Search results for: optimization problems in signal processing.
6109 Transmission Lines Loading Enhancement Using ADPSO Approach
Authors: M. Mahdavi, H. Monsef, A. Bagheri
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Discrete particle swarm optimization (DPSO) is a powerful stochastic evolutionary algorithm that is used to solve the large-scale, discrete and nonlinear optimization problems. However, it has been observed that standard DPSO algorithm has premature convergence when solving a complex optimization problem like transmission expansion planning (TEP). To resolve this problem an advanced discrete particle swarm optimization (ADPSO) is proposed in this paper. The simulation result shows that optimization of lines loading in transmission expansion planning with ADPSO is better than DPSO from precision view point.Keywords: ADPSO, TEP problem, Lines loading optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16086108 Oil Debris Signal Detection Based on Integral Transform and Empirical Mode Decomposition
Authors: Chuan Li, Ming Liang
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Oil debris signal generated from the inductive oil debris monitor (ODM) is useful information for machine condition monitoring but is often spoiled by background noise. To improve the reliability in machine condition monitoring, the high-fidelity signal has to be recovered from the noisy raw data. Considering that the noise components with large amplitude often have higher frequency than that of the oil debris signal, the integral transform is proposed to enhance the detectability of the oil debris signal. To cancel out the baseline wander resulting from the integral transform, the empirical mode decomposition (EMD) method is employed to identify the trend components. An optimal reconstruction strategy including both de-trending and de-noising is presented to detect the oil debris signal with less distortion. The proposed approach is applied to detect the oil debris signal in the raw data collected from an experimental setup. The result demonstrates that this approach is able to detect the weak oil debris signal with acceptable distortion from noisy raw data.Keywords: Integral transform, empirical mode decomposition, oil debris, signal processing, detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17096107 Investigation on Novel Based Metaheuristic Algorithms for Combinatorial Optimization Problems in Ad Hoc Networks
Authors: C. Rajan, N. Shanthi, C. Rasi Priya, K. Geetha
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Routing in MANET is extremely challenging because of MANETs dynamic features, its limited bandwidth, frequent topology changes caused by node mobility and power energy consumption. In order to efficiently transmit data to destinations, the applicable routing algorithms must be implemented in mobile ad-hoc networks. Thus we can increase the efficiency of the routing by satisfying the Quality of Service (QoS) parameters by developing routing algorithms for MANETs. The algorithms that are inspired by the principles of natural biological evolution and distributed collective behavior of social colonies have shown excellence in dealing with complex optimization problems and are becoming more popular. This paper presents a survey on few meta-heuristic algorithms and naturally-inspired algorithms.
Keywords: Ant colony optimization, genetic algorithm, Naturally-inspired algorithms and particle swarm optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26926106 Big Bang – Big Crunch Optimization Method in Optimum Design of Complex Composite Laminates
Authors: Pavel Y. Tabakov
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An accurate optimal design of laminated composite structures may present considerable difficulties due to the complexity and multi-modality of the functional design space. The Big Bang – Big Crunch (BB-BC) optimization method is a relatively new technique and has already proved to be a valuable tool for structural optimization. In the present study the exceptional efficiency of the method is demonstrated by an example of the lay-up optimization of multilayered anisotropic cylinders based on a three-dimensional elasticity solution. It is shown that, due to its simplicity and speed, the BB-BC is much more efficient for this class of problems when compared to the genetic algorithms.Keywords: Big Bang – Big Crunch method, optimization, composite laminates, pressure vessel.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22506105 Investigation on Novel Based Naturally-Inspired Swarm Intelligence Algorithms for Optimization Problems in Mobile Ad Hoc Networks
Authors: C. Rajan, K. Geetha, C. Rasi Priya, S. Geetha
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Nature is the immense gifted source for solving complex problems. It always helps to find the optimal solution to solve the problem. Mobile Ad Hoc NETwork (MANET) is a wide research area of networks which has set of independent nodes. The characteristics involved in MANET’s are Dynamic, does not depend on any fixed infrastructure or centralized networks, High mobility. The Bio-Inspired algorithms are mimics the nature for solving optimization problems opening a new era in MANET. The typical Swarm Intelligence (SI) algorithms are Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Modified Termite Algorithm, Bat Algorithm (BA), Wolf Search Algorithm (WSA) and so on. This work mainly concentrated on nature of MANET and behavior of nodes. Also it analyses various performance metrics such as throughput, QoS and End-to-End delay etc.
