Search results for: multiresolution signal decomposition.
1361 Review of Surface Electromyogram Signals: Its Analysis and Applications
Authors: Anjana Goen, D. C. Tiwari
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Electromyography (EMG) is the study of muscles function through analysis of electrical activity produced from muscles. This electrical activity which is displayed in the form of signal is the result of neuromuscular activation associated with muscle contraction. The most common techniques of EMG signal recording are by using surface and needle/wire electrode where the latter is usually used for interest in deep muscle. This paper will focus on surface electromyogram (SEMG) signal. During SEMG recording, several problems had to been countered such as noise, motion artifact and signal instability. Thus, various signal processing techniques had been implemented to produce a reliable signal for analysis. SEMG signal finds broad application particularly in biomedical field. It had been analyzed and studied for various interests such as neuromuscular disease, enhancement of muscular function and human-computer interface.
Keywords: Evolvable hardware (EHW), Functional Electrical Simulation (FES), Hidden Markov Model (HMM), Hjorth Time Domain (HTD).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35071360 An Algorithm for Computing the Analytic Singular Value Decomposition
Authors: Drahoslava Janovska, Vladimir Janovsky, Kunio Tanabe
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A proof of convergence of a new continuation algorithm for computing the Analytic SVD for a large sparse parameter– dependent matrix is given. The algorithm itself was developed and numerically tested in [5].
Keywords: Analytic Singular Value Decomposition, large sparse parameter–dependent matrices, continuation algorithm of a predictorcorrector type.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14471359 Strip Decomposition Parallelization of Fast Direct Poisson Solver on a 3D Cartesian Staggered Grid
Authors: Minh Vuong Pham, Frédéric Plourde, Son Doan Kim
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A strip domain decomposition parallel algorithm for fast direct Poisson solver is presented on a 3D Cartesian staggered grid. The parallel algorithm follows the principles of sequential algorithm for fast direct Poisson solver. Both Dirichlet and Neumann boundary conditions are addressed. Several test cases are likewise addressed in order to shed light on accuracy and efficiency in the strip domain parallelization algorithm. Actually the current implementation shows a very high efficiency when dealing with a large grid mesh up to 3.6 * 109 under massive parallel approach, which explicitly demonstrates that the proposed algorithm is ready for massive parallel computing.
Keywords: Strip-decomposition, parallelization, fast directpoisson solver.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20371358 Efficient Implementation of Serial and Parallel Support Vector Machine Training with a Multi-Parameter Kernel for Large-Scale Data Mining
Authors: Tatjana Eitrich, Bruno Lang
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This work deals with aspects of support vector learning for large-scale data mining tasks. Based on a decomposition algorithm that can be run in serial and parallel mode we introduce a data transformation that allows for the usage of an expensive generalized kernel without additional costs. In order to speed up the decomposition algorithm we analyze the problem of working set selection for large data sets and analyze the influence of the working set sizes onto the scalability of the parallel decomposition scheme. Our modifications and settings lead to improvement of support vector learning performance and thus allow using extensive parameter search methods to optimize classification accuracy.
