Pub Date : 2004-09-05DOI: 10.1109/ICEEC.2004.1374422
M. Popal, M. Marcu, A. Popa
A wide-spread operation founded in the monitoring, control and command applications is the data acquisition. The data from the external world is read, processed, used for decisions and, eventually, memorized by a digital system. The digital system may be a PC with dedicated interfaces or microcontroller based system. This paper describes a data acquisition system with USB inteijace. I t is based on the P89C51RD2 microcontroller. The USB interface is achieved by an ISPI181 circuit and the data acquisition is done by two TLCO820 analog digital converters. The software executed by the microcontroller was divided in 5 levels: the 0 hardware abstraction level, the 1 hardware abstraction level, the interrupt service routine, the standard USB requests level and the main loop, each one with specific operations.
{"title":"A microcontroller based data acquisition system with USB interface","authors":"M. Popal, M. Marcu, A. Popa","doi":"10.1109/ICEEC.2004.1374422","DOIUrl":"https://doi.org/10.1109/ICEEC.2004.1374422","url":null,"abstract":"A wide-spread operation founded in the monitoring, control and command applications is the data acquisition. The data from the external world is read, processed, used for decisions and, eventually, memorized by a digital system. The digital system may be a PC with dedicated interfaces or microcontroller based system. This paper describes a data acquisition system with USB inteijace. I t is based on the P89C51RD2 microcontroller. The USB interface is achieved by an ISPI181 circuit and the data acquisition is done by two TLCO820 analog digital converters. The software executed by the microcontroller was divided in 5 levels: the 0 hardware abstraction level, the 1 hardware abstraction level, the interrupt service routine, the standard USB requests level and the main loop, each one with specific operations.","PeriodicalId":180043,"journal":{"name":"International Conference on Electrical, Electronic and Computer Engineering, 2004. ICEEC '04.","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122438287","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 : 2004-09-05DOI: 10.1109/ICEEC.2004.1374454
S. Abrar
Error back propagation (EBP) is the most used training algorithm for feedforwrd artiJicia1 neural networks (FFANNs). Howevei; it is generally believed that it is vely slow if it does converge, especially the network size is not too large compared to the problem at hand. The speed of the learning phase depends both on learning rate (LR) and on the choice of activation functions (AFs). In this papei; a non gradient scheme is proposed to enhance the convergence of EBP algorithm; this scheme is based on the observation that keeping high LR and linear AF during startup enhances the learning capability. But as the network output comes close to the target value, a gradual decrement in LR and increment in the slope of AF ensure a better steady state mapping. The proposed scheme is applied on a blind neural equalizer and it performed better than the standard EBP
误差反向传播(Error back propagation, EBP)是前馈人工神经网络(ffann)最常用的训练算法。Howevei;一般认为，如果它确实收敛，它是非常慢的，特别是与手头的问题相比，网络规模不是太大。学习阶段的速度取决于学习率(LR)和激活函数(AFs)的选择。在本文中;为了提高EBP算法的收敛性，提出了一种非梯度格式;该方案基于在启动时保持高LR和线性AF可以增强学习能力的观察。但当网络输出接近目标值时，LR的逐渐减小和AF的斜率的增加保证了较好的稳态映射。将该方法应用于盲神经均衡器，效果优于标准EBP
{"title":"Slope and learning rate adaptation scheme for neural networks and its application to blind equalization","authors":"S. Abrar","doi":"10.1109/ICEEC.2004.1374454","DOIUrl":"https://doi.org/10.1109/ICEEC.2004.1374454","url":null,"abstract":"Error back propagation (EBP) is the most used training algorithm for feedforwrd artiJicia1 neural networks (FFANNs). Howevei; it is generally believed that it is vely slow if it does converge, especially the network size is not too large compared to the problem at hand. The speed of the learning phase depends both on learning rate (LR) and on the choice of activation functions (AFs). In this papei; a non gradient scheme is proposed to enhance the convergence of EBP algorithm; this scheme is based on the observation that keeping high LR and linear AF during startup enhances the learning capability. But as the network output comes close to the target value, a gradual decrement in LR and increment in the slope of AF ensure a better steady state mapping. The proposed scheme is applied on a blind neural equalizer and it performed better than the standard EBP","PeriodicalId":180043,"journal":{"name":"International Conference on Electrical, Electronic and Computer Engineering, 2004. ICEEC '04.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127893590","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 : 2004-09-05DOI: 10.1109/ICEEC.2004.1374541
H. Ghali
Space-filling curves have been used for the development of a miniaturized ultra wideband fractal wire monopole antennas. Several space-filling curves have been investigated and compared. Resistive loading has been used to achieve the ultra wideband performance. In addition, genetic algorithm has been applied to optimize both the values of the resistive loads and their positions. A multi-frequency cost function is implemented, where the cost function is a combination of VSWR and efficiency. A bandwidth of 108% (about 1.3GHz) centered at 1.2 GHz has been achieved using three resistances on a 2nd iteration Hilbert wire monopole. The proposed ultra wideband 2nd iteration Hilbert wire monopole antenna has a minimum radiation efficiency of 30% over the entire frequency band, and a maximum gain of 5.9dB. The proposed antenna has a footprint of only 7x7cm2. Measurements of the antenna return loss has been performed and compared successfully with the simulation results. The design and simulation have been carried out using SuperNEC® electromagnetic simulator.