Keywords: Ant Colony Algorithm, Artificial Bee Colony algorithm, Bio-Inspired algorithm, Modified Termite Algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24616104 Selecting Materialized Views Using Two-Phase Optimization with Multiple View Processing Plan
Authors: Jiratta Phuboon-ob, Raweewan Auepanwiriyakul
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A data warehouse (DW) is a system which has value and role for decision-making by querying. Queries to DW are critical regarding to their complexity and length. They often access millions of tuples, and involve joins between relations and aggregations. Materialized views are able to provide the better performance for DW queries. However, these views have maintenance cost, so materialization of all views is not possible. An important challenge of DW environment is materialized view selection because we have to realize the trade-off between performance and view maintenance cost. Therefore, in this paper, we introduce a new approach aimed at solve this challenge based on Two-Phase Optimization (2PO), which is a combination of Simulated Annealing (SA) and Iterative Improvement (II), with the use of Multiple View Processing Plan (MVPP). Our experiments show that our method provides a further improvement in term of query processing cost and view maintenance cost.Keywords: Data warehouse, materialized views, view selectionproblem, two-phase optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16516103 Complex-Valued Neural Network in Signal Processing: A Study on the Effectiveness of Complex Valued Generalized Mean Neuron Model
Authors: Anupama Pande, Ashok Kumar Thakur, Swapnoneel Roy
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A complex valued neural network is a neural network which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in signal processing. In Neural networks, generalized mean neuron model (GMN) is often discussed and studied. The GMN includes a new aggregation function based on the concept of generalized mean of all the inputs to the neuron. This paper aims to present exhaustive results of using Generalized Mean Neuron model in a complex-valued neural network model that uses the back-propagation algorithm (called -Complex-BP-) for learning. Our experiments results demonstrate the effectiveness of a Generalized Mean Neuron Model in a complex plane for signal processing over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error required on a Generalized Mean neural network model. Some inherent properties of this complex back propagation algorithm are also studied and discussed.Keywords: Complex valued neural network, Generalized Meanneuron model, Signal processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17206102 Feature Subset Selection Using Ant Colony Optimization
Authors: Ahmed Al-Ani
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Feature selection is an important step in many pattern classification problems. It is applied to select a subset of features, from a much larger set, such that the selected subset is sufficient to perform the classification task. Due to its importance, the problem of feature selection has been investigated by many researchers. In this paper, a novel feature subset search procedure that utilizes the Ant Colony Optimization (ACO) is presented. The ACO is a metaheuristic inspired by the behavior of real ants in their search for the shortest paths to food sources. It looks for optimal solutions by considering both local heuristics and previous knowledge. When applied to two different classification problems, the proposed algorithm achieved very promising results.Keywords: Ant Colony Optimization, ant systems, feature selection, pattern recognition.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15846101 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 14046100 An Optimization of Orbital Transfer for Spacecrafts with Finite-thrust Based on Legendre Pseudospectral Method
Authors: Yanan Yang, Zhigang Wang, Xiang Chen
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This paper presents the use of Legendre pseudospectral method for the optimization of finite-thrust orbital transfer for spacecrafts. In order to get an accurate solution, the System-s dynamics equations were normalized through a dimensionless method. The Legendre pseudospectral method is based on interpolating functions on Legendre-Gauss-Lobatto (LGL) quadrature nodes. This is used to transform the optimal control problem into a constrained parameter optimization problem. The developed novel optimization algorithm can be used to solve similar optimization problems of spacecraft finite-thrust orbital transfer. The results of a numerical simulation verified the validity of the proposed optimization method. The simulation results reveal that pseudospectral optimization method is a promising method for real-time trajectory optimization and provides good accuracy and fast convergence.Keywords: Finite-thrust, Orbital transfer, Legendre pseudospectral method
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17926099 Wavelet-Based ECG Signal Analysis and Classification
Authors: Madina Hamiane, May Hashim Ali
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This paper presents the processing and analysis of ECG signals. The study is based on wavelet transform and uses exclusively the MATLAB environment. This study includes removing Baseline wander and further de-noising through wavelet transform and metrics such as signal-to noise ratio (SNR), Peak signal-to-noise ratio (PSNR) and the mean squared error (MSE) are used to assess the efficiency of the de-noising techniques. Feature extraction is subsequently performed whereby signal features such as heart rate, rise and fall levels are extracted and the QRS complex was detected which helped in classifying the ECG signal. The classification is the last step in the analysis of the ECG signals and it is shown that these are successfully classified as Normal rhythm or Abnormal rhythm. The final result proved the adequacy of using wavelet transform for the analysis of ECG signals.
