Search results for: moments.
126 Printed Arabic Sub-Word Recognition Using Moments
Authors: Ibrahim A. El rube, Mohamed T. El Sonni, Soha S. Saleh
Abstract:the cursive nature of the Arabic writing makes it difficult to accurately segment characters or even deal with the whole word efficiently. Therefore, in this paper, a printed Arabic sub-word recognition system is proposed. The suggested algorithm utilizes geometrical moments as descriptors for the separated sub-words. Three types of moments are investigated and applied to the printed sub-word images after dividing each image into multiple parts using windowing. Since moments are global descriptors, the windowing mechanism allows the moments to be applied to local regions of the sub-word. The local-global mixture of the proposed scheme increases the discrimination power of the moments while keeping the simplicity and ease of use of moments.
Keywords: Arabic sub-word recognition, windowing, aspectratio, moments.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1424
125 Moment Invariants in Image Analysis
Authors: Jan Flusser
Abstract:This paper aims to present a survey of object recognition/classification methods based on image moments. We review various types of moments (geometric moments, complex moments) and moment-based invariants with respect to various image degradations and distortions (rotation, scaling, affine transform, image blurring, etc.) which can be used as shape descriptors for classification. We explain a general theory how to construct these invariants and show also a few of them in explicit forms. We review efficient numerical algorithms that can be used for moment computation and demonstrate practical examples of using moment invariants in real applications.
Keywords: Object recognition, degraded images, moments, moment invariants, geometric invariants, invariants to convolution, moment computation.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3700
124 Characteristic Function in Estimation of Probability Distribution Moments
Authors: Vladimir S. Timofeev
In this article the problem of distributional moments estimation is considered. The new approach of moments estimation based on usage of the characteristic function is proposed. By statistical simulation technique author shows that new approach has some robust properties. For calculation of the derivatives of characteristic function there is used numerical differentiation. Obtained results confirmed that author’s idea has a certain working efficiency and it can be recommended for any statistical applications.
Keywords: Characteristic function, distributional moments, robustness, outlier, statistical estimation problem, statistical simulation.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2147
123 Face Recognition Using Discrete Orthogonal Hahn Moments
Authors: Fatima Akhmedova, Simon Liao
Abstract:One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, nonredundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.
Keywords: Face Recognition, Hahn moments, Recognition-by-parts, Time-lapse.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1645
122 A Feature-based Invariant Watermarking Scheme Using Zernike Moments
Authors: Say Wei Foo, Qi Dong
Abstract:In this paper, a novel feature-based image watermarking scheme is proposed. Zernike moments which have invariance properties are adopted in the scheme. In the proposed scheme, feature points are first extracted from host image and several circular patches centered on these points are generated. The patches are used as carriers of watermark information because they can be regenerated to locate watermark embedding positions even when watermarked images are severely distorted. Zernike transform is then applied to the patches to calculate local Zernike moments. Dither modulation is adopted to quantize the magnitudes of the Zernike moments followed by false alarm analysis. Experimental results show that quality degradation of watermarked image is visually transparent. The proposed scheme is very robust against image processing operations and geometric attacks.
Keywords: Image watermarking, Zernike moments, Featurepoint, Invariance, Robustness.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1710
121 Moment Estimators of the Parameters of Zero-One Inflated Negative Binomial Distribution
Authors: Rafid Saeed Abdulrazak Alshkaki
Abstract:In this paper, zero-one inflated negative binomial distribution is considered, along with some of its structural properties, then its parameters were estimated using the method of moments. It is found that the method of moments to estimate the parameters of the zero-one inflated negative binomial models is not a proper method and may give incorrect conclusions.
Keywords: Zero one inflated models, negative binomial distribution, moments estimator, non-negative integer sampling.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 930
120 Content-Based Color Image Retrieval Based On 2-D Histogram and Statistical Moments
Authors: Khalid Elasnaoui, Brahim Aksasse, Mohammed Ouanan
Abstract:In this paper, we are interested in the problem of finding similar images in a large database. For this purpose we propose a new algorithm based on a combination of the 2-D histogram intersection in the HSV space and statistical moments. The proposed histogram is based on a 3x3 window and not only on the intensity of the pixel. This approach overcome the drawback of the conventional 1-D histogram which is ignoring the spatial distribution of pixels in the image, while the statistical moments are used to escape the effects of the discretisation of the color space which is intrinsic to the use of histograms. We compare the performance of our new algorithm to various methods of the state of the art and we show that it has several advantages. It is fast, consumes little memory and requires no learning. To validate our results, we apply this algorithm to search for similar images in different image databases.
