Pub Date : 2019-02-01DOI: 10.1109/KBEI.2019.8735035
S. M. R. Hashemi, Ehsan Kozegar, M. M. Deramgozin, B. Minaei-Bidgoli
Artificial neural networks have been increasingly used in many problems of data classification because of their learning capacity, robustness and extendibility. Training in the neural networks accomplished by identifying the weight of neurons which is one of the main issues addressed in this field. The process of network learning by back-propagation algorithm which is based on gradient, commonly fall into a local optimum. Due to the importance of weights and neural network structure, evolutionary neural networks have been emerged to obtain suitable weight set. This paper will concentrate on training a feed-forward networks by a modified evolutionary algorithm based on asexual reproduction optimization (ARO) in order to data classification problems. The idea is to use real representation (rather the binary) for adjusting weights of the network. Experimental results show a better result in terms of speed and accuracy compared with other evolutionary algorithms including genetic algorithms, simulated annealing and particle swarm optimization.
{"title":"Training Feed-forward Neural Networks using Asexual Reproduction Optimization (ARO) Algorithm","authors":"S. M. R. Hashemi, Ehsan Kozegar, M. M. Deramgozin, B. Minaei-Bidgoli","doi":"10.1109/KBEI.2019.8735035","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735035","url":null,"abstract":"Artificial neural networks have been increasingly used in many problems of data classification because of their learning capacity, robustness and extendibility. Training in the neural networks accomplished by identifying the weight of neurons which is one of the main issues addressed in this field. The process of network learning by back-propagation algorithm which is based on gradient, commonly fall into a local optimum. Due to the importance of weights and neural network structure, evolutionary neural networks have been emerged to obtain suitable weight set. This paper will concentrate on training a feed-forward networks by a modified evolutionary algorithm based on asexual reproduction optimization (ARO) in order to data classification problems. The idea is to use real representation (rather the binary) for adjusting weights of the network. Experimental results show a better result in terms of speed and accuracy compared with other evolutionary algorithms including genetic algorithms, simulated annealing and particle swarm optimization.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132983466","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8734995
Masoud Shirzadeh, M. Shojaeefard, A. Amirkhani, H. Behroozi
In this paper, a nonlinear controller, which can be updated online by means of fuzzy logic, has been proposed for tracking the trajectory of a car-like robot. The advantage of this control scheme is that it eliminates the effects of model disturbances and uncertainties, which cannot be avoided; and especially when we consider the difficult task of determining the exact kinematic and dynamic models of car-like robots. The proposed approach comprises a robust nonlinear section that uses the sliding mode control and a fuzzy section that can update, online, parameters of the nonlinear controller. The stability and the error convergence of the closed-loop system are verified through the Lyapunov criterion. A fuzzy system is designed to deal with the chattering of the car-like robot. In addition to the gains of the sign function, there are also constant parameters in our controller, which are determined by using a genetic algorithm. To show the effectiveness of the proposed design, simulations are performed by considering un-ideal effects such as uncertainties and external disturbances.
{"title":"Adaptive fuzzy nonlinear sliding-mode controller for a car-like robot","authors":"Masoud Shirzadeh, M. Shojaeefard, A. Amirkhani, H. Behroozi","doi":"10.1109/KBEI.2019.8734995","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734995","url":null,"abstract":"In this paper, a nonlinear controller, which can be updated online by means of fuzzy logic, has been proposed for tracking the trajectory of a car-like robot. The advantage of this control scheme is that it eliminates the effects of model disturbances and uncertainties, which cannot be avoided; and especially when we consider the difficult task of determining the exact kinematic and dynamic models of car-like robots. The proposed approach comprises a robust nonlinear section that uses the sliding mode control and a fuzzy section that can update, online, parameters of the nonlinear controller. The stability and the error convergence of the closed-loop system are verified through the Lyapunov criterion. A fuzzy system is designed to deal with the chattering of the car-like robot. In addition to the gains of the sign function, there are also constant parameters in our controller, which are determined by using a genetic algorithm. To show the effectiveness of the proposed design, simulations are performed by considering un-ideal effects such as uncertainties and external disturbances.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123950620","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8735063
M. Golchin
Forecasting the demand of customers has a main role for managing the cost of marketing. Therefore, using a tool for forecasting the demand is vital for companies. There are many tools for forecasting and predicting the demand as time series. In this study a new hybrid model which contains fuzzy inference system and cellular automata has been developed. The results showed that, considering the information of more neighbor customers may cause more reliable forecasting and more complicated, fuzzy system may cause better performance for predicting the demand.
