**Commenced**in January 2007

**Frequency:**Monthly

**Edition:**International

**Paper Count:**3285

# Search results for: loss function decomposition.

##### 3285 Transmission Loss Allocation via Loss Function Decomposition and Current Projection Concept

**Authors:**
M.R. Ebrahimi,
Z. Ghofrani,
M. Ehsan

**Abstract:**

**Keywords:**
Transmission loss,
loss allocation,
current projectionconcept,
loss function decomposition.

##### 3284 Decomposition of Graphs into Induced Paths and Cycles

**Authors:**
I. Sahul Hamid,
Abraham V. M.

**Abstract:**

A decomposition of a graph G is a collection ψ of subgraphs H1,H2, . . . , Hr of G such that every edge of G belongs to exactly one Hi. If each Hi is either an induced path or an induced cycle in G, then ψ is called an induced path decomposition of G. The minimum cardinality of an induced path decomposition of G is called the induced path decomposition number of G and is denoted by πi(G). In this paper we initiate a study of this parameter.

**Keywords:**
Path decomposition,
Induced path decomposition,
Induced path decomposition number.

##### 3283 Induced Acyclic Path Decomposition in Graphs

**Authors:**
Abraham V. M.,
I. Sahul Hamid

**Abstract:**

**Keywords:**
Cycle decomposition,
Induced acyclic path decomposition,
Induced acyclic path decomposition number.

##### 3282 Estimation of Bayesian Sample Size for Binomial Proportions Using Areas P-tolerance with Lowest Posterior Loss

**Authors:**
H. Bevrani,
N. Najafi

**Abstract:**

**Keywords:**
Bayesian inference,
Beta-binomial Distribution,
LPLcriteria,
quadratic loss function.

##### 3281 Method of Intelligent Fault Diagnosis of Preload Loss for Single Nut Ball Screws through the Sensed Vibration Signals

**Authors:**
Yi-Cheng Huang,
Yan-Chen Shin

**Abstract:**

**Keywords:**
Empirical Mode Decomposition,
Hilbert-Huang Transform,
Multi-scale Entropy,
Preload Loss,
Single-nut Ball Screw

##### 3280 A New Definition of the Intrinsic Mode Function

**Authors:**
Zhihua Yang,
Lihua Yang

**Abstract:**

This paper makes a detailed analysis regarding the definition of the intrinsic mode function and proves that Condition 1 of the intrinsic mode function can really be deduced from Condition 2. Finally, an improved definition of the intrinsic mode function is given.

**Keywords:**
Empirical Mode Decomposition (EMD),
Hilbert-Huang transform(HHT),
Intrinsic Mode Function(IMF).

##### 3279 A Novel Instantaneous Frequency Computation Approach for Empirical Mode Decomposition

**Authors:**
Liming Zhang

**Abstract:**

**Keywords:**
Instantaneous frequency,
empirical mode decomposition,
intrinsic mode function.

##### 3278 Blind Channel Estimation Based on URV Decomposition Technique for Uplink of MC-CDMA

**Authors:**
Pradya Pornnimitkul,
Suwich Kunaruttanapruk,
Bamrung Tau Sieskul,
Somchai Jitapunkul

**Abstract:**

In this paper, we investigate a blind channel estimation method for Multi-carrier CDMA systems that use a subspace decomposition technique. This technique exploits the orthogonality property between the noise subspace and the received user codes to obtain channel of each user. In the past we used Singular Value Decomposition (SVD) technique but SVD have most computational complexity so in this paper use a new algorithm called URV Decomposition, which serve as an intermediary between the QR decomposition and SVD, replaced in SVD technique to track the noise space of the received data. Because of the URV decomposition has almost the same estimation performance as the SVD, but has less computational complexity.

**Keywords:**
Channel estimation,
MC-CDMA,
SVD,
URV.

##### 3277 Empirical Mode Decomposition Based Multiscale Analysis of Physiological Signal

**Authors:**
Young-Seok Choi

**Abstract:**

**Keywords:**
EEG,
subscale entropy,
Empirical mode
decomposition,
Intrinsic mode function.

##### 3276 Generalized Morphological 3D Shape Decomposition Grayscale Interframe Interpolation Method

**Authors:**
Dragos Nicolae VIZIREANU

**Abstract:**

One of the main image representations in Mathematical Morphology is the 3D Shape Decomposition Representation, useful for Image Compression and Representation,and Pattern Recognition. The 3D Morphological Shape Decomposition representation can be generalized a number of times,to extend the scope of its algebraic characteristics as much as possible. With these generalizations, the Morphological Shape Decomposition 's role to serve as an efficient image decomposition tool is extended to grayscale images.This work follows the above line, and further develops it. Anew evolutionary branch is added to the 3D Morphological Shape Decomposition's development, by the introduction of a 3D Multi Structuring Element Morphological Shape Decomposition, which permits 3D Morphological Shape Decomposition of 3D binary images (grayscale images) into "multiparameter" families of elements. At the beginning, 3D Morphological Shape Decomposition representations are based only on "1 parameter" families of elements for image decomposition.This paper addresses the gray scale inter frame interpolation by means of mathematical morphology. The new interframe interpolation method is based on generalized morphological 3D Shape Decomposition. This article will present the theoretical background of the morphological interframe interpolation, deduce the new representation and show some application examples.Computer simulations could illustrate results.

