Sharif Digital Repository

The performance of degree of polarization (DOP) is investigated as a control signal in polarization-mode dispersion (PMD) compensation systems aided by polarization scrambling. The relation between the input and output polarization states of a signal propagating through a polarization scrambler and a PMD-induced optical fiber is described by a 3 × 3 Stokes transfer matrix. The average DOP of the output signal over a period of polarization scrambling is derived as an alternative to the conventional DOP-based control signal, i.e., minimum DOP. In the presence of first- and all-order PMDs, the performance of the average and minimum DOPs in monitoring of differential group delay (DGD) for... 

Numerous methods have been proposed previously to describe the characterization of porous materials; however, no well-developed theory is still available. Three different modeling methods were employed in this study to explore the relationship between the characterization parameters of activated carbon (AC) and its methane uptake. The first and the second methods were based on the Radial Basis Function (R.B.F) neural networks. At the first R.B.F. modeling, the neural networks algorithm was designed using the Gaussian function. The collected data for modeling were divided into two parts; (i) the data used for training the network and (ii) the data used for testing the predicted network. At... 

In this paper, the truly Meshless Local Petrov-Galerkin (MLPG) method is extended for computation of steady incompressible flows, governed by the Navier-Stokes equations (NSE), in vorticity-stream function formulation. The present method is a truly meshless method based on only a number of randomly located nodes. The formulation is based on two equations including stream function Poisson equation and vorticity advection-dispersion-reaction equation (ADRE). The meshless method is based on a local weighted residual method with the Heaviside step function and quartic spline as the test functions respectively over a local subdomain. Radial basis functions (RBF) interpolation is employed in shape... 

In this work, neural networks are used for estimation of flow stress of AA5083 with regard to dynamic strain ageing that occurs in certain deformation conditions and varies flow stress behavior of the metal being deformed. The input variables are selected to be strain rate, temperature and strain and the output value is the flow stress. In the first stage, the appearance and terminal of dynamic strain aging are determined with the aid of tensile testing at various temperatures and strain rates and subsequently for the serrated flow and the smooth yielding domains different neural networks are constructed based on the achieved results. While a feed-forward backpropagation algorithm is... 

Feed-forward is one of the best methods for linearizing microwave power amplifiers, but due to device tolerance in implementation of the system components, the practical Inter-Modulation Rejection (IMR) value may differ quite much from the theoretical IMR value. One of the methods to improve the practical performance of the system is using the multi-loop configuration. Here we have introduced the multi-loop feedforward systems and we have estimated the practical IMR values of the system using Monte-Carlo analysis. As the analysis shows, although the number of components in a multi-loop system is increased with respect to a simple feed-forward system, but the difference between the practical... 

The current statistical model and adaptive filtering (CSMAF) algorithm is one of the most effective methods for tracking the maneuvering targets. However, it is still worthy to investigate the characteristics of the CSMAF algorithm, which has a higher precision in tracking the maneuvering targets with larger accelerations while it has a lower precision in tracking the maneuvering targets with smaller acceleration. In this paper a novel adaptive tracking algorithm for maneuvering targets is proposed. To overcome the disadvantage of the CSMAF algorithm, a simple multi-layer feedforward neural network (NN) is used By introducing NN, two sources of information of the filter are fused while its... 

In this paper, a feedforward proportional-integral-derivative (PID) controller is developed to effectively control the clad height in laser solid freeform fabrication (LSFF). The scanning velocity is selected as the input control variable and the clad height is chosen as the output. A novel knowledge-based Hammerstein model, including a linear dynamic and a nonlinear memoryless block, is developed, and its parameters are identified offline using experimental data. The architecture of the controller consists of a PID and a feedforward module, which is the inverse of the identified model. The advantage of adding a feedforward path to the PID controller is evaluated experimentally, in which the... 

In this study, we have proposed a novel approach to investigate the features of four subbands of 2-D wavelet transform in magnetic resonance images (MRIs) for normal and abnormal brains which defected by Multiple Sclerosis (MS). Concurrently, another method extracts different kinds of features in spatial domain. Totally, 116 features have been extracted. Before applying the algorithm, we have to use a registration method because of variety in size of brain images. All extracted features have been passed over the Principal Component Analysis (PCA) and have been pushed to an Artificial Neural Network (ANN) that is a feed-forward type. According to changing in position of defected parts of... 

