In this paper, a ContikiOS based Library Fire Detection System has been designed and implemented using wireless sensor networks. The system consists of Atmel AVR IRIS motes which are operating with IEEE 802.15.4 network protocol, Linux based RaspberryPI, and ESP8266 Wi-Fi transceiver. The system can be easily transported, re- positioned and expanded. Benefiting from multithreading feature of ContikiOS and executing the tasks in parallel, the system has a short response time, which is critical for fire detection. According to the test results, the system responds to the changes in temperature and prompts a warning/alarm message in approximately 4 seconds.
{"title":"ContikiOS based library fire detection system","authors":"Burak Karaduman, Moharram Challenger, Raheleh Eslampanah","doi":"10.1109/ICEEE2.2018.8391340","DOIUrl":"https://doi.org/10.1109/ICEEE2.2018.8391340","url":null,"abstract":"In this paper, a ContikiOS based Library Fire Detection System has been designed and implemented using wireless sensor networks. The system consists of Atmel AVR IRIS motes which are operating with IEEE 802.15.4 network protocol, Linux based RaspberryPI, and ESP8266 Wi-Fi transceiver. The system can be easily transported, re- positioned and expanded. Benefiting from multithreading feature of ContikiOS and executing the tasks in parallel, the system has a short response time, which is critical for fire detection. According to the test results, the system responds to the changes in temperature and prompts a warning/alarm message in approximately 4 seconds.","PeriodicalId":6482,"journal":{"name":"2018 5th International Conference on Electrical and Electronic Engineering (ICEEE)","volume":"16 1","pages":"247-251"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83154697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-03DOI: 10.1109/ICEEE2.2018.8391290
Gamze Nalcaci, M. Ermiş
Selective Harmonic Elimination (SHE) shows superior harmonic performance at low switching frequencies to eliminate low-order harmonics and this property decreasing losses is a very effective way to reach higher efficiencies in power electronics applications. In this paper, Whale Optimizer Algorithm (WOA) is implemented to decide optimum switching angles for three-phase Voltage Source Inverter (VSI) of eliminating some high order harmonics while providing the required voltage. Besides, Particle Swarm Optimization (PSO) algorithm is also applied and the optimum switching angles are calculated off-line to eliminate the 5th, 7th, 11th, 13th, 17th, and 19th harmonics. The output voltages obtained by the application of WOA and PSO are compared using the total harmonic distortion (THD). By the comparison of these results, we show that WOA gives faster and more accurate results in terms of decreasing THD than PSO algorithm in SHE applications.
{"title":"Selective harmonic elimination for three-phase voltage source inverters using whale optimizer algorithm","authors":"Gamze Nalcaci, M. Ermiş","doi":"10.1109/ICEEE2.2018.8391290","DOIUrl":"https://doi.org/10.1109/ICEEE2.2018.8391290","url":null,"abstract":"Selective Harmonic Elimination (SHE) shows superior harmonic performance at low switching frequencies to eliminate low-order harmonics and this property decreasing losses is a very effective way to reach higher efficiencies in power electronics applications. In this paper, Whale Optimizer Algorithm (WOA) is implemented to decide optimum switching angles for three-phase Voltage Source Inverter (VSI) of eliminating some high order harmonics while providing the required voltage. Besides, Particle Swarm Optimization (PSO) algorithm is also applied and the optimum switching angles are calculated off-line to eliminate the 5th, 7th, 11th, 13th, 17th, and 19th harmonics. The output voltages obtained by the application of WOA and PSO are compared using the total harmonic distortion (THD). By the comparison of these results, we show that WOA gives faster and more accurate results in terms of decreasing THD than PSO algorithm in SHE applications.","PeriodicalId":6482,"journal":{"name":"2018 5th International Conference on Electrical and Electronic Engineering (ICEEE)","volume":"12 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78507779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-03DOI: 10.1109/ICEEE2.2018.8391358
Ali Cüvitoğlu, Z. Işik
Machine-Learning (ML) methods are applied to diagnose diseases and to observe disease developments. We utilized several ML methods on Z-Alizadeh Sani dataset, which is about Coronary Artery Disease (CAD). We applied t-test for feature selection and then Principal Component Analysis (PCA) to reduce dimensionality because of small sample size. 10-fold Cross-Validation was applied to ML methods, which achieved higher than 80% average accuracy. Besides, sensitivity and specificity results are around 70% and 90%, respectively. The Artificial Neural Network reached 93% AUC, which is the best performance out of six methods. The overall results are quite promising compared to the previous study.
