Pub Date : 2021-01-01DOI: 10.3934/ELECTRENG.2021007
Rebecca M. Hein, Julius-Maximilians-Universität Würzburg Am Hubland D Würzburg Human-Computer Interaction, C. Wienrich, M. Latoschik, Julius-Maximilians-Universität Würzburg Oswald-Külpe-Weg D Würzburg Human-Technique Systems
This study provides a systematic literature review of research (2001–2020) in the field of teaching and learning a foreign language and intercultural learning using immersive technologies. Based on 2507 sources, 54 articles were selected according to a predefined selection criteria. The review is aimed at providing information about which immersive interventions are being used for foreign language learning and teaching and where potential research gaps exist. The papers were analyzed and coded according to the following categories: (1) investigation form and education level, (2) degree of immersion, and technology used, (3) predictors, and (4) criterions. The review identified key research findings relating the use of immersive technologies for learning and teaching a foreign language and intercultural learning at cognitive, affective, and conative levels. The findings revealed research gaps in the area of teachers as a target group, and virtual reality (VR) as a fully immersive intervention form. Furthermore, the studies reviewed rarely examined behavior, and implicit measurements related to inter- and trans-cultural learning and teaching. Inter- and transcultural learning and teaching especially is an underrepresented investigation subject. Finally, concrete suggestions for future research are given. The systematic review contributes to the challenge of interdisciplinary cooperation between pedagogy, foreign language didactics, and Human-Computer Interaction to achieve innovative teaching-learning formats and a successful digital transformation.
{"title":"A systematic review of foreign language learning with immersive technologies (2001-2020)","authors":"Rebecca M. Hein, Julius-Maximilians-Universität Würzburg Am Hubland D Würzburg Human-Computer Interaction, C. Wienrich, M. Latoschik, Julius-Maximilians-Universität Würzburg Oswald-Külpe-Weg D Würzburg Human-Technique Systems","doi":"10.3934/ELECTRENG.2021007","DOIUrl":"https://doi.org/10.3934/ELECTRENG.2021007","url":null,"abstract":"This study provides a systematic literature review of research (2001–2020) in the field of teaching and learning a foreign language and intercultural learning using immersive technologies. Based on 2507 sources, 54 articles were selected according to a predefined selection criteria. The review is aimed at providing information about which immersive interventions are being used for foreign language learning and teaching and where potential research gaps exist. The papers were analyzed and coded according to the following categories: (1) investigation form and education level, (2) degree of immersion, and technology used, (3) predictors, and (4) criterions. The review identified key research findings relating the use of immersive technologies for learning and teaching a foreign language and intercultural learning at cognitive, affective, and conative levels. The findings revealed research gaps in the area of teachers as a target group, and virtual reality (VR) as a fully immersive intervention form. Furthermore, the studies reviewed rarely examined behavior, and implicit measurements related to inter- and trans-cultural learning and teaching. Inter- and transcultural learning and teaching especially is an underrepresented investigation subject. Finally, concrete suggestions for future research are given. The systematic review contributes to the challenge of interdisciplinary cooperation between pedagogy, foreign language didactics, and Human-Computer Interaction to achieve innovative teaching-learning formats and a successful digital transformation.","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70221958","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 : 2021-01-01DOI: 10.3934/electreng.2021012
C. Priyanka, D. Ratnam, Sai Krishna Santosh G
Low noise amplifier (LNA) is a ubiquitous Radio Frequency (RF) component employed in the global navigation satellite system (GNSS) front end receiver to amplify the degraded RF signals captured by the antenna to the desired level. GNSS LNA boosts the desired signal power by adding minimal noise and distortion to mitigate the impact of noise added by subsequential components of the RF receiver chain thereby improving the overall signal-to-noise ratio (SNR) and the overall performance of the system. This paper explores the various GNSS LNA topologies that improve the system's overall performance with minimum power consumption, low noise figure (NF), high gain, good input-output matching, stability, and linearity. The outcome of this research work would help to design a successful LNA for enhancing the performance of the GNSS receiver.