Keywords: 2-D histogram, Statistical moments, Indexing, Similarity distance, Histograms intersection.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1533
119 Method of Moments for Analysis of Multiple Crack Interaction in an Isotropic Elastic Solid
Authors: Weifeng Wang, Xianwei Zeng, Jianping Ding
Abstract:The problem of N cracks interaction in an isotropic elastic solid is decomposed into a subproblem of a homogeneous solid without crack and N subproblems with each having a single crack subjected to unknown tractions on the two crack faces. The unknown tractions, namely pseudo tractions on each crack are expanded into polynomials with unknown coefficients, which have to be determined by the consistency condition, i.e. by the equivalence of the original multiple cracks interaction problem and the superposition of the N+1 subproblems. In this paper, Kachanov-s approach of average tractions is extended into the method of moments to approximately impose the consistence condition. Hence Kachanov-s method can be viewed as the zero-order method of moments. Numerical results of the stress intensity factors are presented for interactions of two collinear cracks, three collinear cracks, two parallel cracks, and three parallel cracks. As the order of moment increases, the accuracy of the method of moments improves.
Keywords: Crack interaction, stress intensity factor, multiplecracks, method of moments.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1473
118 Fuzzy Numbers and MCDM Methods for Portfolio Optimization
Authors: Thi T. Nguyen, Lee N. Gordon-Brown
Abstract:A new deployment of the multiple criteria decision making (MCDM) techniques: the Simple Additive Weighting (SAW), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for portfolio allocation, is demonstrated in this paper. Rather than exclusive reference to mean and variance as in the traditional mean-variance method, the criteria used in this demonstration are the first four moments of the portfolio distribution. Each asset is evaluated based on its marginal impacts to portfolio higher moments that are characterized by trapezoidal fuzzy numbers. Then centroid-based defuzzification is applied to convert fuzzy numbers to the crisp numbers by which SAW and TOPSIS can be deployed. Experimental results suggest the similar efficiency of these MCDM approaches to selecting dominant assets for an optimal portfolio under higher moments. The proposed approaches allow investors flexibly adjust their risk preferences regarding higher moments via different schemes adapting to various (from conservative to risky) kinds of investors. The other significant advantage is that, compared to the mean-variance analysis, the portfolio weights obtained by SAW and TOPSIS are consistently well-diversified.
Keywords: Fuzzy numbers, SAW, TOPSIS, portfolio optimization, higher moments, risk management.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2002
117 A Normalization-based Robust Watermarking Scheme Using Zernike Moments
Authors: Say Wei Foo, Qi Dong
Digital watermarking has become an important technique for copyright protection but its robustness against attacks remains a major problem. In this paper, we propose a normalizationbased robust image watermarking scheme. In the proposed scheme, original host image is first normalized to a standard form. Zernike transform is then applied to the normalized image to calculate Zernike moments. Dither modulation is adopted to quantize the magnitudes of Zernike moments according to the watermark bit stream. The watermark extracting method is a blind method. Security analysis and false alarm analysis are then performed. The quality degradation of watermarked image caused by the embedded watermark is visually transparent. Experimental results show that the proposed scheme has very high robustness against various image processing operations and geometric attacks.
Keywords: Image watermarking, Image normalization, Zernike moments, Robustness.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1648
116 Extreme Rainfall Frequency Analysis for Meteorological Sub-Division 4 of India Using L-Moments
Authors: Th. Arti Devi, Parthasarthi Choudhury
Extreme rainfall frequency analysis for Meteorological Sub-Division 4 of India was analyzed using L-moments approach. Serial Correlation and Mann Kendall tests were conducted for checking serially independent and stationarity of the observations. The discordancy measure for the sites was conducted to detect the discordant sites. The regional homogeneity was tested by comparing with 500 generated homogeneous regions using a 4 parameter Kappa distribution. The best fit distribution was selected based on ZDIST statistics and L-moments ratio diagram from the five extreme value distributions GPD, GLO, GEV, P3 and LP3. The LN3 distribution was selected and regional rainfall frequency relationship was established using index-rainfall procedure. A regional mean rainfall relationship was developed using multiple linear regression with latitude and longitude of the sites as variables.