Keywords: Support Vector Machines, Shared Memory Parallel Computing, Large Data
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15711357 Wavelet-Based Classification of Myocardial Ischemia, Arrhythmia, Congestive Heart Failure and Sleep Apnea
Authors: Santanu Chattopadhyay, Gautam Sarkar, Arabinda Das
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This paper presents wavelet based classification of various heart diseases. Electrocardiogram signals of different heart patients have been studied. Statistical natures of electrocardiogram signals for different heart diseases have been compared with the statistical nature of electrocardiograms for normal persons. Under this study four different heart diseases have been considered as follows: Myocardial Ischemia (MI), Congestive Heart Failure (CHF), Arrhythmia and Sleep Apnea. Statistical nature of electrocardiograms for each case has been considered in terms of kurtosis values of two types of wavelet coefficients: approximate and detail. Nine wavelet decomposition levels have been considered in each case. Kurtosis corresponding to both approximate and detail coefficients has been considered for decomposition level one to decomposition level nine. Based on significant difference, few decomposition levels have been chosen and then used for classification.Keywords: Arrhythmia, congestive heart failure, discrete wavelet transform, electrocardiogram, myocardial ischemia, sleep apnea.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6581356 AC Signals Estimation from Irregular Samples
Authors: Predrag B. Petrović
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The paper deals with the estimation of amplitude and phase of an analogue multi-harmonic band-limited signal from irregularly spaced sampling values. To this end, assuming the signal fundamental frequency is known in advance (i.e., estimated at an independent stage), a complexity-reduced algorithm for signal reconstruction in time domain is proposed. The reduction in complexity is achieved owing to completely new analytical and summarized expressions that enable a quick estimation at a low numerical error. The proposed algorithm for the calculation of the unknown parameters requires O((2M+1)2) flops, while the straightforward solution of the obtained equations takes O((2M+1)3) flops (M is the number of the harmonic components). It is applied in signal reconstruction, spectral estimation, system identification, as well as in other important signal processing problems. The proposed method of processing can be used for precise RMS measurements (for power and energy) of a periodic signal based on the presented signal reconstruction. The paper investigates the errors related to the signal parameter estimation, and there is a computer simulation that demonstrates the accuracy of these algorithms.
Keywords: Band-limited signals, Fourier coefficient estimation, analytical solutions, signal reconstruction, time.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17401355 Signal Transmission Analysis of Differential Pairs Using Semicircle-Shaped Via Structure
Authors: Moonjung Kim, Chang-Ho Hyun, Won-Ho Kim
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In this paper, the signal transmission analysis of the semicircle-shaped via structure for the differential pairs is presented in the frequency range up to 10 GHz. In order to improve the signal transmission properties in the differential pairs, single via is separated centrally into two semicircle-shaped sections, which are interconnected with the traces of differential pairs respectively. This via structure make possible to route differential pairs using only one via. In addition, it can improve impedance discontinuity around its region and then enhance the signal transmission properties in the differential pairs. The electrical analysis such as S-parameter calculation and eye diagram simulation has been performed to investigate the improvement of the signal transmission property in the differential pairs with new via structure.Keywords: Differential pairs, signal transmission property, via, S-parameter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 39171354 Target Signal Detection Using MUSIC Spectrum in Noise Environment
Authors: Sangjun Park, Sangbae Jeong, Moonsung Han, Minsoo hahn
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In this paper, a target signal detection method using multiple signal classification (MUSIC) algorithm is proposed. The MUSIC algorithm is a subspace-based direction of arrival (DOA) estimation method. The algorithm detects the DOAs of multiple sources using the inverse of the eigenvalue-weighted eigen spectra. To apply the algorithm to target signal detection for GSC-based beamforming, we utilize its spectral response for the target DOA in noisy conditions. For evaluation of the algorithm, the performance of the proposed target signal detection method is compared with that of the normalized cross-correlation (NCC), the fixed beamforming, and the power ratio method. Experimental results show that the proposed algorithm significantly outperforms the conventional ones in receiver operating characteristics(ROC) curves.Keywords: Beamforming, direction of arrival, multiple signal classification, target signal detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25311353 A Linearization and Decomposition Based Approach to Minimize the Non-Productive Time in Transfer Lines
Authors: Hany Osman, M. F. Baki
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We address the balancing problem of transfer lines in this paper to find the optimal line balancing that minimizes the nonproductive time. We focus on the tool change time and face orientation change time both of which influence the makespane. We consider machine capacity limitations and technological constraints associated with the manufacturing process of auto cylinder heads. The problem is represented by a mixed integer programming model that aims at distributing the design features to workstations and sequencing the machining processes at a minimum non-productive time. The proposed model is solved by an algorithm established using linearization schemes and Benders- decomposition approach. The experiments show the efficiency of the algorithm in reaching the exact solution of small and medium problem instances at reasonable time.Keywords: Transfer line balancing, Benders' decomposition, Linearization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17161352 Robust Stability Criteria for Uncertain Genetic Regulatory Networks with Time-Varying Delays
Authors: Wenqin Wang, Shouming Zhong
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This paper presents the robust stability criteria for uncertain genetic regulatory networks with time-varying delays. One key point of the criterion is that the decomposition of the matrix ˜D into ˜D = ˜D1 + ˜D2. This decomposition corresponds to a decomposition of the delayed terms into two groups: the stabilizing ones and the destabilizing ones. This technique enables one to take the stabilizing effect of part of the delayed terms into account. Meanwhile, by choosing an appropriate new Lyapunov functional, a new delay-dependent stability criteria is obtained and formulated in terms of linear matrix inequalities (LMIs). Finally, numerical examples are presented to illustrate the effectiveness of the theoretical results.
