconstructed image sequences in hybrid video coding systems. However, the higher quality is achieved by notably increased Motion Field (MF) bitrate and more complex computations. In this paper, new half-pixel block matching ME algorithms are proposed to improve the rate-distortion characteristics of low bitrate video communications. The proposed methods tend to decrease the required video bandwidth, while improving the motion compensation quality. The key idea is to put a deeper focus on the search origin of the ME process, based on center-bias characteristics of low bitrate video MFs. To employ the... 

Motion estimation at fractional-pixel accuracy results in higher quality video sequences. However, the higher quality is achieved by more computations and increased required motion field bitrates. In this paper, new half-pixel accuracy block matching-based motion estimation algorithms are proposed to improve the rate-distortion characteristics of low-bitrate video communications. The proposed methods especially tend to decrease the required video bandwidth, with no degradation in quality of reconstructed image sequences. The key idea is to put a deeper focus on the origin (zero motion) based on the center-bias characteristics of low bitrate video motion fields. The experimental results show... 

Motion estimation and compensation is an essential part of existing video coding systems. Compared to the widely used block-matching algorithms (BMA), the mesh-based motion estimation (MME) produces better subjective and objective qualified image sequences in many cases, especially at low bitrates. However, the iterative refinement step of the MME is computationally too expensive. In this paper, we propose a fast MME scheme, which adjusts its interpolation patterns to the motion features of image sequences to achieve higher quality reconstructed results. Experimental results show notable rate-distortion improvement over both the BMA and the conventional non-iterative MME schemes, especially... 

In this paper, a fuzzy random minimum cost flow problem is presented. In this problem, cost parameters and decision variables are fuzzy random variables and fuzzy numbers respectively. The object of the problem is to find optimal flows of a capacitated network. Then, two algorithms are developed to solve the problem based on Er-expected value of fuzzy random variables and chance-constrained programming. Furthermore, the results of two algorithms will be compared. An illustrative example is also provided to clarify the concept  

In this paper, we will discuss two special classes of mathematical programming models with fuzzy random variables. In the first model, a linear programming problem with fuzzy decision variables and fuzzy random coefficients is introduced. Then an algorithm is developed to solve the model based on fuzzy optimization method and fuzzy ranking method. In the second model, a fuzzy random quadratic spanning tree problem is presented. Then the proposed problem is formulated and solved by using the scalar expected value of fuzzy random variables. Furthermore, illustrative numerical examples are also given to clarify the methods discussed in this paper