MATLAB Software Environment Research Articles

Simulation of а car parameters impact on the process of its acceleration

Goal. The purpose of the work is mathematical modeling of Daewoo Lanos passenger car acceleration dynamics. Methodology. The mathematical model is based on the methodology of E.A. Chudakov and N.A.Yakovlev. According to this method, the main factor that determines the current value of vehicle acceleration at an elementary speed section is the dynamic factor. This factor depends on the traction force, the air resistance force and the weight of the vehicle. The paper proposes formulas for determining the dynamic factor and parameters of vehicle acceleration at an elementary speed section, where gear shift takes place. The model is implemented in the MATLAB software environment. The software product allows to determine the parameters of the car during acceleration to the maximum speed when the engine is running at the external speed characteristic modes. Results Based on the results of mathematical modeling for the Daewoo Lanos car, the loads arising in the drive of the car were analyzed. It is shown that the tractive effort is mainly spent on overcoming the inertial forces, which at the beginning of the movement exceed the resistance forces of the road and air by more than 50 times. With an increase in the vehicle speed, the inertia force decreases and at a speed of 100 km / h it is only twice the other load components. It is shown that with the accepted initial data, the Daewoo Lanos car accelerates to 100 km/h in 17.7 s, which corresponds to the experimental data. The influence of the mass of the car, the rated power of the engine, the mode and time of gear shifting, the radius of the wheels, the height of the car, the coefficient of aerodynamic drag on the dynamics of acceleration of the car is analyzed. It was revealed that the vehicle weight and the nominal power of the engine affect the dynamics of acceleration from 0 to 100 km/h to the greatest extent. The influence of other parameters in the indicated speed range is not somewhat significant. The explanation of the obtained results is given. Practical value. The mathematical model presented in the work allows to determine the parameters of the engine and the car during acceleration, take into account the influence of the design and adjusting parameters of the engine and the car on these indicators, and carry out optimization studies.

Modelling of bivariate meteorological drought analysis in Lake Urmia Basin using Archimedean copula functions

AbstractThe Urmia Lake Basin as the world's second largest salt lake has experienced severe drought during recent years. The purpose of this study is to analyse the bivariate characteristics of drought (i.e., duration and severity) using two indices including SPI (standard precipitation index) and SPImod (modified SPI) associated with copula functions. For this purpose, rainfall data of six stations were used for the period of 1971–2017. At first, the characteristics of drought were extracted using the two indices. Then, through coding in the MATLAB software environment, eight families of Archimedean copula functions were applied. The simultaneous return period and conditional and Kendall returns were also investigated. The result showed that the Joe copula function was the best predictor for the analysis of both intensity and duration of drought for the study area. The correlation coefficients of Spearman, linear correlation and Tau Kendall computed for the SPI of stations were >0.65, >0.72 and >0.48, respectively, while all of them were significant. At a given critical probability level, t, the value of the Kendall return period was much greater than the standard return period, so that this difference increased with increasing t value. The results obtained from the time series of indices indicated that at least 40% of the months were dry, and the severity of droughts in the Urmia station was much higher than other stations during the studied period. Moreover, SPImod to a large extent eliminates the disadvantages of conventional SPI and takes into account seasonal variations of precipitation in the calculation of SPI.

A Novel Hybrid Algorithm of Max-Min Ant System with Quadratic Programming to Solve the Unit Commitment Problem

In this paper, we propose a novel hybrid algorithm based on MAX-MIN Ant System version of ant colony optimization coupled with quadratic programming (MMAS-QP). Quadratic programming is used to optimize the Economic Dispatching process and MMAS for planning the switching schedule of a set of production units. The algorithm is implemented in MATLAB software environment for two systems, one is 4 generating units running for 8 hours, and the other is 10 generating units running for 24 hours. The impact of heuristic parameters on the behavior of the algorithm is highlighted through the parameters setting. Results obtained shows improved solution compared to several methods such as Modified Ant Colony Optimization (MACO), particle Swarm Optimization combined with Lagrange Relaxation (PSO-LR), Swarm and Evolutionary Computation (SEC), Particle Swarm Optimization combined with Genetic Algorithm (PSO-GA). The proposed method improves sufficiently the quality of the solution as well as the execution time.