In the last decades, much attention has been paid to the design of multi-speaker voice conversion. In this work, a new method for voice conversion (VC) using nonlinear principal component analysis (NLPCA) is presented. The principal components are extracted and transformed by a feed-forward neural network which is trained by combination of Genetic Algorithm (GA) and Back-Propagation (BP). Common pre- and post-processing approaches are applied to increase the quality of the synthesized speech. The results indicate that the proposed method can be considered as a step towards multi-speaker Voice conversion. © 2007 IEEE  

In this paper, the application of neural networks for simulation and optimization of the cogeneration systems has been presented. CGAM problem, a benchmark in cogeneration systems, is chosen as a case study. Thermodynamic model includes precise modeling of the whole plant. For simulation of the steady sate behavior, the static neural network is applied. Then using dynamic neural network, plant is optimized thermodynamically. Multi layer feed forward neural networks is chosen as static net and recurrent neural networks as dynamic net. The steady state behavior of CGAM problem is simulated by MFNN. Subsequently, it is optimized by dynamic net. Results of static net have excellence agreement... 

According to the fact that humans and animals show marvelous abilities in walking on irregular terrain, there is a strong need for adaptive algorithms in walking of biped robots to behave like them. Since the stance leg can easily rise from the ground and it can easily rotate about the toe or the heel, the problem of controlling the biped robots is difficult. In this paper, according to the adaptive locomotion patterns of animals, coordination and control of body links have been done with Central Pattern Generator (CPG) in spinal cord and feedback network from musculoskeletal system. A one layer feedforward neural network that its inputs are the scaled joint variables and the touch sensors... 

The aim of this work is to introduce a new method based on time frequency distribution for classifying the EEG signals. Some parameters are extracted using time-frequency distribution as inputs to a feed-forward backpropagation neural networks (FBNN). The proposed method had better results with 98.25% accuracy compared to previously studied methods such as wavelet transform, entropy, logistic regression and Lyapunov exponent  

The adaptive capability of filters is known to be increased by incorporating a neural network into the filtering procedure. In this paper, an adaptive algorithm for tracking maneuvering targets based on neural networks is proposed. This algorithm is implemented with two filters based on the current statistical model and a multilayer feedforward neural network. The two filters track the same maneuvering target in parallel and the neural network automatically considers all the state information of the two filters and adaptively adjusts the process variance of one of them to achieve better performance in different target maneuver tracking. Simulations results show that the proposed adaptive... 

In this study, we have used a single link system with a pair of muscles that are excited with alpha and gamma signals to achieve both point to point and oscillatory movements with variable amplitude and frequency. The system is highly nonlinear in all its physical and physiological attributes. The major physiological characteristics of this system are simultaneous activation of a pair of nonlinear musclelike- actuators for control purposes, existence of nonlinear spindle-like sensors and Golgi tendon organlike sensor, actions of gravity and external loading. Transmission delays are included in the afferent and efferent neural paths to account for a more accurate representation of the reflex... 

The single-reference/multiple-output active noise control (ANC) of the accurate physical model of an acoustic duct system, developed earlier by the authors [1] is investigated. An adaptive feedforward algorithm is developed that minimizes a generic cost function consisting of the p-norm of the error vector. A computer model of a multi-channel ANC system, with the tonal and sweep sine input signals, is established, and the results for different single-input/single-output (SISO) configurations (error microphone and secondary source locations) of the ANC system are compared. The dynamic response of the single-reference/multiple-output ANC systems, using the Minimax and MEFXLMS algorithms, is... 

Based on the closed-form solution of a one-dimensional wave equation, the primary, secondary and acoustic feedback paths for the active control of sound in an acoustic duct have been investigated. Accurate models for the condenser microphone and loudspeaker, which include both the electro-mechanical and mechano-acoustical couplings as well as acoustical damping, have been considered. A generalized form of the filtered-x least mean square (FXLMS) algorithm that uses a more general recursive adaptive weight update equation to improve the performance of the FXLMS algorithm has been developed. Computer simulations were carried out to investigate the performance of acoustical feedback and...