Sharif Digital Repository

In this study, N-way partial least squares (NPLS) is proposed to correlate comprehensive two-dimensional gas chromatography-time of flight mass spectrometry (GC × GC-TOFMS) data of different aromatic oil fractions (fresh and weathered) to their toxicity values. Before NPLS modeling, since drift and wander of baseline interfere with information of sought analytes in GC × GC-TOFMS data, a novel method called two-dimensional asymmetric least squares is thus developed for comprehensive correction of the baseline contributions in both chromatographic dimensions. The algorithm is termed comprehensive because it functions to correct the entire chromatogram in both dimensions and it preserves the... 

In an electronic warfare environment, an electronic support system receives signals emitted by different radars. One of the key tasks in an electronic support system is PRI estimation tracking Pulse Trains using Pulse Repetition Interval (PRI) of these signals. In this paper we present a simple method for PRI estimation and tracking radar pulse trains with complex PRI Modulations. This method uses nonlinear least square, Pisarenko and innovative methods for PRI estimation and tracking pulse train. Simulation results show high robustness of the proposed method against noise (spurious and missing pulses)  

A method for two dimensional position finding of stationary targets whose bearing measurements suffers from indeterminable bias and random noise has been proposed. The algorithm uses convex optimization to minimize an error function which has been calculated based on circular as well as linear loci of error. Taking into account a number of observations, certain modifications have been applied to the initial crude method so as to arrive at a faster, more accurate method. Simulation results of the method illustrate up to 30% increase in accuracy compared with the well-known least square filter  

Estimation of physical parameters of a parametrically excited gyroscope is studied in this paper. This estimation is possible by reading the input and output data of the gyroscope. Because of different faults in the manufacturing process and tolerances, physical parameters of a gyroscope are not exactly same as the expected values of the manufacturer. Moreover, changing of temperature, humidity, external acceleration, etc. can change the physical parameters of the gyro. Thus, the physical parameters of gyroscope are not fixed values and may deviate from the desired designed values. The physical parameters of gyroscope determine the optimal region for working of gyroscope. Thus, if the... 

pH control is a challenging problem due to its highly nonlinear nature. In this paper the performances of two different adaptive global linearizing controllers (GLC) are compared. Least squares technique has been used for identifying the titration curve. The first controller is a standard GLC based on material balances of each species. For implementation of this controller a nonlinear state estimator is used. Some modifications are proposed to avoid the singularity of the observer gain. The second controller is designed based on the reduced state equation. Through computer simulations, it has been shown that the performances of the second GLC is superior and it is more robust to process... 

Node localization is of paramount importance to different wireless sensor network (WSN) applications. This paper investigates the received signal strength (RSS) based localization problem with unknown path-loss model parameters. Most works in RSS localization assume the transmit power and path-loss exponent (PLE) are known that is not a realistic assumption in some cases. However this paper, assumes the transmit power and the PLE are both unknown and a novel algorithm for sensor location is proposed. The algorithm is based on the generalized total least-squares (GTLS) method and gives an explicit solution for the localization problem. The performance of the proposed method is compared with... 

In this paper we consider the problem of improving unknown node localization by using differential received signal strength (DRSS). Many existing localization approaches, especially those using the least squares methods, either ignore nonlinear constraint among model parameters or utilize them inefficiently. In this paper, we develop four DRSS-based localization methods by utilizing different combinations of covariance and weight matrices. Each method constructs a two-stage procedure. During the first stage, an initial coarse position estimate is obtained. The second stage results the refined localization by accounting for nonlinear dependency among estimator variables. The proper choice... 

The potentials of partial least squares regression (PLSR) and multivariate curve resolution alternating least squares (MCR-ALS) are evaluated for the simultaneous determination of diclofenac (DCF), naproxen (NAP), mefenamic acid (MEF) and carbamazepine (CBZ) as target analytes and gemfibrozil (GEM) as an interference in synthetic and real environmental samples. The analysis of first-order UV-Vis spectra is performed using PLSR with different variable selection methods, which include variable importance in projection (VIP), recursive weighted partial least squares (rPLS), regression coefficient (RV) and uninformative variable elimination (UVE), and using MCR-ALS with correlation constraint... 

In this study, N-way partial least squares (NPLS) is proposed to correlate comprehensive two-dimensional gas chromatography-time of flight mass spectrometry (GC×GCTOFMS) data of different aromatic oil fractions (fresh and weathered) to their toxicity values. Before NPLS modeling, since drift and wander of baseline interfere with information of sought analytes in GC×GC-TOFMS data, a novel method called two-dimensional asymmetric least squares is thus developed for comprehensive correction of the baseline contributions in both chromatographic dimensions. The algorithmis termed comprehensive because it functions to correct the entire chromatogram in both dimensions and it preserves the... 

An extension to conventional Hidden Markov Model (HMM)-based speech enhancement method is developed. An algebraic method is proposed to estimate gain of speech and noise in order to improve the quality of the estimated speech. Different pronunciations and intonations may affect speech gain. Besides, gain of noise may vary remarkably from one environment to the other one. This may lead in a mismatch between energy contour of trained models and energy contour of noisy speech signal. In this work, speech gain and noise gain are estimated based on an algebraic method simultaneously in order to match gain of noisy speech and noisy model. To carry out this procedure an extension of least square... 