Intelligent Control System Architecture for Phosphorus Production from Apatite-Nepheline Ore Waste

This paper proposes multilevel architecture for an intelligent control system for the complex chemical energy technological process of yellow phosphorus production from apatite-nepheline ore processing waste. The research revealed that, when controlling this process, one has to deal with large amounts of multiformat and polymodal information, and control goals differ at different levels not only in effectiveness criteria, but also in the structuredness of the level problems. On this basis, it is proposed that intelligent methods be used for the implementation of information processes and control goals at individual levels and the whole system. The artificial intelligence methods underlying the informational model of a control system offer solutions to problems of analyzing control processes at different hierarchy levels, namely the initial level of sensing devices, the levels of programmable logic controllers, dispatching of control and production processes, enterprise management and strategic planning. Besides, the intelligent control system architecture includes analytical and simulation models of processes occurring in the multistage procedure of ore waste processing by a plant consisting of a granulating machine, a conveyor-type multichambercalcining machine, and an ore thermal furnace. The architecture of information support for the control system comprises a knowledge-based inference block intended for implementing the self-refinement of neural network and simulation models. Fuzzy logic methods are proposed for constructing this block. The paper considers the deployment of control algorithms for a phosphorus production system using the Matlab software environment on the basis of a modern complex system development paradigm known as the model-oriented design concept.

Railroad Turnout Wear Diagnostics.

The article presents a few issues related to the technical condition of a railway turnout, an important element of the railway network where about 90% of railway accidents occur. In the first part of the article, the results of railway turnout wear are presented. A comparison of normal forces (in wheel–rail contact) in vehicle traffic on straight track without a turnout and normal forces occurring when a rail vehicle passes a turnout is presented. Then, turnout wear processes for selected speeds are presented. In the next part of the paper, the possibilities of using a vision system are presented, which, in combination with tools for image processing analysis, makes it possible to detect wear and distances between the key elements of a railway turnout. The main idea of the proposed online diagnostic system solution is to use the analysis of received images (photos) with the help of a vision system. The basic problem to be solved in the proposed system was to develop algorithms responsible for generating wear areas from high-resolution images. The algorithms created within the work were implemented and tested in the MATLAB software environment. The presented method is an original procedure for diagnosing turnout elements for each time instant. The proposed system is compatible with railway traffic control systems.

Modeling of welding arc power supply diagrams in Matlab / Simulink

Purpose. Creation of virtual blocks and simulation laboratory stands for the study and comprehensive research of the dynamic properties of welding power supplies. Methodology. Review of literary sources on the subject, simulation modeling of electromagnetic processes in the MATLAB software environment, comparative analysis of obtained and available data. Findings. The comparative analysis of means of modeling of power sources of a welding arc is executed. One of the main parameters by which the environments were compared is functionality. Among the considered simulators, Simulink of the MATLAB software environment is the most effective one in the considered systems modeling. Using special features, its user can not only simulate, but also analyze the operation of the over time installation. Mathematical and functional models of welding arc power supplies were built using SimPowerSystems elements and blocks from the Simulink library with the involvement of the MATLAB system itself, which significantly expands the possibilities for such systems modeling. Mathematization of certain processes to some extent shows the level of reliability of the results and the degree of their scientific development. The developed models act as a laboratory, which allows you to set and explore any modes and characteristics. Numerical experiments and comparative analysis of numerical and field experiments are given. Experimental verification of the obtained results on specific examples showed the relevance of the problem and the correctness of its solution. Further research is related to the expansion of the range of simulated power sources of the electric arc, a comprehensive study of their dynamic properties and basic characteristics, experimental verification of the developed models, as well as comparative analysis and development of recommendations for model improvement. Originality. The method of circuit modeling of general-purpose electrical and electronic circuits was further developed by extending it to a new class of objects - the power supply system of electrical installations. Practical value. Construction of mathematical and functional models of complex systems with the involvement of MATLAB allows to take into account their main features, significantly expands the possibilities for modeling, study and research of power supplies. Based on the proposed approach, simulation laboratory stands of specific power supplies were developed and built, which allow to set and study any modes and characteristics.