{"title":"A Review on design of low noise amplifiers for global navigational satellite system","authors":"C. Priyanka, D. Ratnam, Sai Krishna Santosh G","doi":"10.3934/electreng.2021012","DOIUrl":"https://doi.org/10.3934/electreng.2021012","url":null,"abstract":"Low noise amplifier (LNA) is a ubiquitous Radio Frequency (RF) component employed in the global navigation satellite system (GNSS) front end receiver to amplify the degraded RF signals captured by the antenna to the desired level. GNSS LNA boosts the desired signal power by adding minimal noise and distortion to mitigate the impact of noise added by subsequential components of the RF receiver chain thereby improving the overall signal-to-noise ratio (SNR) and the overall performance of the system. This paper explores the various GNSS LNA topologies that improve the system's overall performance with minimum power consumption, low noise figure (NF), high gain, good input-output matching, stability, and linearity. The outcome of this research work would help to design a successful LNA for enhancing the performance of the GNSS receiver.","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70222038","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 : 2021-01-01DOI: 10.3934/electreng.2021013
Chetana Kamlaskar, A. Abhyankar
For reliable and accurate multimodal biometric based person verification, demands an effective discriminant feature representation and fusion of the extracted relevant information across multiple biometric modalities. In this paper, we propose feature level fusion by adopting the concept of canonical correlation analysis (CCA) to fuse Iris and Fingerprint feature sets of the same person. The uniqueness of this approach is that it extracts maximized correlated features from feature sets of both modalities as effective discriminant information within the features sets. CCA is, therefore, suitable to analyze the underlying relationship between two feature spaces and generates more powerful feature vectors by removing redundant information. We demonstrate that an efficient multimodal recognition can be achieved with a significant reduction in feature dimensions with less computational complexity and recognition time less than one second by exploiting CCA based joint feature fusion and optimization. To evaluate the performance of the proposed system, Left and Right Iris, and thumb Fingerprints from both hands of the SDUMLA-HMT multimodal dataset are considered in this experiment. We show that our proposed approach significantly outperforms in terms of equal error rate (EER) than unimodal system recognition performance. We also demonstrate that CCA based feature fusion excels than the match score level fusion. Further, an exploration of the correlation between Right Iris and Left Fingerprint images (EER of 0.1050%), and Left Iris and Right Fingerprint images (EER of 1.4286%) are also presented to consider the effect of feature dominance and laterality of the selected modalities for the robust multimodal biometric system.
{"title":"Iris-Fingerprint multimodal biometric system based on optimal feature level fusion model","authors":"Chetana Kamlaskar, A. Abhyankar","doi":"10.3934/electreng.2021013","DOIUrl":"https://doi.org/10.3934/electreng.2021013","url":null,"abstract":"For reliable and accurate multimodal biometric based person verification, demands an effective discriminant feature representation and fusion of the extracted relevant information across multiple biometric modalities. In this paper, we propose feature level fusion by adopting the concept of canonical correlation analysis (CCA) to fuse Iris and Fingerprint feature sets of the same person. The uniqueness of this approach is that it extracts maximized correlated features from feature sets of both modalities as effective discriminant information within the features sets. CCA is, therefore, suitable to analyze the underlying relationship between two feature spaces and generates more powerful feature vectors by removing redundant information. We demonstrate that an efficient multimodal recognition can be achieved with a significant reduction in feature dimensions with less computational complexity and recognition time less than one second by exploiting CCA based joint feature fusion and optimization. To evaluate the performance of the proposed system, Left and Right Iris, and thumb Fingerprints from both hands of the SDUMLA-HMT multimodal dataset are considered in this experiment. We show that our proposed approach significantly outperforms in terms of equal error rate (EER) than unimodal system recognition performance. We also demonstrate that CCA based feature fusion excels than the match score level fusion. Further, an exploration of the correlation between Right Iris and Left Fingerprint images (EER of 0.1050%), and Left Iris and Right Fingerprint images (EER of 1.4286%) are also presented to consider the effect of feature dominance and laterality of the selected modalities for the robust multimodal biometric system.","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70222083","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 : 2020-11-08DOI: 10.3934/electreng.2020.4.347
A. A. Ahmad, A. Mohammed, M. Ajiya, Z. Yunusa, H. Rabiu
This paper deals with analysis of the Barker binary phase radar signal as part of ways to counteract upcoming threats in the field of electronic warfare support (ES) system. The ES part of electronic warfare (EW) provides tactical support by providing key information to other sections responsible for providing response in the form of attack and protection. The analysis of this paper focused on the correct estimation of the basic time parameters (pulse width and pulse repetition period) of this radar signal using instantaneous power obtained from the time-marginal of the time-frequency distribution (TFD), the maxima (power) of the TFD and directly from the product of signal. The main TFD is a modified version of the most common quadratic TFD (QTFD), the Wigner-Ville distribution (WVD) using appropriately chosen separable kernels. This analysis and estimation method developed is tested in the presence of white noise of Gaussian probability density function at different signal-to-noise ratios (SNR). Results obtained show that instantaneous power gotten from the maxima of TFD outshines the other methods with a minimum SNR of ‒14 dB when the specific threshold of 37.5% is used. It also shows that the proposed methods chosen outperform previous works of similar objectives and therefore, making it suitable for practical EW systems.