{"title":"Companies Products Demands Forecasting using Learning Fuzzy Cellular Automata Model. Case Study: Barij Essence Pharmaceutical Company","authors":"M. Golchin","doi":"10.1109/KBEI.2019.8735063","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735063","url":null,"abstract":"Forecasting the demand of customers has a main role for managing the cost of marketing. Therefore, using a tool for forecasting the demand is vital for companies. There are many tools for forecasting and predicting the demand as time series. In this study a new hybrid model which contains fuzzy inference system and cellular automata has been developed. The results showed that, considering the information of more neighbor customers may cause more reliable forecasting and more complicated, fuzzy system may cause better performance for predicting the demand.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124268549","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8735050
Mostafa Soleymanifard, M. Hamghalam
One of the purposes from segmenting the brain tissues is to separate the damaged tissue in the patient's brain. In fact, brain tissue segmentation is one of the essential steps in the detection and treatment of brain abnormalities. This time-consuming task is usually performed by clinical experts who are not errorless. The proposed method in this paper is to automate the brain tumor segmentation with the aim of making the segmentation process more complete and closer to the clinical treatments. We propose a novel method that is a combination of neural networks and active contours to automatically segment the gliomas in MRI multi-modalities brain images. The proposed algorithm is trained locally by using a neural network at random points in tumor boundary patches, then, by combining the modality of the MRI images and the active contours, the complete tumor is segmented. The obtained results as well as the evaluation criteria such as DICE coefficient, show that the proposed model is highly competitive in comparison with the state of the art segmentation methods.
{"title":"Segmentation of Whole Tumor Using Localized Active Contour and Trained Neural Network in Boundaries","authors":"Mostafa Soleymanifard, M. Hamghalam","doi":"10.1109/KBEI.2019.8735050","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735050","url":null,"abstract":"One of the purposes from segmenting the brain tissues is to separate the damaged tissue in the patient's brain. In fact, brain tissue segmentation is one of the essential steps in the detection and treatment of brain abnormalities. This time-consuming task is usually performed by clinical experts who are not errorless. The proposed method in this paper is to automate the brain tumor segmentation with the aim of making the segmentation process more complete and closer to the clinical treatments. We propose a novel method that is a combination of neural networks and active contours to automatically segment the gliomas in MRI multi-modalities brain images. The proposed algorithm is trained locally by using a neural network at random points in tumor boundary patches, then, by combining the modality of the MRI images and the active contours, the complete tumor is segmented. The obtained results as well as the evaluation criteria such as DICE coefficient, show that the proposed model is highly competitive in comparison with the state of the art segmentation methods.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130189388","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8734929
H. Ghasemi, Saeed Ansari-Rad, A. Kalhor, M. T. Masouleh
Autonomous quad-rotor flight systems have grabbed considerable attention for varied missions in rescue, inspection devices, and so forth. Accordingly, various control methods have been employed for hovering these devices. Recently, in order to extend the applications of quad-rotors, including, among the others, the pick-and-place, a robotic arm has been attached, which requires the analysis of both dynamic equations and control procedures. However, considering the coupled system as a case of robot-robot interaction, these state-of-the-art flight systems have rarely received attention due to much higher complexity of dynamic equations. Moreover, flight time expense is revealed as another critical issue in the flight systems with the attached arm, which requires effective solution due to excessive arm loads and power source limitations. To this end, in this paper, the dynamic equations of quad-rotor with a 3-link arm are obtained in order to be employed in designing suitable control methods. In this regard, by stabilizing the quad-rotor in desired coordinations and tracking desired paths for robotic arm, the dynamic interaction as the main challenge of the robot-robot interaction is successfully handled. Thereafter, a Linear Quadratic Regulator (LQR) is proposed to tackle the flight time issue in which by assigning optimal values to the state input weighting matrix, the motion of arm links reduced and as the result, the flight time effectively increases. In order to demonstrate the superiority of the proposed method, two well-known control approaches, namely, Sliding Mode Control (SMC) and Pole Placement are implemented in the same conditions. In simulation with Matlab software, the performance of the forgoing methods is compared by employing different indices, where it is inferred that despite presence of an external force resembling windy condition, the proposed LQR decreases the motion index by 24.14% in compare with SMC and Pole Placement methods, with approximately similar tracking index to them.