An energy-aware approach for resources allocating in the internet of things using a forest optimization algorithm

PurposeInternet of things (IoT) is essential in technical, social and economic domains, but there are many challenges that researchers are continuously trying to solve. Traditional resource allocation methods in IoT focused on the optimal resource selection process, but the energy consumption for allocating resources is not considered sufficiently. This paper aims to propose a resource allocation technique aiming at energy and delay reduction in resource allocation. Because of the non-deterministic polynomial-time hard nature of the resource allocation issue and the forest optimization algorithm’s success in complex problems, the authors used this algorithm to allocate resources in IoT.Design/methodology/approachFor the vast majority of IoT applications, energy-efficient communications, sustainable energy supply and reduction of latency have been major goals in resource allocation, making operating systems and applications more efficient. One of the most critical challenges in this field is efficient resource allocation. This paper has provided a new technique to solve the mentioned problem using the forest optimization algorithm. To simulate and analyze the proposed technique, the MATLAB software environment has been used. The results obtained from implementing the proposed method have been compared to the particle swarm optimization (PSO), genetic algorithm (GA) and distance-based algorithm.FindingsSimulation results show that the proper performance of the proposed technique. The proposed method, in terms of “energy” and “delay,” is better than other ones (GA, PSO and distance-based algorithm).Practical implicationsThe paper presents a useful method for improving resource allocation methods. The proposed method has higher efficiency compared to the previous methods. The MATLAB-based simulation results have indicated that energy consumption and delay have been improved compared to other algorithms, which causes the high application of this method in practical projects. In the future, the focus will be on resource failure and reducing the service level agreement violation rate concerning the number of resources.Originality/valueThe proposed technique can solve the mentioned problem in the IoT with the best resource utilization, low delay and reduced energy consumption. The proposed forest optimization-based algorithm is a promising technique to help enterprises participate in IoT initiatives and develop their business.

Systematic energy and exergy assessment of a hydropurification process: Theoretical and practical insights

Improvement of process efficiency and reduction of operation costs are of significant importance in industrial chemical plants. In this study, an effective approach is proposed to analyze a hydropurification process, focusing on energy utilization, operating costs, environmental impact (e.g., CO2 emissions), and exergy performance. The hydropurification process includes heat exchangers, pumps, crystallizers, reactor, and furnace. This process is operated under high pressures and temperatures; it is prone to high consumption of energy and considerable loss of work quality. The vital operating parameters affecting the system performance are chosen by employing Taguchi method. The process simulation and/or thermodynamic modeling are carried out using Aspen Plus® software, and by writing codes for the exergy calculation in MATLAB software environment. The results are in acceptable agreement with the industrial data. The optimal conditions lead to 15% reduction in the process exergy destruction. The optimal operation can be established by implementing lower minimum approach temperature (ΔTmin) of the reaction system feed preheaters (e.g., 5 °C), setting a higher operating pressure in the heat exchangers of the feed preparation section (e.g., 96 bar), and enhancing the performance of heat exchangers using oil as heat transfer medium (optimizing furnace operating conditions). Furthermore, the performance of the fourth and sixth heat exchangers can be enhanced by 33.3%; the performance of the fourth crystallizer can be improved up to 18.7%. The furnace, which utilizes the expensive Therminol® 66 (as the heat transfer fluid), experiences a significant exergy destruction due to significant fluctuations in temperature and thermodynamic irreversibility in the combustion process. Implementation of the proposed optimal conditions can lower the operation costs and carbon tax by 9.96% ($20.5/h) and 14.75% ($14.54/h), respectively; and the CO2 emission rate can be decreased by 0.582 t/h. A decrease in ΔTmin of the heat exchangers improves the process specific energy consumption and exergy destruction. Moreover, effective control of the plant and avoidance of high fluctuations in the process parameters can lead to exergy destruction reduction.

