Pub Date : 2016-12-01DOI: 10.1109/ICENCO.2016.7856461
B. Gamal, A. Ouda, Y. Elhalwagy, G. Elnashar
This paper describes implementation of target detecting and tracking system, which can extract required information from images without need for an external processing unit and track the target, based on embedded system. The requirements of image capturing, target detection, allocate target position, and implementing based on raspberry pi system as embedded system on chip kit. Real time tracking is achieved using simple and fast color detection procedures based on frame differencing and camera motion compensation for estimate the motion vectors to control the pan tilt DC motors, which drive the camera to track the moving target in real-time.
{"title":"Embedded target detection system based on raspberry pi system","authors":"B. Gamal, A. Ouda, Y. Elhalwagy, G. Elnashar","doi":"10.1109/ICENCO.2016.7856461","DOIUrl":"https://doi.org/10.1109/ICENCO.2016.7856461","url":null,"abstract":"This paper describes implementation of target detecting and tracking system, which can extract required information from images without need for an external processing unit and track the target, based on embedded system. The requirements of image capturing, target detection, allocate target position, and implementing based on raspberry pi system as embedded system on chip kit. Real time tracking is achieved using simple and fast color detection procedures based on frame differencing and camera motion compensation for estimate the motion vectors to control the pan tilt DC motors, which drive the camera to track the moving target in real-time.","PeriodicalId":332360,"journal":{"name":"2016 12th International Computer Engineering Conference (ICENCO)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116839892","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 : 2016-12-01DOI: 10.1109/ICENCO.2016.7856452
S. Aly, Basma Osman, Walaa Aly, Mahmoud Saber
Automatic Arabic sign language recognition (ArSL) and fingerspelling considered to be the preferred communication method among deaf people. In this paper, we propose a system for alphabetic Arabic sign language recognition using depth and intensity images which acquired from SOFTKINECT™ sensor. The proposed method does not require any extra gloves or any visual marks. Local features from depth and intensity images are learned using unsupervised deep learning method called PCANet. The extracted features are then recognized using linear support vector machine classifier. The performance of the proposed method is evaluated on dataset of real images captured from multi-users. Experiments using a combination of depth and intensity images and also using depth and intensity images separately are performed. The obtained results show that the performance of the proposed system improved by combining both depth and intensity information which give an average accuracy of 99:5%.
{"title":"Arabic sign language fingerspelling recognition from depth and intensity images","authors":"S. Aly, Basma Osman, Walaa Aly, Mahmoud Saber","doi":"10.1109/ICENCO.2016.7856452","DOIUrl":"https://doi.org/10.1109/ICENCO.2016.7856452","url":null,"abstract":"Automatic Arabic sign language recognition (ArSL) and fingerspelling considered to be the preferred communication method among deaf people. In this paper, we propose a system for alphabetic Arabic sign language recognition using depth and intensity images which acquired from SOFTKINECT™ sensor. The proposed method does not require any extra gloves or any visual marks. Local features from depth and intensity images are learned using unsupervised deep learning method called PCANet. The extracted features are then recognized using linear support vector machine classifier. The performance of the proposed method is evaluated on dataset of real images captured from multi-users. Experiments using a combination of depth and intensity images and also using depth and intensity images separately are performed. The obtained results show that the performance of the proposed system improved by combining both depth and intensity information which give an average accuracy of 99:5%.","PeriodicalId":332360,"journal":{"name":"2016 12th International Computer Engineering Conference (ICENCO)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130978197","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 : 2016-12-01DOI: 10.1109/ICENCO.2016.7856469
Mohammed Badawy, A. El-Aziz, H. Hefny
This study aimed to analyze the learning objectives of the higher education textbooks, according to verbs of intended learning outcomes which were set by the Quality Management of Institute of Statistical Studies and Research (ISSR), Cairo University, Egypt. This study provides a set of recommendations that will help to choose the best chapters of a textbook which is investigating the largest amount of targeted intended learning outcomes that helps explore the key performance indicators for organizations. A dataset of learning objectives for each chapter and intended learning outcomes has been collected. Each learning objective from chapters and the Intended learning outcomes were processed through the removal of punctuation and stop words, tokenization, stemming and term weighting.