{"title":"Classification of CAD dataset by using principal component analysis and machine learning approaches","authors":"Ali Cüvitoğlu, Z. Işik","doi":"10.1109/ICEEE2.2018.8391358","DOIUrl":"https://doi.org/10.1109/ICEEE2.2018.8391358","url":null,"abstract":"Machine-Learning (ML) methods are applied to diagnose diseases and to observe disease developments. We utilized several ML methods on Z-Alizadeh Sani dataset, which is about Coronary Artery Disease (CAD). We applied t-test for feature selection and then Principal Component Analysis (PCA) to reduce dimensionality because of small sample size. 10-fold Cross-Validation was applied to ML methods, which achieved higher than 80% average accuracy. Besides, sensitivity and specificity results are around 70% and 90%, respectively. The Artificial Neural Network reached 93% AUC, which is the best performance out of six methods. The overall results are quite promising compared to the previous study.","PeriodicalId":6482,"journal":{"name":"2018 5th International Conference on Electrical and Electronic Engineering (ICEEE)","volume":"23 1","pages":"340-343"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86247346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-03DOI: 10.1109/ICEEE2.2018.8391294
İskender Özdemir, A. Yildiz
In this study, an efficient method for the analysis of full-wave quasi-resonant zero-current switching buck converter is proposed. To decrease the switching losses, the converter control uses with zero-current switching (ZCS) technique. In the analysis, the modified nodal analysis (MNA) is used to obtain system equations. Simulation results are included to the study.
{"title":"Time-domain analysis of full-wave quasi-resonant zero-current switching buck converter by modified nodal analysis","authors":"İskender Özdemir, A. Yildiz","doi":"10.1109/ICEEE2.2018.8391294","DOIUrl":"https://doi.org/10.1109/ICEEE2.2018.8391294","url":null,"abstract":"In this study, an efficient method for the analysis of full-wave quasi-resonant zero-current switching buck converter is proposed. To decrease the switching losses, the converter control uses with zero-current switching (ZCS) technique. In the analysis, the modified nodal analysis (MNA) is used to obtain system equations. Simulation results are included to the study.","PeriodicalId":6482,"journal":{"name":"2018 5th International Conference on Electrical and Electronic Engineering (ICEEE)","volume":"72 1","pages":"23-26"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82199559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-03DOI: 10.1109/ICEEE2.2018.8391297
H. Bodur, F. Zungor, Erdem Akboy
In this paper, an isolated dc-dc converter based on an active demagnetization structure is presented in order to demagnetize transformer of a converter. Also, duty cycle limitation of two switch forward converter is improved with using this structure. At the same time, A Zero Voltage Transition (ZVT) cell is integrated into this improved converter and Soft Switching (SS) for the switches is achieved, too. So, the proposed converter has features duty cycle more than %50 and no turn on switching losses. Operation principles, theoretical analyses and design methods are presented. These theoretical analyses are verified with simulation results using PowerSIM (PSIM) programme.