SYNTHESIS TRENDS OF FORECASTING USING INDUCTIVE MODELING METHODS

Modern development of computer technology and the possibility of implementing calculations in parallel allow to solve increasingly large-scale problems of numerical modeling. The development of multiprocessor computing and parallel computing makes it important to solve problems of optimization analysis. The optimization analysis is based on the mass solution of inverse problems when the defining parameters of the considered class of problems change in certain ranges. Thus, calculations of not only direct problems where it is necessary to model the phenomenon at the known initial data, but also calculations of inverse problems where it is necessary to define on what defining parameters there is this or that phenomenon become more and more demanded. This formulation requires multiple solutions of direct problems and solving the problem of optimization analysis and construction of predictive trends. Sets of multidimensional parametric data in the paper are considered as numerical solutions of the optimization problem. The construction of predictive trends is implemented on the basis of the group method of data handling as a direction of induction modeling. The methodology of visualization of results of calculation of parametric functions is realized. The scheme of Data Mining with application of methods of visualization by means of the Matlab software environment is described

The design of a seasonal heat storage system with a geothermal heat pump for a residential building in Tehran

Purpose In this study, a solar water heating system along with a seasonal thermal energy storage and a heat pump is designed for a villa with an area of 192 m2 in Tehran, the capital of Iran. Design/methodology/approach According to the material and the area of the residential space, the required heating of the building was calculated manually and then the thermodynamic analysis of the system and simulation was done in MATLAB software. Finally, regarding the waste of system, an efficient solar heating system, providing all the required energy to heat the building, was obtained. Findings The surface area of the solar collector is equal to 46 m2, the capacity of the tank is about 2,850 m3, insulation thickness stands at 55 cm and the coefficient of performance in required heat pump is accounted to about 9.02. Also, according to the assessments, the maximum level of received energy by the collector in this system occurs at a maximum temperature of 68ºC. Originality/value To the best of the authors’ knowledge, in the present work, for the first time, using mathematical modeling and analyzing of the first and second laws of thermodynamics, as well as using of computational code in MATLAB software environment, the solar-assisted ground source heat pump system is simulated in a residential unit located in Tehran.

Yellow Pigment Powders Based on Lead and Antimony: Particle Size and Colour Hue.

This paper reports the results of particle size analysis and colour measurements concerning yellow powders, synthesised in our laboratories according to ancient recipes aiming at producing pigments for paintings, ceramics, and glasses. These pigments are based on lead and antimony as chemical elements, that, combined in different proportions and fired at different temperatures, times, and with various additives, gave materials of yellow colours, changing in hues and particle size. Artificial yellow pigments, based on lead and antimony, have been widely studied, but no specific investigation on particle size distribution and its correlation to colour hue has been performed before. In order to evaluate the particle size distribution, segmentation of sample data has been performed using the MATLAB software environment. The extracted parameters were examined by principal component analysis (PCA) in order to detect differences and analogies between samples on the base of those parameters. Principal component analysis was also applied to colour data acquired by a reflectance spectrophotometer in the visible range according to the CIELAB colour space. Within the two examined groups, i.e., yellows containing NaCl and those containing K-tartrate, differences have been found between samples and also between different areas of the same powder indicating the inhomogeneity of the synthesised pigments. On the other hand, colour data showed homogeneity within each yellow sample and clear differences between the different powders. The comparison of results demonstrates the potentiality of the particle segmentation and analysis in the study of morphology and distribution of pigment powders produced artificially, allowing the characterisation of the lead and antimony-based pigments through micro-image analysis and colour measurements combined with a multivariate approach.