Keywords: ECG Signal, QRS detection, thresholding, wavelet decomposition, feature extraction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12536098 A Query Optimization Strategy for Autonomous Distributed Database Systems
Authors: Dina K. Badawy, Dina M. Ibrahim, Alsayed A. Sallam
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Distributed database is a collection of logically related databases that cooperate in a transparent manner. Query processing uses a communication network for transmitting data between sites. It refers to one of the challenges in the database world. The development of sophisticated query optimization technology is the reason for the commercial success of database systems, which complexity and cost increase with increasing number of relations in the query. Mariposa, query trading and query trading with processing task-trading strategies developed for autonomous distributed database systems, but they cause high optimization cost because of involvement of all nodes in generating an optimal plan. In this paper, we proposed a modification on the autonomous strategy K-QTPT that make the seller’s nodes with the lowest cost have gradually high priorities to reduce the optimization time. We implement our proposed strategy and present the results and analysis based on those results.
Keywords: Autonomous strategies, distributed database systems, high priority, query optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10476097 Early Diagnosis of Alzheimer's Disease Using a Combination of Images Processing and Brain Signals
Authors: E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari
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Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%.
Keywords: Alzheimer's disease, image and signal processing, medial temporal atrophy, LOO Cycle.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20286096 Relation between Roots and Tangent Lines of Function in Fractional Dimensions: A Method for Optimization Problems
Authors: Ali Dorostkar
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In this paper, a basic schematic of fractional dimensional optimization problem is presented. As will be shown, a method is performed based on a relation between roots and tangent lines of function in fractional dimensions for an arbitrary initial point. It is shown that for each polynomial function with order N at least N tangent lines must be existed in fractional dimensions of 0 < α < N+1 which pass exactly through the all roots of the proposed function. Geometrical analysis of tangent lines in fractional dimensions is also presented to clarify more intuitively the proposed method. Results show that with an appropriate selection of fractional dimensions, we can directly find the roots. Method is presented for giving a different direction of optimization problems by the use of fractional dimensions.
Keywords: Tangent line, fractional dimension, root, optimization problem.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5536095 Analysis of Electrocardiograph (ECG) Signal for the Detection of Abnormalities Using MATLAB
Authors: Durgesh Kumar Ojha, Monica Subashini
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The proposed method is to study and analyze Electrocardiograph (ECG) waveform to detect abnormalities present with reference to P, Q, R and S peaks. The first phase includes the acquisition of real time ECG data. In the next phase, generation of signals followed by pre-processing. Thirdly, the procured ECG signal is subjected to feature extraction. The extracted features detect abnormal peaks present in the waveform Thus the normal and abnormal ECG signal could be differentiated based on the features extracted. The work is implemented in the most familiar multipurpose tool, MATLAB. This software efficiently uses algorithms and techniques for detection of any abnormalities present in the ECG signal. Proper utilization of MATLAB functions (both built-in and user defined) can lead us to work with ECG signals for processing and analysis in real time applications. The simulation would help in improving the accuracy and the hardware could be built conveniently.