Keywords: L-moments, ZDIST statistics, Serial correlation, Mann Kendall test.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2312
115 FPGA Based Parallel Architecture for the Computation of Third-Order Cross Moments
Authors: Syed Manzoor Qasim, Shuja Abbasi, Saleh Alshebeili, Bandar Almashary, Ateeq Ahmad Khan
Abstract:Higher-order Statistics (HOS), also known as cumulants, cross moments and their frequency domain counterparts, known as poly spectra have emerged as a powerful signal processing tool for the synthesis and analysis of signals and systems. Algorithms used for the computation of cross moments are computationally intensive and require high computational speed for real-time applications. For efficiency and high speed, it is often advantageous to realize computation intensive algorithms in hardware. A promising solution that combines high flexibility together with the speed of a traditional hardware is Field Programmable Gate Array (FPGA). In this paper, we present FPGA-based parallel architecture for the computation of third-order cross moments. The proposed design is coded in Very High Speed Integrated Circuit (VHSIC) Hardware Description Language (VHDL) and functionally verified by implementing it on Xilinx Spartan-3 XC3S2000FG900-4 FPGA. Implementation results are presented and it shows that the proposed design can operate at a maximum frequency of 86.618 MHz.
Keywords: Cross moments, Cumulants, FPGA, Hardware Implementation.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1595
114 Magnetic Properties of NiO and MnO by LSDA+U
Authors: Chewa Thassana, Wicharn Techitdheera
Abstract:The spin (ms) and orbital (mo) magnetic moment of the antiferromagnetic NiO and MnO have been studied in the local spin density approximation (LSDA+U) within full potential linear muffin-tin orbital (FP-LMTO method with in the coulomb interaction U varying from 0 to 10eV, exchange interaction J, from 0 to 1.0eV, and volume compression VC in range of 0 to 80%. Our calculated results shown that the spin magnetic moments and the orbital magnetic moments increase linearly with increasing U and J. While the interesting behaviour appears when volume compression is greater than 70% for NiO and 50% for MnO at which ms collapses. Further increase of volume compression to be at 80% leads to the disappearance of both magnetic moments.
Keywords: spin-orbital magnetic moment, Coulomb interaction U and exchange interaction J, volume compression VC, LSDA+U.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2061
113 Effect of Exchange Interaction J on Magnetic Moment of MnO
Authors: C. Thassana, W. Techitdheera
Abstract:This calculation focus on the effect of exchange interaction J and Coulomb interaction U on spin magnetic moments (ms) of MnO by using the local spin density approximation plus the Coulomb interaction (LSDA+U) method within full potential linear muffin-tin orbital (FP-LMTO). Our calculated results indicated that the spin magnetic moments correlated to J and U. The relevant results exhibited the increasing spin magnetic moments with increasing exchange interaction and Coulomb interaction. Furthermore, equations of spin magnetic moment, which h good correspondence to the experimental data 4.58μB, are defined ms = 0.11J +4.52μB and ms = 0.03U+4.52μB. So, the relation of J and U parameter is obtained, it is obviously, J = -0.249U+1.346 eV.
Keywords: exchange interaction J, the Coulomb interaction U, spin magnetic moment, LSDA+U, MnO.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1578
112 Detection and Analysis of Deficiencies in Groundnut Plant using Geometric Moments
Authors: Sumeet S. Nisale, Chandan J. Bharambe, Vidya N.More
Abstract:We propose our genuine research of geometric moments which detects the mineral inadequacy in the frail groundnut plant. This plant is prone to many deficiencies as a result of the variance in the soil nutrients. By analyzing the leaves of the plant, we detect the visual symptoms that are not recognizable to the naked eyes. We have collected about 160 samples of leaves from the nearby fields. The images have been taken by keeping every leaf into a black box to avoid the external interference. For the first time, it has been possible to provide the farmer with the stages of deficiencies. This paper has applied the algorithms successfully to many other plants like Lady-s finger, Green Bean, Lablab Bean, Chilli and Tomato. But we submit the results of the groundnut predominantly. The accuracy of our algorithm and method is almost 93%. This will again pioneer a kind of green revolution in the field of agriculture and will be a boon to that field.