{"title":"Estimation of time-parameters of Barker binary phase coded radar signal using instantaneous power based methods","authors":"A. A. Ahmad, A. Mohammed, M. Ajiya, Z. Yunusa, H. Rabiu","doi":"10.3934/electreng.2020.4.347","DOIUrl":"https://doi.org/10.3934/electreng.2020.4.347","url":null,"abstract":"This paper deals with analysis of the Barker binary phase radar signal as part of ways to counteract upcoming threats in the field of electronic warfare support (ES) system. The ES part of electronic warfare (EW) provides tactical support by providing key information to other sections responsible for providing response in the form of attack and protection. The analysis of this paper focused on the correct estimation of the basic time parameters (pulse width and pulse repetition period) of this radar signal using instantaneous power obtained from the time-marginal of the time-frequency distribution (TFD), the maxima (power) of the TFD and directly from the product of signal. The main TFD is a modified version of the most common quadratic TFD (QTFD), the Wigner-Ville distribution (WVD) using appropriately chosen separable kernels. This analysis and estimation method developed is tested in the presence of white noise of Gaussian probability density function at different signal-to-noise ratios (SNR). Results obtained show that instantaneous power gotten from the maxima of TFD outshines the other methods with a minimum SNR of ‒14 dB when the specific threshold of 37.5% is used. It also shows that the proposed methods chosen outperform previous works of similar objectives and therefore, making it suitable for practical EW systems.","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46672395","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 : 2020-09-08DOI: 10.3934/electreng.2020.3.326
Amleset Kelati, Hossam Gaber, J. Plosila, H. Tenhunen
Nonintrusive Appliance Load Monitoring (NIALM) is used to analyze individual’s house energy consumption by distinguishing variations in voltage and current of appliances in a household. The method identifies load consumption of each appliance from the aggregated home energy consumption. NIALM will also provide information of load consumptions of each appliance by indirectly detecting the abnormal changes of appliance usage. The proposed NIALM approach is based on features extraction from load consumptions measurements of electrical power signals in order to classify appliance’s state of operation. In this work, we have improved the identification accuracy and the detection of appliances based on their operational state by employing Machine Learning (ML) technique; namely k-nearest neighbor (k-NN) classification algorithm. The dataset used to perform this process is from the publicly available (PLAID) of power, voltage and current signals of appliances from several houses. This is used as benchmark data set. The PLAID dataset is collected and processed for each appliance and our classification results based on k-NN algorithm achieved high accuracy and is able to gain cost-effective solution. In addition, the result shows that k-NN classifier is a proven as an efficient method for NIALM techniques when compared with other proposed different ML options. Based on the used dataset, the average F-score measure obtained using the k-NN classifier is 90%. Possible reasons behind these findings are discussed and areas for further exploration are proposed.