Keywords: Genetic regulatory network, Time-varying delay, Uncertain system, Lyapunov-Krasovskii functional
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15191351 A Review in Advanced Digital Signal Processing Systems
Authors: Roza Dastres, Mohsen Soori
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Digital Signal Processing (DSP) is the use of digital processing systems by computers in order to perform a variety of signal processing operations. It is the mathematical manipulation of a digital signal's numerical values in order to increase quality as well as effects of signals. DSP can include linear or nonlinear operators in order to process and analyze the input signals. The nonlinear DSP processing is closely related to nonlinear system detection and can be implemented in time, frequency and space-time domains. Applications of the DSP can be presented as control systems, digital image processing, biomedical engineering, speech recognition systems, industrial engineering, health care systems, radar signal processing and telecommunication systems. In this study, advanced methods and different applications of DSP are reviewed in order to move forward the interesting research filed.Keywords: Digital signal processing, advanced telecommunication, nonlinear signal processing, speech recognition systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10101350 A Semi-Classical Signal Analysis Method for the Analysis of Turbomachinery Flow Unsteadiness
Authors: Fadi Eleiwi, Taous Meriem Laleg-Kirati, Sofiane Khelladi, Farid Bakir
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This paper presents the use of a semi-classical signal analysis method that has been developed recently for the analysis of turbomachinery flow unsteadiness. We will focus on the correlation between theSemi-Classical Signal Analysis parameters and some physical parameters in relation with turbomachinery features. To demonstrate the potential of the proposed approach, a static pressure signal issued from a rotor/stator interaction of a centrifugal pump is studied. Several configurations of the pump are compared.Keywords: Semi-classical signal analysis, turbomachines, newindices, physical parameters
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14361349 Carbon Supported Cu and TiO2 Catalysts Applied for Ozone Decomposition
Authors: Katya Milenova, Penko Nikolov, Irina Stambolova, Plamen Nikolov, Vladimir Blaskov
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In this article a comparison was made between Cu and TiO2 supported catalysts on activated carbon for ozone decomposition reaction. The activated carbon support in the case of TiO2/AC sample was prepared by physicochemical pyrolysis and for Cu/AC samples the supports are chemically modified carbons. The prepared catalysts were synthesized by impregnation method. The samples were annealed in two different regimes- in air and under vacuum. To examine adsorption efficiency of the samples BET method was used. All investigated catalysts supported on chemically modified carbons have higher specific surface area compared to the specific surface area of TiO2 supported catalysts, varying in the range 590÷620 m2/g. The method of synthesis of the precursors had influenced catalytic activity.