Keywords: Component image, geometric moments, average intensity, average affected area, black boxProcedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1996
111 Proton and Neutron Magnetic Moments Based On Bag Models
Authors: G. R. Boroun, R. Harami
Using form factors of the proton and the neutron for different of Q2, bag radius of the proton and the neutron can be obtained based on bag models. Then using static bag radius, magnetic moments of the proton and the neutron can be obtained and compared with other results.
Keywords: MIT bag model, proton and neutron, magnetic moment.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1469
110 Persian Printed Numeral Characters Recognition Using Geometrical Central Moments and Fuzzy Min-Max Neural Network
Authors: Hamid Reza Boveiri
Abstract:In this paper, a new proposed system for Persian printed numeral characters recognition with emphasis on representation and recognition stages is introduced. For the first time, in Persian optical character recognition, geometrical central moments as character image descriptor and fuzzy min-max neural network for Persian numeral character recognition has been used. Set of different experiments on binary images of regular, translated, rotated and scaled Persian numeral characters has been done and variety of results has been presented. The best result was 99.16% correct recognition demonstrating geometrical central moments and fuzzy min-max neural network are adequate for Persian printed numeral character recognition.
Keywords: Fuzzy min-max neural network, geometrical centralmoments, optical character recognition, Persian digits recognition, Persian printed numeral characters recognition.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1577
109 On a Conjecture Regarding the Adam Optimizer
Authors: Mohamed Akrout, Douglas Tweed
The great success of deep learning relies on efficient optimizers, which are the algorithms that decide how to adjust network weights and biases based on gradient information. One of the most effective and widely used optimizers in recent years has been the method of adaptive moments, or Adam, but the mathematical reasons behind its effectiveness are still unclear. Attempts to analyse its behaviour have remained incomplete, in part because they hinge on a conjecture which has never been proven, regarding ratios of powers of the first and second moments of the gradient. Here we show that this conjecture is in fact false, but that a modified version of it is true, and can take its place in analyses of Adam.
Keywords: Adam optimizer, Bock’s conjecture, stochastic optimization, average regret.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28
108 Response Delay Model: Bridging the Gap in Urban Fire Disaster Response System
Authors: Sulaiman Yunus
The need for modeling response to urban fire disaster cannot be over emphasized, as recurrent fire outbreaks have gutted most cities of the world. This necessitated the need for a prompt and efficient response system in order to mitigate the impact of the disaster. Promptness, as a function of time, is seen to be the fundamental determinant for efficiency of a response system and magnitude of a fire disaster. Delay, as a result of several factors, is one of the major determinants of promptgness of a response system and also the magnitude of a fire disaster. Response Delay Model (RDM) intends to bridge the gap in urban fire disaster response system through incorporating and synchronizing the delay moments in measuring the overall efficiency of a response system and determining the magnitude of a fire disaster. The model identified two delay moments (pre-notification and Intra-reflex sequence delay) that can be elastic and collectively plays a significant role in influencing the efficiency of a response system. Due to variation in the elasticity of the delay moments, the model provides for measuring the length of delays in order to arrive at a standard average delay moment for different parts of the world, putting into consideration geographic location, level of preparedness and awareness, technological advancement, socio-economic and environmental factors. It is recommended that participatory researches should be embarked on locally and globally to determine standard average delay moments within each phase of the system so as to enable determining the efficiency of response systems and predicting fire disaster magnitudes.
Keywords: Delay moment, fire disaster, reflex sequence, response, response delay moment.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 572
107 A Real-Time Tracking System Developed for an Interactive Stage Performance
Authors: S. Hu, J. Mortensen, Bernard F. Buxton
A real-time tracking system was built to track performers on an interactive stage. Using an ordinary, up to date, desktop workstation, the performers- silhouette was segmented from the background and parameterized by calculating the normalized central image moments. In the stage system, the silhouette moments were then sent to a parallel workstation, which used them to generate corresponding 3D virtual geometry and projected the generated graphic back onto the stage.