{"title":"Implementation of non-intrusive appliances load monitoring (NIALM) on k-nearest neighbors (k-NN) classifier","authors":"Amleset Kelati, Hossam Gaber, J. Plosila, H. Tenhunen","doi":"10.3934/electreng.2020.3.326","DOIUrl":"https://doi.org/10.3934/electreng.2020.3.326","url":null,"abstract":"Nonintrusive Appliance Load Monitoring (NIALM) is used to analyze individual’s house energy consumption by distinguishing variations in voltage and current of appliances in a household. The method identifies load consumption of each appliance from the aggregated home energy consumption. NIALM will also provide information of load consumptions of each appliance by indirectly detecting the abnormal changes of appliance usage. The proposed NIALM approach is based on features extraction from load consumptions measurements of electrical power signals in order to classify appliance’s state of operation. In this work, we have improved the identification accuracy and the detection of appliances based on their operational state by employing Machine Learning (ML) technique; namely k-nearest neighbor (k-NN) classification algorithm. The dataset used to perform this process is from the publicly available (PLAID) of power, voltage and current signals of appliances from several houses. This is used as benchmark data set. The PLAID dataset is collected and processed for each appliance and our classification results based on k-NN algorithm achieved high accuracy and is able to gain cost-effective solution. In addition, the result shows that k-NN classifier is a proven as an efficient method for NIALM techniques when compared with other proposed different ML options. Based on the used dataset, the average F-score measure obtained using the k-NN classifier is 90%. Possible reasons behind these findings are discussed and areas for further exploration are proposed.","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43918511","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 : 2020-08-19DOI: 10.3934/electreng.2020.3.303
Cherechi Ndukwe, M. Iqbal, Xiaodong Liang, Jahangir Khan, Lawrence O. Aghenta
This paper proposes a LoRa-based wireless communication system for data transfer in microgrids. The proposed system allows connection of multiple sensors to the LoRa transceivers, and enables data collection from various units within a microgrid. The proposed system focuses on communications at the secondary communication level of the microgrid between local controllers of each distributed generation (DG) unit and the microgrid central controller due to the possibility of applying low-bandwidth communication systems at this level. In a proof of concept test bed setup, the data collected by the sensors are sent to the LoRa gateway, which serves as the central monitoring system from which control messages are sent to various microgrid components through their local controllers such as DG units, storage systems and load. In this work, to improve communication security, a private server has been developed using Node-Red instead of cloud servers that are currently used in most Internet-of-Things (IoT) monitoring systems. A range test of the proposed system is carried out to observe the rate of data delivery. It demonstrated over 90% data delivery at 4 km. Finally, a test bed experiment is conducted to validate key features of the proposed system by achieving one-directional data transfer in a grid monitoring system.
{"title":"LoRa-based communication system for data transfer in microgrids","authors":"Cherechi Ndukwe, M. Iqbal, Xiaodong Liang, Jahangir Khan, Lawrence O. Aghenta","doi":"10.3934/electreng.2020.3.303","DOIUrl":"https://doi.org/10.3934/electreng.2020.3.303","url":null,"abstract":"This paper proposes a LoRa-based wireless communication system for data transfer in microgrids. The proposed system allows connection of multiple sensors to the LoRa transceivers, and enables data collection from various units within a microgrid. The proposed system focuses on communications at the secondary communication level of the microgrid between local controllers of each distributed generation (DG) unit and the microgrid central controller due to the possibility of applying low-bandwidth communication systems at this level. In a proof of concept test bed setup, the data collected by the sensors are sent to the LoRa gateway, which serves as the central monitoring system from which control messages are sent to various microgrid components through their local controllers such as DG units, storage systems and load. In this work, to improve communication security, a private server has been developed using Node-Red instead of cloud servers that are currently used in most Internet-of-Things (IoT) monitoring systems. A range test of the proposed system is carried out to observe the rate of data delivery. It demonstrated over 90% data delivery at 4 km. Finally, a test bed experiment is conducted to validate key features of the proposed system by achieving one-directional data transfer in a grid monitoring system.","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46487683","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 : 2020-01-03DOI: 10.3934/electreng.2020.1.114
Mohamed M. Albarghot, M. T. Iqbal, K. Pope, L. Rolland
The actual power system of the MUN Explorer Autonomous Underwater Vehicles (AUVs) uses 11 Lithium-ion (Li-ion) batteries as a main energy source. The batteries are directly connected into the BLDC motor to run the MUN Explorer for the desired operating sequence. This paper presents a dynamic model of the MUN Explorer AUV including a fuel cell system to run under the same operating conditions as suggested by its manual. A PI controller was applied into the dynamic model to maintain the operating conditions such as motor speed, DC bus voltage and the load torque, due to its advantages and simplicity for tuning technique. The MUN Explorer AUV dynamic model with a fuel cell is a proposed system to increase the power capacity, it is better to use a simple controller to see the system behaviors. The simulation of the entire system dynamics model along with the proportional-integral (PI) controller is done in MATLAB / Simulink. The simulation results are included in the paper. The DC bus voltage is measured at 48 V, and the motor speed is 20 (rad/s), which is equivalent to 190 (rpm). The power profile of the fuel cell and battery are presented and plotted against time. The PI controller gives satisfactory results in terms of maintaining the same operating conditions of the MUN Explorer AUV with a fuel cell.