Keywords: Activated carbon, adsorption, copper, ozone decomposition, TiO2.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26441348 Enhancement of Low Contrast Satellite Images using Discrete Cosine Transform and Singular Value Decomposition
Authors: A. K. Bhandari, A. Kumar, P. K. Padhy
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In this paper, a novel contrast enhancement technique for contrast enhancement of a low-contrast satellite image has been proposed based on the singular value decomposition (SVD) and discrete cosine transform (DCT). The singular value matrix represents the intensity information of the given image and any change on the singular values change the intensity of the input image. The proposed technique converts the image into the SVD-DCT domain and after normalizing the singular value matrix; the enhanced image is reconstructed by using inverse DCT. The visual and quantitative results suggest that the proposed SVD-DCT method clearly shows the increased efficiency and flexibility of the proposed method over the exiting methods such as Linear Contrast Stretching technique, GHE technique, DWT-SVD technique, DWT technique, Decorrelation Stretching technique, Gamma Correction method based techniques.Keywords: Singular Value Decomposition (SVD), discretecosine transforms (DCT), image equalization and satellite imagecontrast enhancement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 38261347 Bisymmetric, Persymmetric Matrices and Its Applications in Eigen-decomposition of Adjacency and Laplacian Matrices
Authors: Mahdi Nouri
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In this paper we introduce an efficient solution method for the Eigen-decomposition of bisymmetric and per symmetric matrices of symmetric structures. Here we decompose adjacency and Laplacian matrices of symmetric structures to submatrices with low dimension for fast and easy calculation of eigenvalues and eigenvectors. Examples are included to show the efficiency of the method.Keywords: Graphs theory, Eigensolution, adjacency and Laplacian matrix, Canonical forms, bisymmetric, per symmetric.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24311346 Measurement of UHF Signal Strength Propagating from Road Surface with Vehicle Obstruction
Authors: C. Thongsopa, P. Sukphongchirakul, A. Intarapanich, P. Jarataku
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Radio wave propagation on the road surface is a major problem on wireless sensor network for traffic monitoring. In this paper, we compare receiving signal strength on two scenarios 1) an empty road and 2) a road with a vehicle. We investigate the effect of antenna polarization and antenna height to the receiving signal strength. The transmitting antenna is installed on the road surface. The receiving signal is measured 360 degrees around the transmitting antenna with the radius of 2.5 meters. Measurement results show the receiving signal fluctuation around the transmitting antenna in both scenarios. Receiving signal with vertical polarization antenna results in higher signal strength than horizontal polarization antenna. The optimum antenna elevation is 1 meter for both horizon and vertical polarizations with the vehicle on the road. In the empty road, the receiving signal level is unvarying with the elevation when the elevation is greater than 1.5 meters.Keywords: Wave propagation, wireless sensor network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17461345 Traffic Signal Design and Simulation for Vulnerable Road Users Safety and Bus Preemption
Authors: Shih-Ching Lo, Hsieh-Chu Huang
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Mostly, pedestrian-car accidents occurred at a signalized interaction is because pedestrians cannot across the intersection safely within the green light. From the viewpoint of pedestrian, there might have two reasons. The first one is pedestrians cannot speed up to across the intersection, such as the elders. The other reason is pedestrians do not sense that the signal phase is going to change and their right-of-way is going to lose. Developing signal logic to protect pedestrian, who is crossing an intersection is the first purpose of this study. Another purpose of this study is improving the reliability and reduce delay of public transportation service. Therefore, bus preemption is also considered in the designed signal logic. In this study, the traffic data of the intersection of Chong-Qing North Road and Min-Zu West Road, Taipei, Taiwan, is employed to calibrate and validate the signal logic by simulation. VISSIM 5.20, which is a microscopic traffic simulation software, is employed to simulate the signal logic. From the simulated results, the signal logic presented in this study can protect pedestrians crossing the intersection successfully. The design of bus preemption can reduce the average delay. However, the pedestrian safety and bus preemptive signal will influence the average delay of cars largely. Thus, whether applying the pedestrian safety and bus preemption signal logic to an isolated intersection or not should be evaluated carefully.Keywords: vulnerable road user, bus preemption, signal design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16641344 Sub-Image Detection Using Fast Neural Processors and Image Decomposition
Authors: Hazem M. El-Bakry, Qiangfu Zhao
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In this paper, an approach to reduce the computation steps required by fast neural networksfor the searching process is presented. The principle ofdivide and conquer strategy is applied through imagedecomposition. Each image is divided into small in sizesub-images and then each one is tested separately usinga fast neural network. The operation of fast neuralnetworks based on applying cross correlation in thefrequency domain between the input image and theweights of the hidden neurons. Compared toconventional and fast neural networks, experimentalresults show that a speed up ratio is achieved whenapplying this technique to locate human facesautomatically in cluttered scenes. Furthermore, fasterface detection is obtained by using parallel processingtechniques to test the resulting sub-images at the sametime using the same number of fast neural networks. Incontrast to using only fast neural networks, the speed upratio is increased with the size of the input image whenusing fast neural networks and image decomposition.