{"title":"Analysis of learning objectives for higher education textbooks using text mining","authors":"Mohammed Badawy, A. El-Aziz, H. Hefny","doi":"10.1109/ICENCO.2016.7856469","DOIUrl":"https://doi.org/10.1109/ICENCO.2016.7856469","url":null,"abstract":"This study aimed to analyze the learning objectives of the higher education textbooks, according to verbs of intended learning outcomes which were set by the Quality Management of Institute of Statistical Studies and Research (ISSR), Cairo University, Egypt. This study provides a set of recommendations that will help to choose the best chapters of a textbook which is investigating the largest amount of targeted intended learning outcomes that helps explore the key performance indicators for organizations. A dataset of learning objectives for each chapter and intended learning outcomes has been collected. Each learning objective from chapters and the Intended learning outcomes were processed through the removal of punctuation and stop words, tokenization, stemming and term weighting.","PeriodicalId":332360,"journal":{"name":"2016 12th International Computer Engineering Conference (ICENCO)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133698103","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 : 2016-12-01DOI: 10.1109/ICENCO.2016.7856467
A. Hamad, E. H. Houssein, A. Hassanien, A. Fahmy
Epilepsy is one of the most common a chronic neurological disorders of the brain that affect millions of the world's populations. It is characterized by recurrent seizures, which are physical reactions to sudden, usually brief, excessive electrical discharges in a group of brain cells. Hence, seizure identification has great importance in clinical therapy of epileptic patients. Electroencephalogram (EEG) is most commonly used in epilepsy detection since it includes precious physiological information of the brain. However, it could be a challenge to detect the subtle but critical changes included in EEG signals. Feature extraction of EEG signals is core trouble on EEG-based brain mapping analysis. This paper will extract ten features from EEG signal based on discrete wavelet transform (DWT) for epilepsy detection. These numerous features will help the classifiers to achieve a good accuracy when utilize to classify EEG signal to detect epilepsy. Subsequently, the results have illustrated that DWT has been adopted to extract various features i.e., Entropy, Min, Max, Mean, Median, Standard deviation, Variance, Skewness, Energy and Relative Wave Energy (RWE).
{"title":"Feature extraction of epilepsy EEG using discrete wavelet transform","authors":"A. Hamad, E. H. Houssein, A. Hassanien, A. Fahmy","doi":"10.1109/ICENCO.2016.7856467","DOIUrl":"https://doi.org/10.1109/ICENCO.2016.7856467","url":null,"abstract":"Epilepsy is one of the most common a chronic neurological disorders of the brain that affect millions of the world's populations. It is characterized by recurrent seizures, which are physical reactions to sudden, usually brief, excessive electrical discharges in a group of brain cells. Hence, seizure identification has great importance in clinical therapy of epileptic patients. Electroencephalogram (EEG) is most commonly used in epilepsy detection since it includes precious physiological information of the brain. However, it could be a challenge to detect the subtle but critical changes included in EEG signals. Feature extraction of EEG signals is core trouble on EEG-based brain mapping analysis. This paper will extract ten features from EEG signal based on discrete wavelet transform (DWT) for epilepsy detection. These numerous features will help the classifiers to achieve a good accuracy when utilize to classify EEG signal to detect epilepsy. Subsequently, the results have illustrated that DWT has been adopted to extract various features i.e., Entropy, Min, Max, Mean, Median, Standard deviation, Variance, Skewness, Energy and Relative Wave Energy (RWE).","PeriodicalId":332360,"journal":{"name":"2016 12th International Computer Engineering Conference (ICENCO)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123196481","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 : 2016-12-01DOI: 10.1109/ICENCO.2016.7856445
S. H. Basha, Areeg S. Abdalla, A. Hassanien
In this paper, we present a hybrid intelligent system based on Neutrosophic Logic (NL). In conjunction with Genetic Algorithm(GA) for classification. The neutrosophic logic is adapted for representing different forms of knowledge. GA is used to refine the generated neutrosophic rules. The performance of the proposed system is tested on three real-world databases Iris, Wine, and Wisconsin Diagnostic Breast Cancer (WDBC). In a series of experiments, we compare the performance of the proposed genetic neutrosophic rule-based classification system with that of the neutrosophic rule-based classification system. The performance of both classifiers is measured for the three real-world data sets. We have reached an average accuracy 98.39% in genetic neutrosophic against 94.78% for the corresponding neutrosophic.