**Keywords:**
3D shape decomposition representation,
mathematical morphology,
gray scale interframe interpolation

##### 3275 Loss Function Optimization for CNN-Based Fingerprint Anti-Spoofing

**Authors:**
Yehjune Heo

**Abstract:**

As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

**Keywords:**
Anti-spoofing,
CNN,
fingerprint recognition,
loss function,
optimizer.

##### 3274 Catalytical Effect of Fluka 05120 on Methane Decomposition

**Authors:**
Vidyasagar Shilapuram,
Nesrin Ozalp,
Anam Waheed

**Abstract:**

**Keywords:**
Catalysis,
Fluka 05120,
Hydrogen production,
Methane decomposition

##### 3273 Approximate Solution to Non-Linear Schrödinger Equation with Harmonic Oscillator by Elzaki Decomposition Method

**Authors:**
Emad K. Jaradat,
Ala’a Al-Faqih

**Abstract:**

Nonlinear Schrödinger equations are regularly experienced in numerous parts of science and designing. Varieties of analytical methods have been proposed for solving these equations. In this work, we construct an approximate solution for the nonlinear Schrodinger equations, with harmonic oscillator potential, by Elzaki Decomposition Method (EDM). To illustrate the effects of harmonic oscillator on the behavior wave function, nonlinear Schrodinger equation in one and two dimensions is provided. The results show that, it is more perfectly convenient and easy to apply the EDM in one- and two-dimensional Schrodinger equation.

**Keywords:**
Non-linear Schrodinger equation,
Elzaki decomposition method,
harmonic oscillator,
one and two- dimensional Schrodinger equation.

##### 3272 N-Sun Decomposition of Complete Graphs and Complete Bipartite Graphs

**Authors:**
R. Anitha,
R. S. Lekshmi

**Abstract:**

**Keywords:**
Hamilton cycle,
n-sun decomposition,
perfectmatching,
spanning tree.

##### 3271 A Modified Laplace Decomposition Algorithm Solution for Blasius’ Boundary Layer Equation of the Flat Plate in a Uniform Stream

**Authors:**
M. A. Koroma,
Z. Chuangyi,
A. F.,
Kamara,
A. M. H. Conteh

**Abstract:**

In this work, we apply the Modified Laplace decomposition algorithm in finding a numerical solution of Blasius’ boundary layer equation for the flat plate in a uniform stream. The series solution is found by first applying the Laplace transform to the differential equation and then decomposing the nonlinear term by the use of Adomian polynomials. The resulting series, which is exactly the same as that obtained by Weyl 1942a, was expressed as a rational function by the use of diagonal padé approximant.

**Keywords:**
Modified Laplace decomposition algorithm,
Boundary
layer equation,
Padé approximant,
Numerical solution.

##### 3270 Analysis of Catalytic Properties of Ni3Al Thin Foils for the Methanol and Hexane Decomposition

**Authors:**
M. Michalska-Domańska,
P. Jóźwik,
Z. Bojar

**Abstract:**

**Keywords:**
hexane decomposition,
methanol decomposition,
Ni3Al thin foils,
Ni nanoparticles

##### 3269 Ranking - Convex Risk Minimization

**Authors:**
Wojciech Rejchel

**Abstract:**

The problem of ranking (rank regression) has become popular in the machine learning community. This theory relates to problems, in which one has to predict (guess) the order between objects on the basis of vectors describing their observed features. In many ranking algorithms a convex loss function is used instead of the 0-1 loss. It makes these procedures computationally efficient. Hence, convex risk minimizers and their statistical properties are investigated in this paper. Fast rates of convergence are obtained under conditions, that look similarly to the ones from the classification theory. Methods used in this paper come from the theory of U-processes as well as empirical processes.

**Keywords:**
Convex loss function,
empirical risk minimization,
empirical process,
U-process,
boosting,
euclidean family.