{"title":"Control of Quad-rotor in Cooperation with an Attached 3-DOF Manipulator","authors":"H. Ghasemi, Saeed Ansari-Rad, A. Kalhor, M. T. Masouleh","doi":"10.1109/KBEI.2019.8734929","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734929","url":null,"abstract":"Autonomous quad-rotor flight systems have grabbed considerable attention for varied missions in rescue, inspection devices, and so forth. Accordingly, various control methods have been employed for hovering these devices. Recently, in order to extend the applications of quad-rotors, including, among the others, the pick-and-place, a robotic arm has been attached, which requires the analysis of both dynamic equations and control procedures. However, considering the coupled system as a case of robot-robot interaction, these state-of-the-art flight systems have rarely received attention due to much higher complexity of dynamic equations. Moreover, flight time expense is revealed as another critical issue in the flight systems with the attached arm, which requires effective solution due to excessive arm loads and power source limitations. To this end, in this paper, the dynamic equations of quad-rotor with a 3-link arm are obtained in order to be employed in designing suitable control methods. In this regard, by stabilizing the quad-rotor in desired coordinations and tracking desired paths for robotic arm, the dynamic interaction as the main challenge of the robot-robot interaction is successfully handled. Thereafter, a Linear Quadratic Regulator (LQR) is proposed to tackle the flight time issue in which by assigning optimal values to the state input weighting matrix, the motion of arm links reduced and as the result, the flight time effectively increases. In order to demonstrate the superiority of the proposed method, two well-known control approaches, namely, Sliding Mode Control (SMC) and Pole Placement are implemented in the same conditions. In simulation with Matlab software, the performance of the forgoing methods is compared by employing different indices, where it is inferred that despite presence of an external force resembling windy condition, the proposed LQR decreases the motion index by 24.14% in compare with SMC and Pole Placement methods, with approximately similar tracking index to them.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128272025","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8734974
Niyoosha Dallalazar, A. Ayatollahi, M. Habibi, A. Kermani
Intravascular optical coherence tomography IVOCT is a catheter-based imaging modality that uses near-infrared light, to produce high-resolution cross-sectional images of the vessel wall. Segmentation of the vessel wall is important to indicate stenosis and analyze atherosclerotic plaques. In this study we use the recently proposed region detector, named Extremal Region of Extremum Level (EREL), to detect the lumen and media contours in IVOCT frames, and then we used a region selection method to detect the most precise lumen and media contours from the extracted ERELs. We evaluated the proposed method on the dataset containing 142 IVOCT images. We get, the average Hausdorff Distances (HD) and Dice metric (DSC) between the extracted ERELs and the lumen and media contours, 0.045 mm, 0.141 mm and 0.986, 0.96, respectively. The results of our study showed that the IVOCT image segmentation using the proposed method is more robust and more precise than state-of-the-art.