Keywords: Image moment, interactive stage, real-time, silhouette.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1107
106 A Study on Stochastic Integral Associated with Catastrophes
Authors: M. Reni Sagayaraj, S. Anand Gnana Selvam, R. Reynald Susainathan
We analyze stochastic integrals associated with a mutation process. To be specific, we describe the cell population process and derive the differential equations for the joint generating functions for the number of mutants and their integrals in generating functions and their applications. We obtain first-order moments of the processes of the two-way mutation process in first-order moment structure of X (t) and Y (t) and the second-order moments of a one-way mutation process. In this paper, we obtain the limiting behaviour of the integrals in limiting distributions of X (t) and Y (t).
Keywords: Stochastic integrals, single–server queue model, catastrophes, busy period.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 681
105 Method of Moments Applied to a Cuboidal Cavity Resonator: Effect of Gravitational Field Produced by a Black Hole
Authors: Arti Vaish, Harish Parthasarathy
This paper deals with the formulation of Maxwell-s equations in a cavity resonator in the presence of the gravitational field produced by a blackhole. The metric of space-time due to the blackhole is the Schwarzchild metric. Conventionally, this is expressed in spherical polar coordinates. In order to adapt this metric to our problem, we have considered this metric in a small region close to the blackhole and expressed this metric in a cartesian system locally.
Keywords: Method of moments, General theory of relativity, Electromagnetism, Metric tensor, schwarzchild metric, Wave Equation.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1537
104 A Fuzzy Approach to Liver Tumor Segmentation with Zernike Moments
Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire
Abstract:In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy CMeans methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc.).
Keywords: Defuzzification, floating search, fuzzy clustering, Zernike moments.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1934
103 The Determinants of Corporate Cash Holdings in Nigeria: Evidence from General Method of Moments (GMM)
Authors: Sunday E. Ogundipe, Rafiu O. Salawu, Lawrencia O. Ogundipe
The study examines the determinants of corporate cash holding of non-financial quoted firms in Nigeria using a sample of fifty four non-financial quoted firms listed on the Nigeria Stock Exchange for the period 1995-2009. Data were sourced from the Annual reports of the sampled firms and analyzed using Generalized Method of Moments(GMM). The study finds evidence supportive of a target adjustment model and that firms can not instantaneously adjust towards the target cash level owing to the fact that adjustment cost being costly,. Also, the result shows significant negative relationship between cash holdings and firm size, net working capital, return on asset and bank relationship and positive relationship with growth opportunities, leverage, inventories, account receivables and financial distress. Furthermore, there is no significant relationship between cash holdings and cash flow. In Nigerian setting, most of the variables that are relevant for explaining cash holdings in the Developed countries are found by this study to be relevant also in Nigeria.
Keywords: Adjustment Model , Cash holding, Determinant, Generalized Method of Moments(GMM)Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3983
102 Effect of U-Turn in Reinforced Concrete Dog-Legged Stair Slabs
Authors: Abdul Baqi, Zaid Mohammad
Abstract:Reinforced concrete stair slabs with mid landings i.e. Dog-legged shaped are conventionally designed as per specifications of standard codes of practices which guide about the effective span according to the varying support conditions. Presently, the behavior of such slabs has been investigated using Finite Element method. A single flight stair slab with landings on both sides and supported at ends on wall, and a multi flight stair slab with landings and six different support arrangements have been analyzed. The results obtained for stresses, strains and deflections are used to describe the behavior of such stair slabs, including locations of critical moments and deflections. Values of critical moments obtained by F.E. analysis have also have been compared with that obtained from conventional analysis. Analytical results show that the moments are also critical near the kinks i.e. junction of mid-landing and inclined waist slab. This change in the behavior of dog-legged stair slab may be due to continuity of the material in transverse direction in two landings adjoining the waist slab, hence additional stiffness achieved. This change in the behavior is generally not taken care of in conventional method of design.