本文提出了一种基于嗜中性逻辑(NL)的混合智能系统。结合遗传算法(GA)进行分类。中性逻辑适用于表示不同形式的知识。利用遗传算法对生成的嗜中性规则进行细化。该系统的性能在三个真实数据库Iris、Wine和Wisconsin Diagnostic Breast Cancer (WDBC)上进行了测试。在一系列实验中，我们将提出的基于遗传中性粒细胞规则的分类系统与基于中性粒细胞规则的分类系统的性能进行了比较。这两个分类器的性能是针对三个真实世界的数据集进行测量的。基因嗜中性粒细胞的平均准确率为98.39%，而相应嗜中性粒细胞的平均准确率为94.78%。
{"title":"GNRCS: Hybrid Classification System based on Neutrosophic Logic and Genetic Algorithm","authors":"S. H. Basha, Areeg S. Abdalla, A. Hassanien","doi":"10.1109/ICENCO.2016.7856445","DOIUrl":"https://doi.org/10.1109/ICENCO.2016.7856445","url":null,"abstract":"In this paper, we present a hybrid intelligent system based on Neutrosophic Logic (NL). In conjunction with Genetic Algorithm(GA) for classification. The neutrosophic logic is adapted for representing different forms of knowledge. GA is used to refine the generated neutrosophic rules. The performance of the proposed system is tested on three real-world databases Iris, Wine, and Wisconsin Diagnostic Breast Cancer (WDBC). In a series of experiments, we compare the performance of the proposed genetic neutrosophic rule-based classification system with that of the neutrosophic rule-based classification system. The performance of both classifiers is measured for the three real-world data sets. We have reached an average accuracy 98.39% in genetic neutrosophic against 94.78% for the corresponding neutrosophic.","PeriodicalId":332360,"journal":{"name":"2016 12th International Computer Engineering Conference (ICENCO)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126671307","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 : 2016-12-01DOI: 10.1109/ICENCO.2016.7856450
Heba Abdelghany, A. El-Bastawissy, Mohamed Osman
e-Government implementation and applications have gained a growing attention in the last decade. Countries seek to apply and extend the use of e-Government, and international organizations evaluate e-Government implementation and its impacts. The benefits of e-Government sound to be worthy while the costs of e-Government implementation sound to be costly. A clear implementation plan is a must to avoid financial loss. Countries should follow a road map compatible with their specific capabilities. Countries can depend on e-Government Maturity Models as guidelines for e-Government implementation. Available e-Government Maturity Models do not address the needs of individual countries. This article presents a new e-Government Maturity Model adjustable according to countries own capabilities through multi-layers, to ensure e-Government successful implementation within available resources. So this model is applicable for any given country, and it is even more useful for countries with limited resources.