血管内光学相干断层扫描(IVOCT)是一种基于导管的成像方式，使用近红外光产生血管壁的高分辨率横截面图像。血管壁的分割对于显示狭窄和分析动脉粥样硬化斑块很重要。在本研究中，我们使用最近提出的区域检测器——极值水平的极值区域(extreme region of Extremum Level, EREL)来检测IVOCT帧中的腔体和介质轮廓，然后我们使用区域选择方法从提取的EREL中检测出最精确的腔体和介质轮廓。我们在包含142张IVOCT图像的数据集上评估了所提出的方法。我们得到的平均Hausdorff距离(HD)和Dice度量(DSC)在提取的ERELs与腔体和介质轮廓之间分别为0.045 mm, 0.141 mm和0.986,0.96。研究结果表明，使用该方法进行的IVOCT图像分割比现有方法具有更强的鲁棒性和精度。
{"title":"Automatic vessel wall segmentation of IVOCT images using region detection EREL algorithm","authors":"Niyoosha Dallalazar, A. Ayatollahi, M. Habibi, A. Kermani","doi":"10.1109/KBEI.2019.8734974","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734974","url":null,"abstract":"Intravascular optical coherence tomography IVOCT is a catheter-based imaging modality that uses near-infrared light, to produce high-resolution cross-sectional images of the vessel wall. Segmentation of the vessel wall is important to indicate stenosis and analyze atherosclerotic plaques. In this study we use the recently proposed region detector, named Extremal Region of Extremum Level (EREL), to detect the lumen and media contours in IVOCT frames, and then we used a region selection method to detect the most precise lumen and media contours from the extracted ERELs. We evaluated the proposed method on the dataset containing 142 IVOCT images. We get, the average Hausdorff Distances (HD) and Dice metric (DSC) between the extracted ERELs and the lumen and media contours, 0.045 mm, 0.141 mm and 0.986, 0.96, respectively. The results of our study showed that the IVOCT image segmentation using the proposed method is more robust and more precise than state-of-the-art.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123117326","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8734934
M. Navabi, A. Davoodi
Fuel slosh dynamics can disturb attitude of spacecraft which has a partially filled container, in orbital maneuvering. So, it is necessary to control this harmful phenomenon. This paper models coupled dynamics of fuel sloshing and attitude of the spacecraft by two-pendulum model, and designs a fuzzy controller to control sloshing and attitude dynamics of the vehicle. Also, effectiveness of this controller is illustrated by conducted simulation.
{"title":"2D Modeling and Fuzzy Control of Slosh Dynamics in a Spacecraft","authors":"M. Navabi, A. Davoodi","doi":"10.1109/KBEI.2019.8734934","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734934","url":null,"abstract":"Fuel slosh dynamics can disturb attitude of spacecraft which has a partially filled container, in orbital maneuvering. So, it is necessary to control this harmful phenomenon. This paper models coupled dynamics of fuel sloshing and attitude of the spacecraft by two-pendulum model, and designs a fuzzy controller to control sloshing and attitude dynamics of the vehicle. Also, effectiveness of this controller is illustrated by conducted simulation.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121620414","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8735068
Mahdi Salehi, F. Farivar
Car wing has many capabilities to work on and benefit from. There are different types of wings and spoilers in sport cars that are being used to help having better acceleration, braking, etc. Generally after aerodynamic analysis of wings or rear spoilers, and simulation the second step is to find the best control system to achieve maximum advantages from wings and spoilers. In other words, the wing working time is during car’s cornering and turning on different angels, braking or accelerating that is the time for a control system to operate. In this paper the goal is to implement state feedback tracking control system and optimization of the system by LQR method around equilibrium and operating points of the system specially during cornering of the vehicle. So to obtain the goal, the first step is to review previous works and benefit from. Then the second section is considered for mathematical calculation and the system dynamics plus design of mechanical components and assembled system by CATIA software. After that the control model is extracted for the control system. Furthermore the control system, which is tracking control system, is designed, implemented and the results are shown by figures and plots. The final step is to optimize the control system by LQR optimal control method and the results are compared to other methods. In this article the control system is simulated by MATLAB software.
