MODARES TECHNICAL AND ENGINEERING
Year:2004 | Volume:- | Issue:16|Papers Count:12

In this paper, a generalized method for accurate full-wave analysis of shielded MIC's and the three-layer microstrip structure enclosed in a rectangular cavity based on Mixed Potential Integral Equation (MPIE) derived in real space have been developed. Method of moments (MoM) with Galerkin technique has been used for the solution of the integral equation to obtain the surface electric currents distribution on the conductors. An accurate de-embedding procedure for the characterizing electric currents distribution and extracting S parameters based on pencil of matrix technique are employed. A new numerical technique for fast convergence of the double infinite series expansion of the MoM solution has been considered. A computer program implementing the analysis has been written in Fortran on a personal computer. Several types of microstrip discontinuities such as Open-end, bend, collinear Broadside Coupled Line (BCL) and crossover is analyzed and numerical results are presented and compared with both previously published data and the results found by HP-HFSS software.

In this paper, we try to use modeling based on singular perturbation theory, in order to control satellite attitude during the wide rolling angle maneuvering through nonlinear H∞ control strategy. Differential equations describing dynamics of the satellite are presented first, and by choosing the appropriate dynamic model for actuators and based on the standard singular perturbation model, the closed-loop system is created. Next, this model is put into the appropriate form to solve H∞ problem. Then, after solving the HJI equation, the control law is determined. Simulation results for a nominal satellite control based on our approach are finally presented.

In most industrial applications, including overhead cranes, two motors with equal speeds are required. To meet this, different traditional and modern methods are used. In the modern methods, work is done with more precision but the cost is remarkably high, also the maintenance of equipment needs specialized personnel. Among traditional methods, the two-motors selsyn method is noteworthy due to its considerable low cost. But this method has some problems in starting with high rotor resistance, working at nominal speed, and braking. In this paper after analyzing of selsyn methods, the stability conditions and some problems that occur in two-motor selsyn have been studied. In continuation, some solutions have been suggested and the effectiveness of the system has been validated through practical tests and simulation results.

In this paper two nodes to model isotropic and anisotropic media in Transmission Line Matrix Method (TLM) are presented. By using these two nodes, the permeability and permittivity of an anisotropic media can be modeled simultaneously. Another application of these nodes is in modeling media with permittivity and permeability less than one. In the conventional 2 dimensional TLM, the stubs representing permittivity and or permeability get negative characteristic impedances, which in turn cause instability in the computation. Studying the two suggested nodes, called the stub node and the hybrid node, respectively, shows the hybrid node can best model the simultaneous variations of permeability, permittivity of the isotropic and non isotropic media.

A parallel hybrid system of HMM and GMM modeling techniques was implemented and used in a telephony speaker verification and identification system. Spectral subtraction and Weighted Projection Measure were used to render this system more robust against additional noise. Cepstral Mean Subtraction method was also applied for the compensation of convolution noise due to transmission channel degradation and differences in the frequency response of telephone handsets. For a population of 100 speakers of FARSDIGITS1 database with a SNR of 8.8 dB, a speaker identification performance of 95.51% and a speaker verification error rate of 0.37% were obtained. Several score normalization methods in utterance and frame level and weighting of model scores were also implemented, and then compared and evaluated. It was shown that these methods improve discrimination between speakers and yield a reduction of speaker verification and identification error rates.

The geometric distribution of states duration is one of the main performance limiting assumptions of hidden Markov modeling of speech signals. Stochastic segment models, generally, and segmental HMM, specifically, overcome this deficiency partly at the cost of more complexity in both training and recognition phases. In this paper, a new duration modeling approach is presented. The main idea of the model is to consider the effect of adjacent segments on the probability density function estimation and evaluation of each acoustic segment. This idea not only makes the model robust against segmentation errors, but also it models gradual change from one segment to the next one with a minimum set of parameters. The proposed idea is analytically formulated and tested on a TIMIT based context independent phoneme classification system. During the test procedure, the phoneme classification of different phoneme classes was performed by applying various proposed recognition algorithms. The system was optimized and the results have been compared with a continuous density hidden Markov model (CDHMM) with similar computational complexity. The results show slight improvement in phoneme recognition rate in comparison with standard continuous density hidden Markov model. This indicates improved compatibility of the proposed model with the speech nature.

The error of inertial navigation systems increase versus time, therefore for achieving higher accuracy specially in long time navigations we have to use an aiding system. Global positioning system is the best aiding system in this case. In this paper we first simulate a GPS and INS; Then simulate tightly integration and finally review adaptation method of Kalman Filtering a Fuzzy adaptive Kalman filter is proposed in which adaptation is accomplished by adaptive tuning of covariance matrix of measurement noise (R) and process noise (Q). We have achieved adaptive tuning using Fuzzy systems and Covariance - Matching techniques .The results show that the adaptive fuzzy integration of GPS and INS would lead to better performance comparing to the usual methods of integration in which both R and Q matrices are constant.

In this paper an application of Cellular Learning Automata (CLA) to VLSI placement is presented. The CLA, which is introduced for the first time in this paper, is different from standard Cellular Learning Automata in two respects. It has input and the cell neighborhood varies during the operation of CLA. The proposed CLA based algorithm for VLSI placement is tested on number of placement problems and has been compared with several reported algorithms such as: simulated annealing, genetic algorithms, the algorithm proposed by Saheb Zamani and Hellestrand, and the algorithm based on Kohenen neural network. The results obtained show that the proposed algorithm produces results, which are comparable to the other algorithms reported in the literatures. The parallel nature of CLA makes it appropriate for hardware implementation.

The current Internet inherently has a degree of survivability due to the connection less IP Protocol. Dynamic routing Protocols are designed to react to faults by changing routes when routers learn about topology changes via routing information updates (e.g., link status advertisements). Loss of Quality of service (QoS) has not been an issue because current Internet traffic is the best-effort. On the contrary, the multi protocol label switching (MPLS) approach is connection-oriented, which implies greater potential vulnerability to faults. At the same time, MPLS will support integrated services, which are more sensitive to loss of service. Reliability is becoming more important as more users depend on the internet for critical communication services and expect a higher level of performance. Usually, fault recovery is attempted first at the lowest layer, and escalated to the next layer if recovery was unsuccessful or impossible. Fault recovery capabilities in the MPLS layer are needed as well to decouple MPLS from dependence on physical layer fault recovery mechanisms which may differ between networks. This paper proposes an enhanced-scheme for fast rerouting to pre-assigned label-switched paths (LSPs) in case of LSP or link failures. In order to minimize backup resources, it allows possibility of splitting traffic of faulty LSP onto available alternative LSPs for fault recovery. We use Pre-assigned backup LSPs for restoration, when fault occurs. Total traffic throughput and resource utilization can be maximized if the traffic of faulty LSP is split over multiple pre-assigned LSPs. In this paper a new approach to providing fault tolerance in MPLS networks using case-based reasoning (CBR) as a method to find out the amount of traffic forwarded on each pre-assigned LSP based on past experiences of loading process is presented. The pre-assigned LSPs and the percentage of traffic splitting are calculated off-line based on desired QoS and capacity constraints. Also we evaluate the operation of successful decomposition of traffic based on the two mentioned constraints by using CBR, when the number of backup LSPs as a complexity factor increase. In another point of view, in cases when there is no possibility of using the experiences successfully, there would be no other way than using the erroneous unsuccessful experiences. We thus solved our recovery problem by using, first incorrect databases in our experiments, to moving later towards decreasing the error rate in a gradual manner.