{"title":"E-Government multi-layers Maturity Model","authors":"Heba Abdelghany, A. El-Bastawissy, Mohamed Osman","doi":"10.1109/ICENCO.2016.7856450","DOIUrl":"https://doi.org/10.1109/ICENCO.2016.7856450","url":null,"abstract":"e-Government implementation and applications have gained a growing attention in the last decade. Countries seek to apply and extend the use of e-Government, and international organizations evaluate e-Government implementation and its impacts. The benefits of e-Government sound to be worthy while the costs of e-Government implementation sound to be costly. A clear implementation plan is a must to avoid financial loss. Countries should follow a road map compatible with their specific capabilities. Countries can depend on e-Government Maturity Models as guidelines for e-Government implementation. Available e-Government Maturity Models do not address the needs of individual countries. This article presents a new e-Government Maturity Model adjustable according to countries own capabilities through multi-layers, to ensure e-Government successful implementation within available resources. So this model is applicable for any given country, and it is even more useful for countries with limited resources.","PeriodicalId":332360,"journal":{"name":"2016 12th International Computer Engineering Conference (ICENCO)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121628955","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 : 2016-12-01DOI: 10.1109/ICENCO.2016.7856473
A. F. Amer, E. Sallam, I. Sultan
This paper presents a proposed adaptive technique for nonholonomic wheeled mobile robot (NWMR) using the sliding-mode control (SMC) method. The proposed control system based on the backstepping kinematic controller and PI sliding mode dynamic control. With an adaptive fuzzy logic to adjust adaptation gain of SMC for trajectory tracking control of nonholonomic mobile robot. Parametric and nonparametric uncertainties of mobile robot can be solved by using the proposed control which take advantages of stability and robustness in sliding mode control. The adaptation gain of SMC is adjusted by using Mamdani type inference system with adaptive tuning algorithm, which improves the adaptability for uncertainness and eliminate input chattering of the SMC. The stability and convergence of the control system are proved using Lypanouve criteria, and the comparison of the proposed controller with the other controllers ensures the validity and superiority of my own controller
{"title":"Adaptive sliding-mode dynamic controller for nonholonomic mobile robots","authors":"A. F. Amer, E. Sallam, I. Sultan","doi":"10.1109/ICENCO.2016.7856473","DOIUrl":"https://doi.org/10.1109/ICENCO.2016.7856473","url":null,"abstract":"This paper presents a proposed adaptive technique for nonholonomic wheeled mobile robot (NWMR) using the sliding-mode control (SMC) method. The proposed control system based on the backstepping kinematic controller and PI sliding mode dynamic control. With an adaptive fuzzy logic to adjust adaptation gain of SMC for trajectory tracking control of nonholonomic mobile robot. Parametric and nonparametric uncertainties of mobile robot can be solved by using the proposed control which take advantages of stability and robustness in sliding mode control. The adaptation gain of SMC is adjusted by using Mamdani type inference system with adaptive tuning algorithm, which improves the adaptability for uncertainness and eliminate input chattering of the SMC. The stability and convergence of the control system are proved using Lypanouve criteria, and the comparison of the proposed controller with the other controllers ensures the validity and superiority of my own controller","PeriodicalId":332360,"journal":{"name":"2016 12th International Computer Engineering Conference (ICENCO)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124343653","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 : 2016-12-01DOI: 10.1109/ICENCO.2016.7856439
M. M. Mabrook, G. Fahmy, A. Hussein, M. Abdelghany
Spectrum sensing is a key technology in establishing and developing cognitive radio networks. High efficiency, reliability and real time are the most important required parameters for accurate sensing process. Wideband sensing is the main factor to achieve reliability of sensing process. Shadowing, fading and aliasing problems of signals affect the performance of spectrum sensing process therefore; cooperative sensing is effectively used to overcome such problems. In this paper, a novel system is proposed to sense the free channels in a wideband spectrum over distributed cooperative sensing platform of Multi-Coset (MC) periodic non-uniform sampling technique with lower branches then lower complexity than conventional MC sampler. The proposed system is designed to receive a blind input wideband signal. In this work, a system consists of four cooperated nodes by sharing their sensing output data to achieve sensing process. The cooperation between cognitive radio users is executed via reporting channels that connect different nodes. The final decision is based on the majority rules of cooperative sensing. Simulation results illustrated that the probability of detection results from cooperative sensing is higher than the individual sensing by each user itself.