{"title":"State Feedback Control Design of Cars Wings in Order to Improve Road-Holding on Corners of Roads","authors":"Mahdi Salehi, F. Farivar","doi":"10.1109/KBEI.2019.8735068","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8735068","url":null,"abstract":"Car wing has many capabilities to work on and benefit from. There are different types of wings and spoilers in sport cars that are being used to help having better acceleration, braking, etc. Generally after aerodynamic analysis of wings or rear spoilers, and simulation the second step is to find the best control system to achieve maximum advantages from wings and spoilers. In other words, the wing working time is during car’s cornering and turning on different angels, braking or accelerating that is the time for a control system to operate. In this paper the goal is to implement state feedback tracking control system and optimization of the system by LQR method around equilibrium and operating points of the system specially during cornering of the vehicle. So to obtain the goal, the first step is to review previous works and benefit from. Then the second section is considered for mathematical calculation and the system dynamics plus design of mechanical components and assembled system by CATIA software. After that the control model is extracted for the control system. Furthermore the control system, which is tracking control system, is designed, implemented and the results are shown by figures and plots. The final step is to optimize the control system by LQR optimal control method and the results are compared to other methods. In this article the control system is simulated by MATLAB software.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"296 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123460742","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8734984
N. Orouji, A. Ramezani, M. Mosavi
The GPS-based navigation devices play a substantial role in modern life. The GPS receivers provide time, position, and velocity information which are crucial to precise and accurate navigation, especially in the aviation and marine industry. Due to the CDMA nature of the GPS signals, the acquisition and tracking stages are inseparable parts of a GPS receiver. Therefore, high efficiency, high speed, and accuracy are undeniable factors of a good receiver.In this paper, a hardware implementation of the acquisition stage is proposed and analyzed. This structure exploits the parallel frequency search method and utilizes the frequency domain simplifications through the Fourier transform. The structure is implemented and evaluated on the Xilinx ZedBoard which uses an XC7Z020 chip as the main processing unit. The structure's moderate resource usage has made it a good choice for a hardware implementation of GPS receiver.
{"title":"A Hardware Implementation for Acquisition Stage Based on the Parallel Frequency Search Method","authors":"N. Orouji, A. Ramezani, M. Mosavi","doi":"10.1109/KBEI.2019.8734984","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734984","url":null,"abstract":"The GPS-based navigation devices play a substantial role in modern life. The GPS receivers provide time, position, and velocity information which are crucial to precise and accurate navigation, especially in the aviation and marine industry. Due to the CDMA nature of the GPS signals, the acquisition and tracking stages are inseparable parts of a GPS receiver. Therefore, high efficiency, high speed, and accuracy are undeniable factors of a good receiver.In this paper, a hardware implementation of the acquisition stage is proposed and analyzed. This structure exploits the parallel frequency search method and utilizes the frequency domain simplifications through the Fourier transform. The structure is implemented and evaluated on the Xilinx ZedBoard which uses an XC7Z020 chip as the main processing unit. The structure's moderate resource usage has made it a good choice for a hardware implementation of GPS receiver.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127377843","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 : 2019-02-01DOI: 10.1109/KBEI.2019.8734919
Yoosof Mashayekhi, Ehsan Nazerfard, Arman Rahbar, Samira Sirzadeh Haji Mahmood
Fuzzy c-means (FCM) is one of the most popular fuzzy clustering methods and it is used in various applications in computer science. Most clustering methods including FCM, suffer from bad initialization problem. If initial cluster centers (membership degree initialization in FCM) are not selected appropriately, it may yield poor results. In this paper we propose a method called MinMax FCM to overcome this problem. A new objective function is designed in MinMax FCM to this aim. We use maximum variance of clusters as objective function. In this regard, high-variance clusters are penalized. We compare MinMax FCM with FCM in terms of sum of clusters’ variances, maximum variance of clusters, and execution time using a number of UCI datasets.
{"title":"The MinMax Fuzzy C-Means","authors":"Yoosof Mashayekhi, Ehsan Nazerfard, Arman Rahbar, Samira Sirzadeh Haji Mahmood","doi":"10.1109/KBEI.2019.8734919","DOIUrl":"https://doi.org/10.1109/KBEI.2019.8734919","url":null,"abstract":"Fuzzy c-means (FCM) is one of the most popular fuzzy clustering methods and it is used in various applications in computer science. Most clustering methods including FCM, suffer from bad initialization problem. If initial cluster centers (membership degree initialization in FCM) are not selected appropriately, it may yield poor results. In this paper we propose a method called MinMax FCM to overcome this problem. A new objective function is designed in MinMax FCM to this aim. We use maximum variance of clusters as objective function. In this regard, high-variance clusters are penalized. We compare MinMax FCM with FCM in terms of sum of clusters’ variances, maximum variance of clusters, and execution time using a number of UCI datasets.","PeriodicalId":339990,"journal":{"name":"2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133125118","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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