{"title":"An improved duty cycle ZVT two swicth forward converter","authors":"H. Bodur, F. Zungor, Erdem Akboy","doi":"10.1109/ICEEE2.2018.8391297","DOIUrl":"https://doi.org/10.1109/ICEEE2.2018.8391297","url":null,"abstract":"In this paper, an isolated dc-dc converter based on an active demagnetization structure is presented in order to demagnetize transformer of a converter. Also, duty cycle limitation of two switch forward converter is improved with using this structure. At the same time, A Zero Voltage Transition (ZVT) cell is integrated into this improved converter and Soft Switching (SS) for the switches is achieved, too. So, the proposed converter has features duty cycle more than %50 and no turn on switching losses. Operation principles, theoretical analyses and design methods are presented. These theoretical analyses are verified with simulation results using PowerSIM (PSIM) programme.","PeriodicalId":6482,"journal":{"name":"2018 5th International Conference on Electrical and Electronic Engineering (ICEEE)","volume":"26 1","pages":"36-40"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89588961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-03DOI: 10.1109/ICEEE2.2018.8391307
A. O. Arslan, M. Kurtoglu, F. Eroǧlu, A. Vural
In this study, a three-phase, 10-kV DC, 50-Hz, modular multilevel converter is designed in PSCAD environment by using 10 sub-modules in each arm. For each submodule of the designed converter, half bridge structure consisting of two IGBTs, two reverse parallel connected diodes and one capacitor are used. The gate signals triggering the semiconductors are obtained by comparing sinusoidal reference signal and triangular carrier signals are used to compare the level shift and phase shift pulse width modulation (PWM) methods. Modulation methods are compared by changing the modulation index and carrier frequency in terms of switching cases, DC voltage utilization factor and output voltage harmonic content. Level shifting (LS) method is advantageous in terms of number of switching with respect to phase shifting (PS) methods while phase shifting methods is better in terms of direct current voltage utilization factor and harmonic content. In the PS-PWM method, it is seen that the number of switching is independent from the modulation index, whereas in the level shifting PWM methods, the number of switching changes with respect to the modulation index. Modular multi-level converters (MMC) provide a cost advantage in medium and high voltage applications compared to conventional two and three-level inverters because of the output voltages do not need to filter out low harmonic content due to the sinusoidal proximity of the output voltages.
{"title":"Comparison of phase and level shifted switching methods for a three-phase modular multilevel converter","authors":"A. O. Arslan, M. Kurtoglu, F. Eroǧlu, A. Vural","doi":"10.1109/ICEEE2.2018.8391307","DOIUrl":"https://doi.org/10.1109/ICEEE2.2018.8391307","url":null,"abstract":"In this study, a three-phase, 10-kV DC, 50-Hz, modular multilevel converter is designed in PSCAD environment by using 10 sub-modules in each arm. For each submodule of the designed converter, half bridge structure consisting of two IGBTs, two reverse parallel connected diodes and one capacitor are used. The gate signals triggering the semiconductors are obtained by comparing sinusoidal reference signal and triangular carrier signals are used to compare the level shift and phase shift pulse width modulation (PWM) methods. Modulation methods are compared by changing the modulation index and carrier frequency in terms of switching cases, DC voltage utilization factor and output voltage harmonic content. Level shifting (LS) method is advantageous in terms of number of switching with respect to phase shifting (PS) methods while phase shifting methods is better in terms of direct current voltage utilization factor and harmonic content. In the PS-PWM method, it is seen that the number of switching is independent from the modulation index, whereas in the level shifting PWM methods, the number of switching changes with respect to the modulation index. Modular multi-level converters (MMC) provide a cost advantage in medium and high voltage applications compared to conventional two and three-level inverters because of the output voltages do not need to filter out low harmonic content due to the sinusoidal proximity of the output voltages.","PeriodicalId":6482,"journal":{"name":"2018 5th International Conference on Electrical and Electronic Engineering (ICEEE)","volume":"33 1","pages":"91-96"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90345570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-03DOI: 10.1109/ICEEE2.2018.8391295
O. Setyawati, H. Suyono, H. Himawan, Nanang Sulistiyanto, M. Rif'an
We present model simulation as reference and ARM STM32 microcontroller - based prototype buck converter. The inductor current and output voltage of the buck converter were controlled using Mamdani method - fuzzy logic in pulse width modulation switching mode. In this research, the prototypes were built based on fuzzy logic and also PID (Proportional-Integral-Derivative) controller. The system prototype without controller, controlled by fuzzy logic, and controlled by PID reached settling time of 31 ms, 24 ms, and 60 ms, respectively. Steady state error of the system prototype controlled by PID was the least, i.e. 0.34 %, meanwhile the prototype controlled by fuzzy logic showed 1.34 % However, controlling the system using fuzzy logic was able to eliminate the overshoot completely. These design and experiment results show that the system can be used for adjusting LED (Light Emitting Diode) driver.