Keywords: Fast Neural Networks, 2D-FFT, CrossCorrelation, Image decomposition, Parallel Processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21681343 A Nonoblivious Image Watermarking System Based on Singular Value Decomposition and Texture Segmentation
Authors: Soroosh Rezazadeh, Mehran Yazdi
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In this paper, a robust digital image watermarking scheme for copyright protection applications using the singular value decomposition (SVD) is proposed. In this scheme, an entropy masking model has been applied on the host image for the texture segmentation. Moreover, the local luminance and textures of the host image are considered for watermark embedding procedure to increase the robustness of the watermarking scheme. In contrast to all existing SVD-based watermarking systems that have been designed to embed visual watermarks, our system uses a pseudo-random sequence as a watermark. We have tested the performance of our method using a wide variety of image processing attacks on different test images. A comparison is made between the results of our proposed algorithm with those of a wavelet-based method to demonstrate the superior performance of our algorithm.Keywords: Watermarking, copyright protection, singular value decomposition, entropy masking, texture segmentation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17501342 Tool Failure Detection Based on Statistical Analysis of Metal Cutting Acoustic Emission Signals
Authors: Othman Belgassim, Krzysztof Jemielniak
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The analysis of Acoustic Emission (AE) signal generated from metal cutting processes has often approached statistically. This is due to the stochastic nature of the emission signal as a result of factors effecting the signal from its generation through transmission and sensing. Different techniques are applied in this manner, each of which is suitable for certain processes. In metal cutting where the emission generated by the deformation process is rather continuous, an appropriate method for analysing the AE signal based on the root mean square (RMS) of the signal is often used and is suitable for use with the conventional signal processing systems. The aim of this paper is to set a strategy in tool failure detection in turning processes via the statistic analysis of the AE generated from the cutting zone. The strategy is based on the investigation of the distribution moments of the AE signal at predetermined sampling. The skews and kurtosis of these distributions are the key elements in the detection. A normal (Gaussian) distribution has first been suggested then this was eliminated due to insufficiency. The so called Beta distribution was then considered, this has been used with an assumed β density function and has given promising results with regard to chipping and tool breakage detection.Keywords: AE signal, skew, kurtosis, tool failure
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18311341 Solving Fully Fuzzy Linear Systems by use of a Certain Decomposition of the Coefficient Matrix
Authors: S. H. Nasseri, M. Sohrabi, E. Ardil
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In this paper, we give a certain decomposition of the coefficient matrix of the fully fuzzy linear system (FFLS) to obtain a simple algorithm for solving these systems. The new algorithm can solve FFLS in a smaller computing process. We will illustrate our method by solving some examples.Keywords: Fully fuzzy linear system, Fuzzy number, LUdecomposition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16991340 Teager-Huang Analysis Applied to Sonar Target Recognition
Authors: J.-C. Cexus, A.O. Boudraa
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In this paper, a new approach for target recognition based on the Empirical mode decomposition (EMD) algorithm of Huang etal. [11] and the energy tracking operator of Teager [13]-[14] is introduced. The conjunction of these two methods is called Teager-Huang analysis. This approach is well suited for nonstationary signals analysis. The impulse response (IR) of target is first band pass filtered into subsignals (components) called Intrinsic mode functions (IMFs) with well defined Instantaneous frequency (IF) and Instantaneous amplitude (IA). Each IMF is a zero-mean AM-FM component. In second step, the energy of each IMF is tracked using the Teager energy operator (TEO). IF and IA, useful to describe the time-varying characteristics of the signal, are estimated using the Energy separation algorithm (ESA) algorithm of Maragos et al .[16]-[17]. In third step, a set of features such as skewness and kurtosis are extracted from the IF, IA and IMF energy functions. The Teager-Huang analysis is tested on set of synthetic IRs of Sonar targets with different physical characteristics (density, velocity, shape,? ). PCA is first applied to features to discriminate between manufactured and natural targets. The manufactured patterns are classified into spheres and cylinders. One hundred percent of correct recognition is achieved with twenty three echoes where sixteen IRs, used for training, are free noise and seven IRs, used for testing phase, are corrupted with white Gaussian noise.