##### 3268 A Practical Scheme for Transmission Loss Allocation to Generators and Loads in Restructured Power Systems

**Authors:**
M.R. Ebrahimi,
M. Ehsan

**Abstract:**

This paper presents a practical scheme that can be used for allocating the transmission loss to generators and loads. In this scheme first the share of a generator or load on the current through a branch is determined using Z-bus modified matrix. Then the current components are decomposed and the branch loss allocation is obtained. A motivation of proposed scheme is to improve the results of Z-bus method and to reach more fair allocation. The proposed scheme has been implemented and tested on several networks. To achieve practical and applicable results, the proposed scheme is simulated and compared on the transmission network (400kv) of Khorasan region in Iran and the 14-bus standard IEEE network. The results show that the proposed scheme is comprehensive and fair to allocating the energy losses of a power market to its participants.

**Keywords:**
Transmission Loss,
Loss Allocation,
Z-bus modifiedmatrix,
current Components Decomposition and Restructured PowerSystems

##### 3267 Optimizing Approach for Sifting Process to Solve a Common Type of Empirical Mode Decomposition Mode Mixing

**Authors:**
Saad Al-Baddai,
Karema Al-Subari,
Elmar Lang,
Bernd Ludwig

**Abstract:**

**Keywords:**
Empirical mode decomposition,
mode mixing,
sifting
process,
over-sifting.

##### 3266 N-Sun Decomposition of Complete, Complete Bipartite and Some Harary Graphs

**Authors:**
R. Anitha,
R. S. Lekshmi

**Abstract:**

**Keywords:**
Decomposition,
Hamilton cycle,
n-sun graph,
perfect matching,
spanning tree.

##### 3265 Empirical Mode Decomposition Based Denoising by Customized Thresholding

**Authors:**
Wahiba Mohguen,
Raïs El’hadi Bekka

**Abstract:**

This paper presents a denoising method called EMD-Custom that was based on Empirical Mode Decomposition (EMD) and the modified Customized Thresholding Function (Custom) algorithms. EMD was applied to decompose adaptively a noisy signal into intrinsic mode functions (IMFs). Then, all the noisy IMFs got threshold by applying the presented thresholding function to suppress noise and to improve the signal to noise ratio (SNR). The method was tested on simulated data and real ECG signal, and the results were compared to the EMD-Based signal denoising methods using the soft and hard thresholding. The results showed the superior performance of the proposed EMD-Custom denoising over the traditional approach. The performances were evaluated in terms of SNR in dB, and Mean Square Error (MSE).

**Keywords:**
Customized thresholding,
ECG signal,
EMD,
hard thresholding,
Soft-thresholding.

##### 3264 Beyond Taguchi’s Concept of the Quality Loss Function

**Authors:**
Atul Dev,
Pankaj Jha

**Abstract:**

Dr. Genichi Taguchi looked at quality in a broader term and gave an excellent definition of quality in terms of loss to society. However the scope of this definition is limited to the losses imparted by a poor quality product to the customer only and are considered during the useful life of the product and further in a certain situation this loss can even be zero. In this paper, it has been proposed that the scope of quality of a product shall be further enhanced by considering the losses imparted by a poor quality product to society at large, due to associated environmental and safety related factors, over the complete life cycle of the product. Moreover, though these losses can be further minimized with the use of techno-safety interventions, the net losses to society however can never be made zero. This paper proposes an entirely new approach towards defining product quality and is based on Taguchi’s definition of quality.

**Keywords:**
Existing concept,
goal post philosophy,
life cycle,
proposed concept,
quality loss function.

##### 3263 New Subband Adaptive IIR Filter Based On Polyphase Decomposition

**Authors:**
Young-Seok Choi

**Abstract:**

We present a subband adaptive infinite-impulse response (IIR) filtering method, which is based on a polyphase decomposition of IIR filter. Motivated by the fact that the polyphase structure has benefits in terms of convergence rate and stability, we introduce the polyphase decomposition to subband IIR filtering, i.e., in each subband high order IIR filter is decomposed into polyphase IIR filters with lower order. Computer simulations demonstrate that the proposed method has improved convergence rate over conventional IIR filters.