{"title":"Prototype of buck converter using fuzzy logic control for LED driver","authors":"O. Setyawati, H. Suyono, H. Himawan, Nanang Sulistiyanto, M. Rif'an","doi":"10.1109/ICEEE2.2018.8391295","DOIUrl":"https://doi.org/10.1109/ICEEE2.2018.8391295","url":null,"abstract":"We present model simulation as reference and ARM STM32 microcontroller - based prototype buck converter. The inductor current and output voltage of the buck converter were controlled using Mamdani method - fuzzy logic in pulse width modulation switching mode. In this research, the prototypes were built based on fuzzy logic and also PID (Proportional-Integral-Derivative) controller. The system prototype without controller, controlled by fuzzy logic, and controlled by PID reached settling time of 31 ms, 24 ms, and 60 ms, respectively. Steady state error of the system prototype controlled by PID was the least, i.e. 0.34 %, meanwhile the prototype controlled by fuzzy logic showed 1.34 % However, controlling the system using fuzzy logic was able to eliminate the overshoot completely. These design and experiment results show that the system can be used for adjusting LED (Light Emitting Diode) driver.","PeriodicalId":6482,"journal":{"name":"2018 5th International Conference on Electrical and Electronic Engineering (ICEEE)","volume":"2 1","pages":"27-30"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85939284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-03DOI: 10.1109/ICEEE2.2018.8391291
F. Eroǧlu, A. O. Arslan, M. Kurtoglu, A. Vural
Cascaded H-bridge multilevel inverters have gained a significant popularity in medium to high power motor drive applications and grid-connected renewable energy systems in recent years. Under equal DC voltages, cascaded H-bridge multilevel inverters use phase-shifted pulse width modulation (PS-PWM) technique to generate the output voltage. However, under unequal DC voltages which may happen because of the renewable energy sources connected to front-end of the multilevel inverter, traditional PS-PWM method fails to achieve good output harmonics. In this paper, a frequency domain analysis of PS-PWM is presented. By using the analysis, a phase angle modification of traditional PS-PWM is introduced. The proposed method helps eliminate first order harmonics of triangular carrier frequency and its sidebands under randomly selected DC voltages and DC voltage fault conditions. Finally, simulation results for single phase seven- level cascaded H-bridge multilevel inverter are presented to validate the good performance of the proposed method.
{"title":"Generalized adaptive phase-shifted PWM for single-phase seven-level cascaded H-bridge multilevel inverters","authors":"F. Eroǧlu, A. O. Arslan, M. Kurtoglu, A. Vural","doi":"10.1109/ICEEE2.2018.8391291","DOIUrl":"https://doi.org/10.1109/ICEEE2.2018.8391291","url":null,"abstract":"Cascaded H-bridge multilevel inverters have gained a significant popularity in medium to high power motor drive applications and grid-connected renewable energy systems in recent years. Under equal DC voltages, cascaded H-bridge multilevel inverters use phase-shifted pulse width modulation (PS-PWM) technique to generate the output voltage. However, under unequal DC voltages which may happen because of the renewable energy sources connected to front-end of the multilevel inverter, traditional PS-PWM method fails to achieve good output harmonics. In this paper, a frequency domain analysis of PS-PWM is presented. By using the analysis, a phase angle modification of traditional PS-PWM is introduced. The proposed method helps eliminate first order harmonics of triangular carrier frequency and its sidebands under randomly selected DC voltages and DC voltage fault conditions. Finally, simulation results for single phase seven- level cascaded H-bridge multilevel inverter are presented to validate the good performance of the proposed method.","PeriodicalId":6482,"journal":{"name":"2018 5th International Conference on Electrical and Electronic Engineering (ICEEE)","volume":"147 1","pages":"7-12"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89028199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-03DOI: 10.1109/ICEEE2.2018.8391298
Amin Sedighfar, M. R. Moniri
Determination of state of charge (SOC) and state of health (SOH) in today's world becomes an increasingly important issue in all the applications that include a battery. In fact, estimation of the SOC and SOH is a fundamental need for the battery, which is the most important energy storage in Hybrid Electric Vehicles (HEVs), smart grid systems, drones, UPS and so on. Regarding those applications, the estimation algorithms are expected to be precise and easy to implement. This paper presents an online method for the estimation of the SOC and SOH of Valve-Regulated Lead Acid (VRLA) batteries. The proposed method uses the well-known Kalman Filter (KF), and Neural Networks (NNs) and for SOH estimation uses Augmented Kalman Filter (AKF). All of the simulations have been done with MATLAB software. The NN is trained offline using the data collected from the battery discharging process. A generic cell model is used, and the underlying dynamic behavior of the model has used two capacitors (bulk and surface) and three resistors (terminal, surface, and end), where the SOC determined from the voltage represents the bulk capacitor. The aim of this work is to compare the performance of conventional integration-based SOC estimation methods with a mixed algorithm. Moreover, by containing the effect of temperature, the final result becomes more accurate.