{"title":"Novel adaptive non-uniform sub-Nyquist sampling technique for cooperative wideband spectrum sensing","authors":"M. M. Mabrook, G. Fahmy, A. Hussein, M. Abdelghany","doi":"10.1109/ICENCO.2016.7856439","DOIUrl":"https://doi.org/10.1109/ICENCO.2016.7856439","url":null,"abstract":"Spectrum sensing is a key technology in establishing and developing cognitive radio networks. High efficiency, reliability and real time are the most important required parameters for accurate sensing process. Wideband sensing is the main factor to achieve reliability of sensing process. Shadowing, fading and aliasing problems of signals affect the performance of spectrum sensing process therefore; cooperative sensing is effectively used to overcome such problems. In this paper, a novel system is proposed to sense the free channels in a wideband spectrum over distributed cooperative sensing platform of Multi-Coset (MC) periodic non-uniform sampling technique with lower branches then lower complexity than conventional MC sampler. The proposed system is designed to receive a blind input wideband signal. In this work, a system consists of four cooperated nodes by sharing their sensing output data to achieve sensing process. The cooperation between cognitive radio users is executed via reporting channels that connect different nodes. The final decision is based on the majority rules of cooperative sensing. Simulation results illustrated that the probability of detection results from cooperative sensing is higher than the individual sensing by each user itself.","PeriodicalId":332360,"journal":{"name":"2016 12th International Computer Engineering Conference (ICENCO)","volume":"665 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132276313","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 : 2016-12-01DOI: 10.1109/ICENCO.2016.7856441
Amira Abdelatey, Mohamed Elkawkagy, A. El-Sisi, A. Keshk
Negotiation gets more attention in the field of business and becomes a more critical issue especially with the increasing use of services. In web services, negotiation is important for providers to meet consumers' expectation. For consumer and provider, security is an important concern. In this paper, an efficient genetic-based security negotiation approach for web service is proposed. A prototype is implemented for the proposed approach using JADE agent framework. To find a good fitness for the proposed genetic-based approach, we investigate different values for mutation rate and crossover rate. In addition, a comparison between the proposed approach, traditional time-based negotiation approach, and adapted traditional time-based negotiation approach is conducted. Furthermore, scalability tests, the execution time, and the success percentage of the three approaches are measured. From experimental results, the proposed approach outperforms the other two approaches.
{"title":"Efficient genetic-based approach for web service security negotiation","authors":"Amira Abdelatey, Mohamed Elkawkagy, A. El-Sisi, A. Keshk","doi":"10.1109/ICENCO.2016.7856441","DOIUrl":"https://doi.org/10.1109/ICENCO.2016.7856441","url":null,"abstract":"Negotiation gets more attention in the field of business and becomes a more critical issue especially with the increasing use of services. In web services, negotiation is important for providers to meet consumers' expectation. For consumer and provider, security is an important concern. In this paper, an efficient genetic-based security negotiation approach for web service is proposed. A prototype is implemented for the proposed approach using JADE agent framework. To find a good fitness for the proposed genetic-based approach, we investigate different values for mutation rate and crossover rate. In addition, a comparison between the proposed approach, traditional time-based negotiation approach, and adapted traditional time-based negotiation approach is conducted. Furthermore, scalability tests, the execution time, and the success percentage of the three approaches are measured. From experimental results, the proposed approach outperforms the other two approaches.","PeriodicalId":332360,"journal":{"name":"2016 12th International Computer Engineering Conference (ICENCO)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125093205","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 : 2016-12-01DOI: 10.1109/ICENCO.2016.7856438
Rana Mirzalou, M. Wagdy
This paper presents a new 8-PSK Super Regenerative Receiver operating in 402–405 MHz MICS band. The proposed topology employs minimum components to design phase detection engine. The receiver utilizes a combined Low Noise Amplifier (LNA) and Super Regenerative Oscillator (SRO) for current reuse purpose and a digital phase detection engine that extracts modulated phase information, via Latches and D-Flip-flops. The receiver is designed and simulated in 130 nm CMOS process and the whole circuit's power consumption is 119µW for the input of −80dBm at the rate of 6 Mbps with Energy Per Bit of 19.8 pj/b.
{"title":"An 8-PSK Super Regenerative Receiver with new phase detection technique","authors":"Rana Mirzalou, M. Wagdy","doi":"10.1109/ICENCO.2016.7856438","DOIUrl":"https://doi.org/10.1109/ICENCO.2016.7856438","url":null,"abstract":"This paper presents a new 8-PSK Super Regenerative Receiver operating in 402–405 MHz MICS band. The proposed topology employs minimum components to design phase detection engine. The receiver utilizes a combined Low Noise Amplifier (LNA) and Super Regenerative Oscillator (SRO) for current reuse purpose and a digital phase detection engine that extracts modulated phase information, via Latches and D-Flip-flops. The receiver is designed and simulated in 130 nm CMOS process and the whole circuit's power consumption is 119µW for the input of −80dBm at the rate of 6 Mbps with Energy Per Bit of 19.8 pj/b.","PeriodicalId":332360,"journal":{"name":"2016 12th International Computer Engineering Conference (ICENCO)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117240493","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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