MUN探索者无人潜航器（AUV）的实际动力系统使用11节锂离子电池作为主要能源。电池直接连接到无刷直流电机中，以按照所需的操作顺序运行MUN Explorer。本文提出了一个包括燃料电池系统的MUN Explorer AUV的动态模型，该系统将在与其手册建议的相同操作条件下运行。将PI控制器应用于动态模型中，以保持电机转速、直流母线电压和负载转矩等运行条件，因为它具有调谐技术简单的优点。带有燃料电池的MUN-Explorer AUV动态模型是一个旨在增加功率容量的系统，最好使用一个简单的控制器来观察系统行为。在MATLAB/Simulink中对整个系统的动力学模型以及比例积分控制器进行了仿真。文中给出了仿真结果。直流母线电压在48V下测量，电机速度为20（rad/s），相当于190（rpm）。给出了燃料电池和电池的功率分布图，并绘制了与时间的关系图。PI控制器在保持具有燃料电池的MUN Explorer AUV的相同操作条件方面给出了令人满意的结果。
{"title":"Dynamic modeling and simulation of the MUN Explorer autonomous underwater vehicle with a fuel cell system","authors":"Mohamed M. Albarghot, M. T. Iqbal, K. Pope, L. Rolland","doi":"10.3934/electreng.2020.1.114","DOIUrl":"https://doi.org/10.3934/electreng.2020.1.114","url":null,"abstract":"The actual power system of the MUN Explorer Autonomous Underwater Vehicles (AUVs) uses 11 Lithium-ion (Li-ion) batteries as a main energy source. The batteries are directly connected into the BLDC motor to run the MUN Explorer for the desired operating sequence. This paper presents a dynamic model of the MUN Explorer AUV including a fuel cell system to run under the same operating conditions as suggested by its manual. A PI controller was applied into the dynamic model to maintain the operating conditions such as motor speed, DC bus voltage and the load torque, due to its advantages and simplicity for tuning technique. The MUN Explorer AUV dynamic model with a fuel cell is a proposed system to increase the power capacity, it is better to use a simple controller to see the system behaviors. The simulation of the entire system dynamics model along with the proportional-integral (PI) controller is done in MATLAB / Simulink. The simulation results are included in the paper. The DC bus voltage is measured at 48 V, and the motor speed is 20 (rad/s), which is equivalent to 190 (rpm). The power profile of the fuel cell and battery are presented and plotted against time. The PI controller gives satisfactory results in terms of maintaining the same operating conditions of the MUN Explorer AUV with a fuel cell.","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42833098","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 : 2019-11-12DOI: 10.3934/electreng.2019.4.382
Qichun Zhang
Almost all of the complex dynamic processes are subjected to non-Gaussian random noises which leads to the performance deterioration of Kalman filter and Extended Kalman filter (EKF). To enhance the filtering performance, this paper presents an EKF-based filtering algorithm using minimum entropy criterion for a class of stochastic non-linear systems subjected to non-Gaussian noises. For practical implementations, the Kalman filters are widely used and the structure will not be changed due to the system integration, therefore, it is important to enhance the performance without changing the existing system design. In particular, a compensative framework has been developed where the EKF design meets the basic filtering requirements and the polynomial-based non-linear compensation has been used to adjusted the basic estimation from EKF with the entropy criterion. Since the entropy of the system output estimation error can be approximated using the measured data by kernel density estimation (KDE). A data-based framework can be obtained to enhance the performance. In addition, the presented algorithm is analysed from the view of the estimation convergence and a numerical example has been given to demonstrate the effectiveness.