The performance of several regression methods is investigated to estimate the distribution of engineering demand parameters conditioned on intensity measures (EDP|IM) for small record sets. In particular, the performance of the multivariate ordinary least squares (OLS), a simultaneous mean-variance regression (MVR) done by a penalized weighted least-square loss function, and a mean-covariance/variance regression based on expectation maximization method (EM) are assessed. The efficiency of the introduced methods is compared with FEMA-P58 methodology. Performance assessment of EM and MVR methods shows that the overall increase in efficiency is about 25–45% for maximum inter-story drift ratios,... 

In this work, the potential of near-infrared (NIR) and mid-infrared (MIR) spectroscopy along with chemometrics was investigated for authentication and adulteration detection of Iranian saffron samples. First, authentication of one-hundred saffron samples was examined by principal component analysis (PCA). The results showed the NIR spectroscopy can better predict the origin of samples than the MIR. Next, partial least squares-discriminant analysis (PLS-DA) was developed to detect four common plant-derived adulterants (i.e., saffron style, calendula, safflower, and rubia). In all cases, PLS-DA classification figures of merit in terms of sensitivity, specificity, error rate and accuracy were... 

It is possible to define multiresolution by reversing the process of subdivision. One approach to reverse a subdivision scheme appropriates pure numerical algebraic relations for subdivision using the interaction of diagrams (Bartels and Samavati, 2011; Samavati and Bartels, 2006). However, certain assumptions carried through the available work, two of which we wish to challenge: (1) the construction of multiresolutions for irregular meshes are reconsidered in the presence of any extraordinary vertex rather than being prepared beforehand as simple available relations and (2) the connectivity graph of the coarse mesh would have to be a subgraph of the connectivity graph of the fine mesh. 3... 

The laser powder deposition (LPD) process is an advanced material processing technique with many applications. Despite this fact, reliable and accurate control schemes have not yet been fully developed for the process. In this paper, identification of the LPD process is examined to find a more accurate model to predict and control the height of clad in real time. The model is adaptive single inputsingle output (SISO) and its structure is very similar to the Hammerstein model when the effective power (a function of laser power and velocity) is selected as the input and the clad height as the output. Weighted extended recursive least square (WERLS) is adopted to simultaneously estimate the... 

This paper presents a low-order and accurate method for the design of FIR fractional delay (FD) filters with complex coefficients. This method employs least square technique in Hilbert space to approximate the ideal FD transfer function with a FIR filter and to calculate its coefficients. The main advantages of the resulting filter are: very good response at all frequencies compared to other FD filter design methods and a good method to create very small delay. Design examples are presented to illustrate the effectiveness of this new design approach. © World Scientific Publishing Company  

To estimate the parameters of fuzzy linear regression models with fuzzy output and crisp inputs, we develop a mathematical programming model in this paper. The method is constructed on the basis of minimizing the square of the total difference between observed and estimated spread values or in other words minimizing the least square errors. The advantage of the proposed approach is its simplicity in programming and computation as well as its performance. To compare the performance of the proposed approach with the other methods, two examples are presented. © 2004 Elsevier Inc. All rights reserved  

Precipitation and scaling of calcium sulfate have been known as major problems facing process industries and oilfield operations. Most scale prediction models are based on aqueous thermodynamics and solubility behavior of salts in aqueous electrolyte solutions. There is yet a huge interest in developing reliable, simple, and accurate solubility prediction models. In this study, a comprehensive model based on least-squares support vector machine (LS-SVM) is presented, which is mainly devoted to calcium sulfate dihydrate (or gypsum) solubility in aqueous solutions of mixed electrolytes covering wide temperature ranges. In this respect, an aggregate of 880 experimental data were gathered from... 

We present a superlinearly convergent exact penalty method for solving constrained nonlinear least squares problems, in which the projected exact penalty Hessian is approximated by using a structured secant updating scheme. We give general conditions for the two-step superlinear convergence of the algorithm and prove that the projected structured Broyden-Fletcher-Goldfarb-Shanno (BFGS), Powell-symmetric-Broyden (PSB), and Davidon-Fletcher-Powell (DFP) update formulas satisfy these conditions. Then we extend the results to the projected structured convex Broyden family update formulas. Extensive testing results obtained by an implementation of our algorithms, as compared to the results... 

Zinc oxide (ZnO) nanoparticles have been used in a wide-ranging of applications such as transparent UV protection, light emitting diodes, sensors and photovoltaic cells. Many applications of ZnO nanoparticles could be improved by changing the particle size, shape and morphology. Therefore, studying the mechanism of shape evolution is crucial for size and shape controlled synthesis of nanocrystaline ZnO particles. As an alternative to sophisticated techniques such as transmission electron microscopy (TEM) and X-ray powder diffraction (XRD), commonly used for studying nanoparticles evolution, we herein employed UV/Vis spectroscopy for monitoring the evolution process of the ZnO nanocrystals... 

We have recently proposed a structured algorithm for solving constrained nonlinear least-squares problems and established its local two-step Q-superlinear convergence rate. The approach is based on an earlier adaptive structured scheme due to Mahdavi-Amiri and Bartels of the exact penalty method. The structured adaptation makes use of the ideas of Nocedal and Overton for handling quasi-Newton updates of projected Hessians and adapts a structuring scheme due to Engels and Martinez. For robustness, we have employed a specific nonsmooth line search strategy, taking account of the least-squares objective. Numerical results also confirm the practical relevance of our special considerations for...