Keywords: Target recognition, Empirical mode decomposition, Teager-Kaiser energy operator, Features extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22691339 Application of Computational Methods Mm2 and Gussian for Studing Unimolecular Decomposition of Vinil Ethers based on the Mechanism of Hydrogen Bonding
Authors: Behnaz Shahrokh, Garnik N. Sargsyan, Arkadi B. Harutyunyan
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Investigations of the unimolecular decomposition of vinyl ethyl ether (VEE), vinyl propyl ether (VPE) and vinyl butyl ether (VBE) have shown that activation of the molecule of a ether results in formation of a cyclic construction - the transition state (TS), which may lead to the displacement of the thermodynamic equilibrium towards the reaction products. The TS is obtained by applying energy minimization relative to the ground state of an ether under the program MM2 when taking into account the hydrogen bond formation between a hydrogen atom of alkyl residue and the extreme atom of carbon of the vinyl group. The dissociation of TS up to the products is studied by energy minimization procedure using the mathematical program Gaussian. The obtained calculation data for VEE testify that the decomposition of this ether may be conditioned by hydrogen bond formation for two possible versions: when α- or β- hydrogen atoms of the ethyl group are bound to carbon atom of the vinyl group. Applying the same calculation methods to other ethers (VPE and VBE) it is shown that only in the case of hydrogen bonding between α-hydrogen atom of the alkyl residue and the extreme atom of carbon of the vinyl group (αH---C) results in decay of theses ethers.Keywords: Gaussian, MM2, ethers, TS, decomposition
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12131338 Functional Decomposition Based Effort Estimation Model for Software-Intensive Systems
Authors: Nermin Sökmen
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An effort estimation model is needed for softwareintensive projects that consist of hardware, embedded software or some combination of the two, as well as high level software solutions. This paper first focuses on functional decomposition techniques to measure functional complexity of a computer system and investigates its impact on system development effort. Later, it examines effects of technical difficulty and design team capability factors in order to construct the best effort estimation model. With using traditional regression analysis technique, the study develops a system development effort estimation model which takes functional complexity, technical difficulty and design team capability factors as input parameters. Finally, the assumptions of the model are tested.
Keywords: Functional complexity, functional decomposition, development effort, technical difficulty, design team capability, regression analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22691337 Computationally Efficient Signal Quality Improvement Method for VoIP System
Authors: H. P. Singh, S. Singh
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The voice signal in Voice over Internet protocol (VoIP) system is processed through the best effort policy based IP network, which leads to the network degradations including delay, packet loss jitter. The work in this paper presents the implementation of finite impulse response (FIR) filter for voice quality improvement in the VoIP system through distributed arithmetic (DA) algorithm. The VoIP simulations are conducted with AMR-NB 6.70 kbps and G.729a speech coders at different packet loss rates and the performance of the enhanced VoIP signal is evaluated using the perceptual evaluation of speech quality (PESQ) measurement for narrowband signal. The results show reduction in the computational complexity in the system and significant improvement in the quality of the VoIP voice signal.
Keywords: VoIP, Signal Quality, Distributed Arithmetic, Packet Loss, Speech Coder.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18181336 An Improved Algorithm for Calculation of the Third-order Orthogonal Tensor Product Expansion by Using Singular Value Decomposition
Authors: Chiharu Okuma, Naoki Yamamoto, Jun Murakami
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As a method of expanding a higher-order tensor data to tensor products of vectors we have proposed the Third-order Orthogonal Tensor Product Expansion (3OTPE) that did similar expansion as Higher-Order Singular Value Decomposition (HOSVD). In this paper we provide a computation algorithm to improve our previous method, in which SVD is applied to the matrix that constituted by the contraction of original tensor data and one of the expansion vector obtained. The residual of the improved method is smaller than the previous method, truncating the expanding tensor products to the same number of terms. Moreover, the residual is smaller than HOSVD when applying to color image data. It is able to be confirmed that the computing time of improved method is the same as the previous method and considerably better than HOSVD.