Keywords: ECG Waveform, Peak Detection, Arrhythmia, Matlab.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 119936094 Traffic Signal Coordinated Control Optimization: A Case Study
Authors: Pengdi Diao, Zhuo Wang, Zundong Zhang, Hua Cheng
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In the urban traffic network, the intersections are the “bottleneck point" of road network capacity. And the arterials are the main body in road network and the key factor which guarantees the normal operation of the city-s social and economic activities. The rapid increase in vehicles leads to seriously traffic jam and cause the increment of vehicles- delay. Most cities of our country are traditional single control system, which cannot meet the need for the city traffic any longer. In this paper, Synchro6.0 as a platform to minimize the intersection delay, optimizesingle signal cycle and split for Zhonghua Street in Handan City. Meanwhile, linear control system uses to optimize the phase for the t arterial road in this system. Comparing before and after use the control, capacities and service levels of this road and the adjacent road have improved significantly.Keywords: linear control system; delay mode; signal optimization; synchro6.0 simulation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21116093 New Approach in Diagnostics Method for Milling Process using Envelope Analysis
Authors: C. Bisu, M. Zapciu, A. Gérard
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This paper proposes a method to vibration analysis in order to on-line monitoring and predictive maintenance during the milling process. Adapting envelope method to diagnostics and the analysis for milling tool materials is an important contribution to the qualitative and quantitative characterization of milling capacity and a step by modeling the three-dimensional cutting process. An experimental protocol was designed and developed for the acquisition, processing and analyzing three-dimensional signal. The vibration envelope analysis is proposed to detect the cutting capacity of the tool with the optimization application of cutting parameters. The research is focused on Hilbert transform optimization to evaluate the dynamic behavior of the machine/ tool/workpiece.Keywords: diagnostics, envelope, milling, vibration
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19276092 The Whale Optimization Algorithm and Its Implementation in MATLAB
Authors: S. Adhirai, R. P. Mahapatra, Paramjit Singh
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Optimization is an important tool in making decisions and in analysing physical systems. In mathematical terms, an optimization problem is the problem of finding the best solution from among the set of all feasible solutions. The paper discusses the Whale Optimization Algorithm (WOA), and its applications in different fields. The algorithm is tested using MATLAB because of its unique and powerful features. The benchmark functions used in WOA algorithm are grouped as: unimodal (F1-F7), multimodal (F8-F13), and fixed-dimension multimodal (F14-F23). Out of these benchmark functions, we show the experimental results for F7, F11, and F19 for different number of iterations. The search space and objective space for the selected function are drawn, and finally, the best solution as well as the best optimal value of the objective function found by WOA is presented. The algorithmic results demonstrate that the WOA performs better than the state-of-the-art meta-heuristic and conventional algorithms.
Keywords: Optimization, optimal value, objective function, optimization problems, meta-heuristic optimization algorithms, Whale Optimization Algorithm, Implementation, MATLAB.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28806091 Using Pattern Search Methods for Minimizing Clustering Problems
Authors: Parvaneh Shabanzadeh, Malik Hj Abu Hassan, Leong Wah June, Maryam Mohagheghtabar
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Clustering is one of an interesting data mining topics that can be applied in many fields. Recently, the problem of cluster analysis is formulated as a problem of nonsmooth, nonconvex optimization, and an algorithm for solving the cluster analysis problem based on nonsmooth optimization techniques is developed. This optimization problem has a number of characteristics that make it challenging: it has many local minimum, the optimization variables can be either continuous or categorical, and there are no exact analytical derivatives. In this study we show how to apply a particular class of optimization methods known as pattern search methods to address these challenges. These methods do not explicitly use derivatives, an important feature that has not been addressed in previous studies. Results of numerical experiments are presented which demonstrate the effectiveness of the proposed method.Keywords: Clustering functions, Non-smooth Optimization, Nonconvex Optimization, Pattern Search Method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16326090 Solution of Optimal Reactive Power Flow using Biogeography-Based Optimization
Authors: Aniruddha Bhattacharya, Pranab Kumar Chattopadhyay