**Keywords:**
Subband adaptive filter,
IIR filtering. Polyphase decomposition.

##### 3262 Adaptive Fourier Decomposition Based Signal Instantaneous Frequency Computation Approach

**Authors:**
Liming Zhang

**Abstract:**

**Keywords:**
Adaptive Fourier decomposition,
Fourier series,
signal processing,
instantaneous frequency

##### 3261 An Implementation of MacMahon's Partition Analysis in Ordering the Lower Bound of Processing Elements for the Algorithm of LU Decomposition

**Authors:**
Halil Snopce,
Ilir Spahiu,
Lavdrim Elmazi

**Abstract:**

A lot of Scientific and Engineering problems require the solution of large systems of linear equations of the form bAx in an effective manner. LU-Decomposition offers good choices for solving this problem. Our approach is to find the lower bound of processing elements needed for this purpose. Here is used the so called Omega calculus, as a computational method for solving problems via their corresponding Diophantine relation. From the corresponding algorithm is formed a system of linear diophantine equalities using the domain of computation which is given by the set of lattice points inside the polyhedron. Then is run the Mathematica program DiophantineGF.m. This program calculates the generating function from which is possible to find the number of solutions to the system of Diophantine equalities, which in fact gives the lower bound for the number of processors needed for the corresponding algorithm. There is given a mathematical explanation of the problem as well. Keywordsgenerating function, lattice points in polyhedron, lower bound of processor elements, system of Diophantine equationsand : calculus.

**Keywords:**
generating function,
lattice points in polyhedron,
lower bound of processor elements,
system of Diophantine equations and calculus.

##### 3260 Blind Identification and Equalization of CDMA Signals Using the Levenvberg-Marquardt Algorithm

**Authors:**
Mohammed Boutalline,
Imad Badi,
Belaid Bouikhalene,
Said Safi

**Abstract:**

In this paper we describe the Levenvberg-Marquardt (LM) algorithm for identification and equalization of CDMA signals received by an antenna array in communication channels. The synthesis explains the digital separation and equalization of signals after propagation through multipath generating intersymbol interference (ISI). Exploiting discrete data transmitted and three diversities induced at the reception, the problem can be composed by the Block Component Decomposition (BCD) of a tensor of order 3 which is a new tensor decomposition generalizing the PARAFAC decomposition. We optimize the BCD decomposition by Levenvberg-Marquardt method gives encouraging results compared to classical alternating least squares algorithm (ALS). In the equalization part, we use the Minimum Mean Square Error (MMSE) to perform the presented method. The simulation results using the LM algorithm are important.

**Keywords:**
Identification and equalization,
communication
channel,
Levenvberg-Marquardt,
tensor decomposition

##### 3259 A Reconfigurable Processing Element for Cholesky Decomposition and Matrix Inversion

**Authors:**
Aki Happonen,
Adrian Burian,
Erwin Hemming

**Abstract:**

**Keywords:**
Cholesky Decomposition,
Fixed-point,
Matrix
inversion,
Reconfigurable processing.

##### 3258 The Utility of Wavelet Transform in Surface Electromyography Feature Extraction -A Comparative Study of Different Mother Wavelets

**Authors:**
Farzaneh Akhavan Mahdavi,
Siti Anom Ahmad,
Mohd Hamiruce Marhaban,
Mohammad-R. Akbarzadeh-T

**Abstract:**

Electromyography (EMG) signal processing has been investigated remarkably regarding various applications such as in rehabilitation systems. Specifically, wavelet transform has served as a powerful technique to scrutinize EMG signals since wavelet transform is consistent with the nature of EMG as a non-stationary signal. In this paper, the efficiency of wavelet transform in surface EMG feature extraction is investigated from four levels of wavelet decomposition and a comparative study between different mother wavelets had been done. To recognize the best function and level of wavelet analysis, two evaluation criteria, scatter plot and RES index are recruited. Hereupon, four wavelet families, namely, Daubechies, Coiflets, Symlets and Biorthogonal are studied in wavelet decomposition stage. Consequently, the results show that only features from first and second level of wavelet decomposition yields good performance and some functions of various wavelet families can lead to an improvement in separability class of different hand movements.

**Keywords:**
Electromyography signal,
feature extraction,
wavelettransform,
means absolute value.

##### 3257 A Decomposition Method for the Bipartite Separability of Bell Diagonal States

**Authors:**
Wei-Chih Su,
Kuan-Peng Chen,
Ming-Chung Tsai,
Zheng-Yao Su

**Abstract:**

**Keywords:**
decomposition,
bipartite separability,
Bell diagonal states.

##### 3256 Algebraic Riccati Matrix Equation for Eigen- Decomposition of Special Structured Matrices; Applications in Structural Mechanics

**Authors:**
Mahdi Nouri

**Abstract:**

In this paper Algebraic Riccati matrix equation is used for Eigen-decomposition of special structured matrices. This is achieved by similarity transformation and then using algebraic riccati matrix equation to triangulation of matrices. The process is decomposition of matrices into small and specially structured submatrices with low dimensions for fast and easy finding of Eigenpairs. Numerical and structural examples included showing the efficiency of present method.

**Keywords:**
Riccati,
matrix equation,
eigenvalue problem,
symmetric,
bisymmetric,
persymmetric,
decomposition,
canonical
forms,
Graphs theory,
adjacency and Laplacian matrices.