Keywords: Singular value decomposition (SVD), higher-orderSVD (HOSVD), outer product expansion, power method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16811335 Piecewise Interpolation Filter for Effective Processing of Large Signal Sets
Authors: Anatoli Torokhti, Stanley Miklavcic
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Suppose KY and KX are large sets of observed and reference signals, respectively, each containing N signals. Is it possible to construct a filter F : KY → KX that requires a priori information only on few signals, p N, from KX but performs better than the known filters based on a priori information on every reference signal from KX? It is shown that the positive answer is achievable under quite unrestrictive assumptions. The device behind the proposed method is based on a special extension of the piecewise linear interpolation technique to the case of random signal sets. The proposed technique provides a single filter to process any signal from the arbitrarily large signal set. The filter is determined in terms of pseudo-inverse matrices so that it always exists.Keywords: Wiener filter, filtering of stochastic signals.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14041334 The Haar Wavelet Transform of the DNA Signal Representation
Authors: Abdelkader Magdy, Magdy Saeb, A. Baith Mohamed, Ahmed Khadragi
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The Deoxyribonucleic Acid (DNA) which is a doublestranded helix of nucleotides consists of: Adenine (A), Cytosine (C), Guanine (G) and Thymine (T). In this work, we convert this genetic code into an equivalent digital signal representation. Applying a wavelet transform, such as Haar wavelet, we will be able to extract details that are not so clear in the original genetic code. We compare between different organisms using the results of the Haar wavelet Transform. This is achieved by using the trend part of the signal since the trend part bears the most energy of the digital signal representation. Consequently, we will be able to quantitatively reconstruct different biological families.
Keywords: Digital Signal, DNA, Fluctuation part, Haar wavelet, Nucleotides, Trend part.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19131333 Automatic Sleep Stage Scoring with Wavelet Packets Based on Single EEG Recording
Authors: Luay A. Fraiwan, Natheer Y. Khaswaneh, Khaldon Y. Lweesy
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Sleep stage scoring is the process of classifying the stage of the sleep in which the subject is in. Sleep is classified into two states based on the constellation of physiological parameters. The two states are the non-rapid eye movement (NREM) and the rapid eye movement (REM). The NREM sleep is also classified into four stages (1-4). These states and the state wakefulness are distinguished from each other based on the brain activity. In this work, a classification method for automated sleep stage scoring based on a single EEG recording using wavelet packet decomposition was implemented. Thirty two ploysomnographic recording from the MIT-BIH database were used for training and validation of the proposed method. A single EEG recording was extracted and smoothed using Savitzky-Golay filter. Wavelet packets decomposition up to the fourth level based on 20th order Daubechies filter was used to extract features from the EEG signal. A features vector of 54 features was formed. It was reduced to a size of 25 using the gain ratio method and fed into a classifier of regression trees. The regression trees were trained using 67% of the records available. The records for training were selected based on cross validation of the records. The remaining of the records was used for testing the classifier. The overall correct rate of the proposed method was found to be around 75%, which is acceptable compared to the techniques in the literature.Keywords: Features selection, regression trees, sleep stagescoring, wavelet packets.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23191332 Comparison between Higher-Order SVD and Third-order Orthogonal Tensor Product Expansion
Authors: Chiharu Okuma, Jun Murakami, Naoki Yamamoto
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In digital signal processing it is important to approximate multi-dimensional data by the method called rank reduction, in which we reduce the rank of multi-dimensional data from higher to lower. For 2-dimennsional data, singular value decomposition (SVD) is one of the most known rank reduction techniques. Additional, outer product expansion expanded from SVD was proposed and implemented for multi-dimensional data, which has been widely applied to image processing and pattern recognition. However, the multi-dimensional outer product expansion has behavior of great computation complex and has not orthogonally between the expansion terms. Therefore we have proposed an alterative method, Third-order Orthogonal Tensor Product Expansion short for 3-OTPE. 3-OTPE uses the power method instead of nonlinear optimization method for decreasing at computing time. At the same time the group of B. D. Lathauwer proposed Higher-Order SVD (HOSVD) that is also developed with SVD extensions for multi-dimensional data. 3-OTPE and HOSVD are similarly on the rank reduction of multi-dimensional data. Using these two methods we can obtain computation results respectively, some ones are the same while some ones are slight different. In this paper, we compare 3-OTPE to HOSVD in accuracy of calculation and computing time of resolution, and clarify the difference between these two methods.Keywords: Singular value decomposition (SVD), higher-order SVD (HOSVD), higher-order tensor, outer product expansion, power method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1552