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Optimal reactive power flow is an optimization problem with one or more objective of minimizing the active power losses for fixed generation schedule. The control variables are generator bus voltages, transformer tap settings and reactive power output of the compensating devices placed on different bus bars. Biogeography- Based Optimization (BBO) technique has been applied to solve different kinds of optimal reactive power flow problems subject to operational constraints like power balance constraint, line flow and bus voltages limits etc. BBO searches for the global optimum mainly through two steps: Migration and Mutation. In the present work, BBO has been applied to solve the optimal reactive power flow problems on IEEE 30-bus and standard IEEE 57-bus power systems for minimization of active power loss. The superiority of the proposed method has been demonstrated. Considering the quality of the solution obtained, the proposed method seems to be a promising one for solving these problems.Keywords: Active Power Loss, Biogeography-Based Optimization, Migration, Mutation, Optimal Reactive Power Flow.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 42646089 Motor Imagery Signal Classification for a Four State Brain Machine Interface
Authors: Hema C. R., Paulraj M. P., S. Yaacob, A. H. Adom, R. Nagarajan
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Motor imagery classification provides an important basis for designing Brain Machine Interfaces [BMI]. A BMI captures and decodes brain EEG signals and transforms human thought into actions. The ability of an individual to control his EEG through imaginary mental tasks enables him to control devices through the BMI. This paper presents a method to design a four state BMI using EEG signals recorded from the C3 and C4 locations. Principle features extracted through principle component analysis of the segmented EEG are analyzed using two novel classification algorithms using Elman recurrent neural network and functional link neural network. Performance of both classifiers is evaluated using a particle swarm optimization training algorithm; results are also compared with the conventional back propagation training algorithm. EEG motor imagery recorded from two subjects is used in the offline analysis. From overall classification performance it is observed that the BP algorithm has higher average classification of 93.5%, while the PSO algorithm has better training time and maximum classification. The proposed methods promises to provide a useful alternative general procedure for motor imagery classification
Keywords: Motor Imagery, Brain Machine Interfaces, Neural Networks, Particle Swarm Optimization, EEG signal processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24426088 Detection of Clipped Fragments in Speech Signals
Authors: Sergei Aleinik, Yuri Matveev
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In this paper a novel method for the detection of clipping in speech signals is described. It is shown that the new method has better performance than known clipping detection methods, is easy to implement, and is robust to changes in signal amplitude, size of data, etc. Statistical simulation results are presented.
Keywords: Clipping, clipped signal, speech signal processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26616087 Induction Motor Design with Limited Harmonic Currents Using Particle Swarm Optimization
Authors: C. Thanga Raj, S. P. Srivastava, Pramod Agarwal
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This paper presents an optimal design of poly-phase induction motor using Quadratic Interpolation based Particle Swarm Optimization (QI-PSO). The optimization algorithm considers the efficiency, starting torque and temperature rise as objective function (which are considered separately) and ten performance related items including harmonic current as constraints. The QI-PSO algorithm was implemented on a test motor and the results are compared with the Simulated Annealing (SA) technique, Standard Particle Swarm Optimization (SPSO), and normal design. Some benchmark problems are used for validating QI-PSO. From the test results QI-PSO gave better results and more suitable to motor-s design optimization. Cµ code is used for implementing entire algorithms.
Keywords: Design, harmonics, induction motor, particle swarm optimization
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17786086 Subjective Assessment about Super Resolution Image Resolution
Authors: Seiichi Gohshi, Hiroyuki Sekiguchi, Yoshiyasu Shimizu, Takeshi Ikenaga
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Super resolution (SR) technologies are now being applied to video to improve resolution. Some TV sets are now equipped with SR functions. However, it is not known if super resolution image reconstruction (SRR) for TV really works or not. Super resolution with non-linear signal processing (SRNL) has recently been proposed. SRR and SRNL are the only methods for processing video signals in real time. The results from subjective assessments of SSR and SRNL are described in this paper. SRR video was produced in simulations with quarter precision motion vectors and 100 iterations. These are ideal conditions for SRR. We found that the image quality of SRNL is better than that of SRR even though SRR was processed under ideal conditions.Keywords: Super Resolution Image Reconstruction, Super Resolution with Non-Linear Signal Processing, Subjective Assessment, Image Quality
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16876085 Sensitivity Analysis during the Optimization Process Using Genetic Algorithms
Authors: M. A. Rubio, A. Urquia