Combining CFD, ASE, and HEKF approaches to derive all of the hydrodynamic coefficients of an axisymmetric AUV

In this proposed method, which is based on combination of the nonlinear Hybrid Extended Kalman Filter (HEKF) observer, Analytical and Semi-Empirical (ASE) formulas, and Computational Fluid Dynamics (CFD) simulations, all of the hydrodynamic coefficients of a REMUS AUV are estimated to simulate its motions in 6 Degrees of Freedom (6-DoF). First, Using ASE formulas along with necessary static simulations of the AUV using commercial CFD code of ANSYS CFX software, some hydrodynamic derivatives like drag, lift, and fin coefficients are obtained. Then, utilizing the dynamic simulation of the Straight-Line Test (SLT), the longitudinal added mass coefficient is derived. Finally, benefiting from the HEKF code based on the parameter identification, other unknown coefficients like added mass and damping are estimated in the MATLAB software environment. In HEKF, positions and velocities of the vehicle, which are the system output vector, are obtained from a 6-DoF dynamic maneuver in CFX. It is worth mentioning that, in the present study, the remeshing algorithm in the dynamic mesh approach is used to simulate the dynamic maneuvers of the vehicle. Results, obtained from the proposed combined method, indicate a good agreement for estimated coefficients in comparison with the available analytical and experimental values.

ACHIEVING CLOSE RANGE PHOTOGRAMMETRY WITH NON-METRIC MOBILE PHONE CAMERAS

Close range photogrammetry (CRP) has gained increasing relevance over the years with its principles and theories being applied in diverse applications. Further supporting this trend, the current increase in the wide spread usage of mobile phones with high resolution cameras is expected to further popularize positioning by CRP. This paper presents the results of an experimental study wherein two (2) non-metric mobile phone cameras have been used to determine the 3-D coordinates of points on a building by using the collinearity condition equation in an iterative least square bundle adjustment process in MATLAB software environment. The two (2) mobile phones used were Tecno W3 and Infinix X509 phones with focal lengths of 5.432 mm and 8.391 mm respectively. Statistical tests on the results obtained shows that there is no significant difference between the 3-D coordinates obtained by ground survey and those obtained from both cameras at 99% confidence level. Furthermore, the study confirmed the capability of non-metric mobile phone cameras to determine 3D point positions to centimeter level accuracy (with maximum residuals of 11.8 cm, 31.0 cm, and 5.9 cm for the Tecno W3 camera and 14.6 cm, 16.1 cm and 1.8 cm for the Infinix X509 camera in the Eastings, Northings and Heights respectively).

A new damage identification method in beam to column connections and column base connections of steel frame

In the present study, an effective method for damage detecting in beam to column connections and column to the ground connections is presented. Rotational springs are used to model the joints (beam to column and column to the ground) of the steel frame. After finite element modeling of the studied frames in Matlab software environment, modal analysis was performed. To identification of joint damages, an optimization problem formulated to identify location and severity of damages. A new optimization algorithm called moth-flame algorithm with high accuracy and speed is used to solve this problem. The joint damages modeled through the reduction of the rotational stiffness factors. To show the performance of presented approach, two frames consist of a four-story steel frame and a nine-story steel frame have been investigated. In the studied frames, damage was assumed at the beam to column connections and column to the ground connections and then the severity and location of damage at the assumed joint were identified by the proposed method. The results indicated that the proposed method is robust to detect damage in beam to column connections and column to the ground connections that can accurately identify the location and severity of damage at the joints.