Keywords: Dog-legged, Stair slab, F.E. Analysis, Landing, Reinforced concrete.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4426
101 Genetic Algorithm and Padé-Moment Matching for Model Order Reduction
Authors: Shilpi Lavania, Deepak Nagaria
A mixed method for model order reduction is presented in this paper. The denominator polynomial is derived by matching both Markov parameters and time moments, whereas numerator polynomial derivation and error minimization is done using Genetic Algorithm. The efficiency of the proposed method can be investigated in terms of closeness of the response of reduced order model with respect to that of higher order original model and a comparison of the integral square error as well.
Keywords: Model Order Reduction (MOR), control theory, Markov parameters, time moments, genetic algorithm, Single Input Single Output (SISO).Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3377
100 A Methodology for Characterising the Tail Behaviour of a Distribution
Authors: Serge Provost, Yishan Zang
Following a review of various approaches that are utilized for classifying the tail behavior of a distribution, an easily implementable methodology that relies on an arctangent transformation is presented. The classification criterion is actually based on the difference between two specific quantiles of the transformed distribution. The resulting categories enable one to classify distributional tails as distinctly short, short, nearly medium, medium, extended medium and somewhat long, providing that at least two moments exist. Distributions possessing a single moment are said to be long tailed while those failing to have any finite moments are classified as having an extremely long tail. Several illustrative examples will be presented.
Keywords: Arctangent transformation, change of variables, heavy-tailed distributions, tail classification.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 503
99 Torsional Rigidities of Reinforced Concrete Beams Subjected to Elastic Lateral Torsional Buckling
Authors: Ilker Kalkan, Saruhan Kartal
Abstract:Reinforced concrete (RC) beams rarely undergo lateral-torsional buckling (LTB), since these beams possess large lateral bending and torsional rigidities owing to their stocky cross-sections, unlike steel beams. However, the problem of LTB is becoming more and more pronounced in the last decades as the span lengths of concrete beams increase and the cross-sections become more slender with the use of pre-stressed concrete. The buckling moment of a beam mainly depends on its lateral bending rigidity and torsional rigidity. The nonhomogeneous and elastic-inelastic nature of RC complicates estimation of the buckling moments of concrete beams. Furthermore, the lateral bending and torsional rigidities of RC beams and the buckling moments are affected from different forms of concrete cracking, including flexural, torsional and restrained shrinkage cracking. The present study pertains to the effects of concrete cracking on the torsional rigidities of RC beams prone to elastic LTB. A series of tests on rather slender RC beams indicated that torsional cracking does not initiate until buckling in elastic LTB, while flexural cracking associated with lateral bending takes place even at the initial stages of loading. Hence, the present study clearly indicated that the un-cracked torsional rigidity needs to be used for estimating the buckling moments of RC beams liable to elastic LTB.
Keywords: Lateral stability, post-cracking torsional rigidity, uncracked torsional rigidity, critical moment.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1948
98 Evolving Neural Networks using Moment Method for Handwritten Digit Recognition
Authors: H. El Fadili, K. Zenkouar, H. Qjidaa
Abstract:This paper proposes a neural network weights and topology optimization using genetic evolution and the backpropagation training algorithm. The proposed crossover and mutation operators aims to adapt the networks architectures and weights during the evolution process. Through a specific inheritance procedure, the weights are transmitted from the parents to their offsprings, which allows re-exploitation of the already trained networks and hence the acceleration of the global convergence of the algorithm. In the preprocessing phase, a new feature extraction method is proposed based on Legendre moments with the Maximum entropy principle MEP as a selection criterion. This allows a global search space reduction in the design of the networks. The proposed method has been applied and tested on the well known MNIST database of handwritten digits.
Keywords: Genetic algorithm, Legendre Moments, MEP, Neural Network.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1557
97 A Neural Approach for the Offline Recognition of the Arabic Handwritten Words of the Algerian Departments
Authors: Salim Ouchtati, Jean Sequeira, Mouldi Bedda
Abstract:In the context of the handwriting recognition, we propose an off line system for the recognition of the Arabic handwritten words of the Algerian departments. The study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the handwritten word by several methods. The Distribution parameters, the centered moments of the different projections of the different segments, the centered moments of the word image coding according to the directions of Freeman, and the Barr features applied binary image of the word and on its different segments. The classification is achieved by a multi layers perceptron. A detailed experiment is carried and satisfactory recognition results are reported.
Keywords: Handwritten word recognition, neural networks, image processing, pattern recognition, features extraction.Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1799