{"title":"Battery state of charge and state of health estimation for VRLA batteries using Kalman filter and neural networks","authors":"Amin Sedighfar, M. R. Moniri","doi":"10.1109/ICEEE2.2018.8391298","DOIUrl":"https://doi.org/10.1109/ICEEE2.2018.8391298","url":null,"abstract":"Determination of state of charge (SOC) and state of health (SOH) in today's world becomes an increasingly important issue in all the applications that include a battery. In fact, estimation of the SOC and SOH is a fundamental need for the battery, which is the most important energy storage in Hybrid Electric Vehicles (HEVs), smart grid systems, drones, UPS and so on. Regarding those applications, the estimation algorithms are expected to be precise and easy to implement. This paper presents an online method for the estimation of the SOC and SOH of Valve-Regulated Lead Acid (VRLA) batteries. The proposed method uses the well-known Kalman Filter (KF), and Neural Networks (NNs) and for SOH estimation uses Augmented Kalman Filter (AKF). All of the simulations have been done with MATLAB software. The NN is trained offline using the data collected from the battery discharging process. A generic cell model is used, and the underlying dynamic behavior of the model has used two capacitors (bulk and surface) and three resistors (terminal, surface, and end), where the SOC determined from the voltage represents the bulk capacitor. The aim of this work is to compare the performance of conventional integration-based SOC estimation methods with a mixed algorithm. Moreover, by containing the effect of temperature, the final result becomes more accurate.","PeriodicalId":6482,"journal":{"name":"2018 5th International Conference on Electrical and Electronic Engineering (ICEEE)","volume":"2 1","pages":"41-46"},"PeriodicalIF":0.0,"publicationDate":"2018-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79837351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-05-01DOI: 10.1109/ICEEE2.2018.8391319
E. Akçay, A. Yildiz
In this study, the analysis of fixed capacitor thyristor controlled reactor (FC-TCR), one of Static VAR compensation techniques, is performed by modified nodal analysis (MNA). In the analysis, semiconductor elements are modelled with two- valued resistor concept. The resulting equations are solved by Trapezoidal method, used in numerical analysis. All of the simulation results are obtained in Matlab M-File environment.
{"title":"Time-domain analysis of static VAR compensator by modified nodal analysis","authors":"E. Akçay, A. Yildiz","doi":"10.1109/ICEEE2.2018.8391319","DOIUrl":"https://doi.org/10.1109/ICEEE2.2018.8391319","url":null,"abstract":"In this study, the analysis of fixed capacitor thyristor controlled reactor (FC-TCR), one of Static VAR compensation techniques, is performed by modified nodal analysis (MNA). In the analysis, semiconductor elements are modelled with two- valued resistor concept. The resulting equations are solved by Trapezoidal method, used in numerical analysis. All of the simulation results are obtained in Matlab M-File environment.","PeriodicalId":6482,"journal":{"name":"2018 5th International Conference on Electrical and Electronic Engineering (ICEEE)","volume":"19 1","pages":"148-151"},"PeriodicalIF":0.0,"publicationDate":"2018-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73425670","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：