Mathematical Modeling of the Availability of the Information System for Critical Use to Optimize Control of its Communication Capabilities

Background: One of the communication ability characteristics is the availability of information system for critical use (ISCU) which provides the allocation of computational resources the finite volume of which is limited by the concept of a virtual machine (VM) to the authorized person (AP) in response to his input request and access to critical data in accordance with the control schemes synthesized taking into account privileges of AP in the form of system security policy rules. Objective: The objective of the article is to optimize the communication capabilities of the information system for critical use for which purpose to synthesize a mathematical concept of availability oriented to practical application. Method: The article presents new mathematical models for controlling the availability of ISCU which, unlike the existing ones, take into account the features of the ISCU topology, the rules and essence of its service operations while controlling the access process of APs to the information environment (IE) of the system. These models also formalize the connection of the set of service operations with the set of system responses to the input requests from the APs in the form of a controlled semi-Markov process with reserving resources for the self security of a system from the consequences of the actions of the APs. On the basis of suggested models the mathematical programming task was formulated that allows to identify the optimal strategy for managing the availability of the ISCU with minimizing the costs of its functioning and to obtain a stochastic estimation of the availability of the system at any stage of its life cycle. Results: Based on the created mathematical models, simulation of the availability of ISCU was performed using the Matlab software environment. The research results showed that the rules for responding to incoming requests from APs based on the proposed models, depending on the system load and service operations performed in the system IE, make it possible to maintain the probability of incoming requests being rejected from APs within specified limits, minimizing the cost of functioning the ISCU. However, analysis of empirical results showed that during the time of construction of the system security policy rules based on the proposed model of availability of ISCU with reserving resources to ensure the security of the system IE from the actions of APs with the rapidly increasing intensity of incoming requests from APs with high values of the danger characteristic, the number of access rejections starts to increase quadratically. In general, the obtained experimental results confirmed the adequacy of the proposed mathematical models for the availability of ISCU. Conclusion: The study proposes the mathematical models of the availability of the information system for critical use to optimize control of its communication capabilities. Studies have shown that to neutralize the consequences of the above situation leading to a decrease of the availability of ISCU it is necessary to lay a 20% reserve of system resources at the design stage.

Investigation of the throughput of nonlinear surge arresters using the MatLab software environment

This work is devoted to the topical issue of researching the throughput of nonlinear surge suppressors. The article discusses various options for test installations and offers simulation models. The MatLab environment, the Simulink simulation application, was chosen as the simulation software environment. The impulse current curve was calculated, after which the tests of nonlinear arresters using rectangular pulses were carried out. The simulation results of installations for operating tests of the surge arrester were compared with the real indicators of laboratory studies for arresters of the OPNp-110 UHL1 brand.

Feature Extraction and Classification of Segmented ECG Signals Based on Radial Basis Function and Random Forest Methodology

Heart disease is the major cause of death ratio increase in this decade. Nowadays various people of different age sector undergo the high risk of heart problems and miss their precious life all of a sudden. Early detection of heart disease will save many people’s life well in advance. Heart Diseases are predictable and they can be identified in earlier stage. First basic method to identify heart disease is ElectroCardioGram (ECG) which is the basic recording method of electrical activities of a functioning heart. ECG is the cheapest and painless method to detect the basic heart problems. This paper is an attempt to detect and classify heart beat signals which will serve as the basic step to predict basic and serious issues which may affect the functioning of the heart. The raw ECG signals are extracted and preprocessed to remove unwanted noises which will produce effective results. The preprocessed ECG signals are then are utilized to identify the heart beats which comprise of signals such as P,Q,R,S,T and U. After detecting the heart beats, they are segmented to extract the ECG Features. The temporal and spectral features are extracted from the segmented ECG signals for classification purpose. The extracted feature vectors are utilized to classify the signals. Radial Basis function and Random Forest method are commonly used classification methodologies; hence these two methodologies are applied to classify the ECG Signals into five basic classes. Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) Arrhythmia database and Noise Stress database are used for this implementation and the classes are identified based on the given dataset parameters. Performance metrics such as accuracy, specificity and sensitivity are computed to find out the best classification methodology among the applied two methodologies. This performance analysis provides a clear comparative view of both the existing methodologies and specifies that Radial Basis function well suits for the given segmented ECG signals and the extracted features. Hence this performance evaluation paves way for best classification algorithm selection or extension of the best methodology and it can be further optimized for better classification result. The implementation process has been carried out using Matlab software environment.