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Genetic algorithms (GA) are applied to the solution of high-dimensional optimization problems. Additionally, sensitivity analysis (SA) is usually carried out to determine the effect on optimal solutions of changes in parameter values of the objective function. These two analyses (i.e., optimization and sensitivity analysis) are computationally intensive when applied to high-dimensional functions. The approach presented in this paper consists in performing the SA during the GA execution, by statistically analyzing the data obtained of running the GA. The advantage is that in this case SA does not involve making additional evaluations of the objective function and, consequently, this proposed approach requires less computational effort than conducting optimization and SA in two consecutive steps.Keywords: Optimization, sensitivity, genetic algorithms, model calibration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14666084 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 18316083 Practical Guidelines and Examples for the Users of the TMS320C6713 DSK
Authors: Abdullah A Wardak
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This paper describes how the correct endian mode of the TMS320C6713 DSK board can be identified. It also explains how the TMS320C6713 DSK board can be used in the little endian and in the big endian modes for assembly language programming in particular and for signal processing in general. Similarly, it discusses how crucially important it is for a user of the TMS320C6713 DSK board to identify the mode of operation and then use it correctly during the development stages of the assembly language programming; otherwise, it will cause unnecessary confusion and erroneous results as far as storing data into the memory and loading data from the memory is concerned. Furthermore, it highlights and strongly recommends to the users of the TMS320C6713 DSK board to be aware of the availability and importance of various display options in the Code Composer Studio (CCS) for correctly interpreting and displaying the desired data in the memory. The information presented in this paper will be of great importance and interest to those practitioners and developers who wants to use the TMS320C6713 DSK board for assembly language programming as well as input-output signal processing manipulations. Finally, examples that clearly illustrate the concept are presented.Keywords: Assembly language programming, big endian mode, little endian mode, signal processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27766082 Investigating Simple Multipath Compensation for Frequency Modulated Signals at Lower Frequencies
Authors: Lusungu Ndovi
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Radio propagation from point-to-point is affected by the physical channel in many ways. A signal arriving at a destination travels through a number of different paths which are referred to as multi-paths. Research in this area of wireless communications has progressed well over the years with the research taking different angles of focus. By this is meant that some researchers focus on ways of reducing or eluding Multipath effects whilst others focus on ways of mitigating the effects of Multipath through compensation schemes. Baseband processing is seen as one field of signal processing that is cardinal to the advancement of software defined radio technology. This has led to wide research into the carrying out certain algorithms at baseband. This paper considers compensating for Multipath for Frequency Modulated signals. The compensation process is carried out at Radio frequency (RF) and at Quadrature baseband (QBB) and the results are compared. Simulations are carried out using MatLab so as to show the benefits of working at lower QBB frequencies than at RF.Keywords: Quadrature baseband, Radio frequency, MultipathCompensation, Frequency modulation, Signal Processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16446081 A Novel Method for Blood Glucose Measurement by Noninvasive Technique Using Laser
Authors: V.Ashok, A.Nirmalkumar, N.Jeyashanthi
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A method and apparatus for noninvasive measurement of blood glucose concentration based on transilluminated laser beam via the Index Finger has been reported in this paper. This method depends on atomic gas (He-Ne) laser operating at 632.8nm wavelength. During measurement, the index finger is inserted into the glucose sensing unit, the transilluminated optical signal is converted into an electrical signal, compared with the reference electrical signal, and the obtained difference signal is processed by signal processing unit which presents the results in the form of blood glucose concentration. This method would enable the monitoring blood glucose level of the diabetic patient continuously, safely and noninvasively.Keywords: Anisotropy factor, Blood glucose, Diabetes Mellitus, Noninvasive method, Photo detectors.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 32836080 Evolutionary Search Techniques to Solve Set Covering Problems
Authors: Darwin Gouwanda, S. G. Ponnambalam
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Set covering problem is a classical problem in computer science and complexity theory. It has many applications, such as airline crew scheduling problem, facilities location problem, vehicle routing, assignment problem, etc. In this paper, three different techniques are applied to solve set covering problem. Firstly, a mathematical model of set covering problem is introduced and solved by using optimization solver, LINGO. Secondly, the Genetic Algorithm Toolbox available in MATLAB is used to solve set covering problem. And lastly, an ant colony optimization method is programmed in MATLAB programming language. Results obtained from these methods are presented in tables. In order to assess the performance of the techniques used in this project, the benchmark problems available in open literature are used.Keywords: Set covering problem, genetic algorithm, ant colony optimization, LINGO.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3614