{"title":"Performance enhanced Kalman filter design for non-Gaussian stochastic systems with data-based minimum entropy optimisation","authors":"Qichun Zhang","doi":"10.3934/electreng.2019.4.382","DOIUrl":"https://doi.org/10.3934/electreng.2019.4.382","url":null,"abstract":"Almost all of the complex dynamic processes are subjected to non-Gaussian random noises which leads to the performance deterioration of Kalman filter and Extended Kalman filter (EKF). To enhance the filtering performance, this paper presents an EKF-based filtering algorithm using minimum entropy criterion for a class of stochastic non-linear systems subjected to non-Gaussian noises. For practical implementations, the Kalman filters are widely used and the structure will not be changed due to the system integration, therefore, it is important to enhance the performance without changing the existing system design. In particular, a compensative framework has been developed where the EKF design meets the basic filtering requirements and the polynomial-based non-linear compensation has been used to adjusted the basic estimation from EKF with the entropy criterion. Since the entropy of the system output estimation error can be approximated using the measured data by kernel density estimation (KDE). A data-based framework can be obtained to enhance the performance. In addition, the presented algorithm is analysed from the view of the estimation convergence and a numerical example has been given to demonstrate the effectiveness.","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42776605","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 : 2019-11-06DOI: 10.3934/electreng.2019.4.370
A. Malag, G. Sobczak, E. Dąbrowska, M. Teodorczyk
This paper describes the way to stabilize in-junction-plane optical field distribution and emitted beam divergence in high-power 970-nm-band laser diodes (LDs). This is done by introducing a lateral periodic structure into the LD‟s wide-stripe-waveguide, designed to prefer and stabilize the selected (resonant) high-order lateral mode. According to modeling, in CW operation the gain equalization of lateral modes due to thermal index guiding leads to beam divergence stabilization by incorporating the modes up to the resonant one and cutting out higher ones. This was demonstrated experimentally in a wide drive current range. Such stability of a non-Gaussian laser beam profile with steep slopes can be interesting for many applications. Thanks to the drive current flow control by the periodic structure, the effects typical for conventional wide-stripe LDs, such as lateral current crowding, carrier accumulation at stripe edges and optical far-field blooming are not observed.
{"title":"In-junction-plane beam divergence stabilization by lateral periodic structure in wide-stripe laser diodes","authors":"A. Malag, G. Sobczak, E. Dąbrowska, M. Teodorczyk","doi":"10.3934/electreng.2019.4.370","DOIUrl":"https://doi.org/10.3934/electreng.2019.4.370","url":null,"abstract":"This paper describes the way to stabilize in-junction-plane optical field distribution and emitted beam divergence in high-power 970-nm-band laser diodes (LDs). This is done by introducing a lateral periodic structure into the LD‟s wide-stripe-waveguide, designed to prefer and stabilize the selected (resonant) high-order lateral mode. According to modeling, in CW operation the gain equalization of lateral modes due to thermal index guiding leads to beam divergence stabilization by incorporating the modes up to the resonant one and cutting out higher ones. This was demonstrated experimentally in a wide drive current range. Such stability of a non-Gaussian laser beam profile with steep slopes can be interesting for many applications. Thanks to the drive current flow control by the periodic structure, the effects typical for conventional wide-stripe LDs, such as lateral current crowding, carrier accumulation at stripe edges and optical far-field blooming are not observed.","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44612795","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 : 2019-10-31DOI: 10.3934/electreng.2019.4.359
A. Zardadi
In this paper, the set-membership affine projection (SM-AP) algorithm is utilized to censor non-informative data in big data applications. To this end, the probability distribution of the additive noise signal and the excess of mean-squared error (EMSE) in steady-state are employed in order to estimate the threshold parameter of the single threshold SM-AP (ST-SM-AP) algorithm aiming at attaining the desired update rate. Furthermore, by defining an acceptable range for the error signal, the double threshold SM-AP (DT-SM-AP) algorithm is proposed to detect very large errors due to the irrelevant data such as outliers. The DT-SM-AP algorithm can censor non-informative and irrelevant data in big data applications, and it can improve misalignment and convergence rate of the learning process with high computational efficiency. The simulation and numerical results corroborate the superiority of the proposed algorithms over traditional algorithms.
{"title":"Data selection with set-membership affine projection algorithm","authors":"A. Zardadi","doi":"10.3934/electreng.2019.4.359","DOIUrl":"https://doi.org/10.3934/electreng.2019.4.359","url":null,"abstract":"In this paper, the set-membership affine projection (SM-AP) algorithm is utilized to censor non-informative data in big data applications. To this end, the probability distribution of the additive noise signal and the excess of mean-squared error (EMSE) in steady-state are employed in order to estimate the threshold parameter of the single threshold SM-AP (ST-SM-AP) algorithm aiming at attaining the desired update rate. Furthermore, by defining an acceptable range for the error signal, the double threshold SM-AP (DT-SM-AP) algorithm is proposed to detect very large errors due to the irrelevant data such as outliers. The DT-SM-AP algorithm can censor non-informative and irrelevant data in big data applications, and it can improve misalignment and convergence rate of the learning process with high computational efficiency. The simulation and numerical results corroborate the superiority of the proposed algorithms over traditional algorithms.","PeriodicalId":36329,"journal":{"name":"AIMS Electronics and Electrical Engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44907089","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}
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