A robust control strategy for a single‐phase grid‐connected multibus microgrid based on adaptive sliding mode control and dynamic phasor concept

Due to the increasing development of distribution networks, the need to use clean energy resources, and the existence of different single-phase and three-phase consumers, the maximum use of both single-phase and three-phase distributed generation (DG) units has become crucial. However, the presence of DG units in microgrids (MGs) requires efficient control strategies, for power control and voltage regulation, to achieve a rapid and proper dynamic response with respect to external disturbances and uncertainties. In this paper, in order to improve the dynamic and steady-state performance of an unbalanced multibus microgrid including inverter-based single-phase DGs, a robust control strategy is proposed for controlling the active and reactive power of DGs. The proposed control scheme is composed of a current controller based on an adaptive sliding mode control method in a virtual synchronous dq reference frame, to control the single-phase inverter output current, and a PI controller to regulate the voltage magnitude of the generation buses connected to DGs. In the proposed control structure, each single-phase inverter is controlled as a virtual balanced three-phase inverter, based on the dynamic phasor concept that makes decoupled control of the active and reactive powers of single-phase inverters possible. In order to evaluate the validity and effectiveness of the presented control structure, a multibus single-phase MG containing several inverter-based single-phase DG units has been simulated in MATLAB software environment, and the performance of the proposed control scheme has been investigated for various scenarios of parametric uncertainties and external disturbances.

ECG Denoising Methodology using Intrinsic Time Scale Decomposition and Adaptive Switching Mean Filter

Electrocardiogram (ECG) is a widely employed tool for the analysis of cardiac disorders. A clean ECG is often desired for proper treatment of cardiac ailments. However, in the real scenario, ECG signals are corrupted with various noises during acquisition and transmission. In this article, an efficient ECG de-noising methodology using combined intrinsic time scale decomposition (ITD) and adaptive switching mean filter (ASMF) is proposed. The standard performance metric namely output SNR improvement measure the efficacy of the proposed technique at various signal to noise ratio (SNR). The proposed de-noising methodology is compared with other existing ECG de-noising approaches. A detail qualitative and quantitative study and analysis indicate that the proposed technique can be used as an effective tool for de-noising of ECG signals and hence can serve for better diagnostic in computer-based automated medical system. The performance of the proposed work is compared with existing ECG de-noising techniques namely wavelet soft thresholding based filter (DWT) [16], EMD with DWT technique [18], DWT with ADTF technique [19]. The effectiveness of the presented work has been evaluated in both qualitative and quantitative analysis. All the simulations are carried out using MATLAB software environment.

ECG Denoising Methodology using Intrinsic Time Scale Decomposition and Adaptive Switching Mean Filter

Electrocardiogram (ECG) is a widely employed tool for the analysis of cardiac disorders. A clean ECG is often desired for proper treatment of cardiac ailments. However, in the real scenario, ECG signals are corrupted with various noises during acquisition and transmission. In this article, an efficient ECG de-noising methodology using combined intrinsic time scale decomposition (ITD) and adaptive switching mean filter (ASMF) is proposed. The standard performance metric namely output SNR improvement measure the efficacy of the proposed technique at various signal to noise ratio (SNR). The proposed de-noising methodology is compared with other existing ECG de-noising approaches. A detail qualitative and quantitative study and analysis indicate that the proposed technique can be used as an effective tool for de-noising of ECG signals and hence can serve for better diagnostic in computer-based automated medical system. The performance of the proposed work is compared with existing ECG de-noising techniques namely wavelet soft thresholding based filter (DWT) [16], EMD with DWT technique [18], DWT with ADTF technique [19]. The effectiveness of the presented work has been evaluated in both qualitative and quantitative analysis. All the simulations are carried out using MATLAB software environment.