{"title":"Miniaturized ultra wideband fractal antenna","authors":"H. Ghali","doi":"10.1109/ICEEC.2004.1374541","DOIUrl":"https://doi.org/10.1109/ICEEC.2004.1374541","url":null,"abstract":"Space-filling curves have been used for the development of a miniaturized ultra wideband fractal wire monopole antennas. Several space-filling curves have been investigated and compared. Resistive loading has been used to achieve the ultra wideband performance. In addition, genetic algorithm has been applied to optimize both the values of the resistive loads and their positions. A multi-frequency cost function is implemented, where the cost function is a combination of VSWR and efficiency. A bandwidth of 108% (about 1.3GHz) centered at 1.2 GHz has been achieved using three resistances on a 2nd iteration Hilbert wire monopole. The proposed ultra wideband 2nd iteration Hilbert wire monopole antenna has a minimum radiation efficiency of 30% over the entire frequency band, and a maximum gain of 5.9dB. The proposed antenna has a footprint of only 7x7cm2. Measurements of the antenna return loss has been performed and compared successfully with the simulation results. The design and simulation have been carried out using SuperNEC® electromagnetic simulator.","PeriodicalId":180043,"journal":{"name":"International Conference on Electrical, Electronic and Computer Engineering, 2004. ICEEC '04.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128015819","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 : 2004-09-05DOI: 10.1109/ICEEC.2004.1374414
S. S. Attia, H. Mahdi, H.K. Mohammad
Data mining aims at searching for meaninghl injormation like patterns and rules in large volumes of data. Our objective is to mine the data of Intelligent Tutoring Systems (rrS). n e s e are tutoring systems which offer the ability to respond to individualized student ne&. An qweriment was conducted over a lesson for binary relatbns. Students’ answers to questions at the end of the lesson were collected. Data mining was implemented to extract important nrles @om the data (students’ answers) and hence the student can be directed to which parts of the lesson he should take again, thus heking to adopt the brtoring systems to each student individual needs nree approaches are applied to detect the decision nrles based on the Rough Sets and the Md$ed Rough &s. n e s e approaches provide a poweijid foundation to discover important structures in data. These approaches are unique in the sense that they onb use the injormation given by the data and do not rely on other model assumptions. f i e results obtained were in the form of rules that showed what concepts the student understood and which he did not understand depending on which questions he answered correct and which questions he answered wrong. Also some questions of the quizzes were found to be useless. It was concluded that data mining was able to extract some important patterns and rules >om the students’ answers which were hidden before and which are helpfir1 to both the students and the expert. Data mining is a set of methods used as a step in the Knowledge Discovery (KD) process to distinguish previously unknown relationships, rules and patterns within large volumes of data [l]. One of data mining tasks is &scription i.e. to describe databases in terms of patterns which human can understand and make use of In our research, we are trying to mine databases resulting from Intelligent Tutoring Systems (ITS). These are Computerbased tutoring systems which achieve their intelligence by representing pedagogical decisions about how to teach as well as information about the learner. This allows for greater versatility by altering t k system’s interactions with students. Intelligent tutoring systems have been shown to be highly effective at increasing student’s motivation and performance [2]. 0-7803-8575-6/04/$20.00 02004 IEEE The goal of data mining in ITS is to automatically assess student knowledge of the concepts underlying a tutorial topic, and use this assessment to direct remediation of knowledge. It does not require any knowledge about the subject being taught [3]. Thus our main objective is to investigate the application of data mining to provide a reliable way to determine a student knowledge status i.e. what a student does and does not know during the course of instruction. Once student knowledge can be assessed automatically without human intervention, computer4ased educational system can be individually tailored to each student’s leaming needs. This research investigates the application of
{"title":"Data mining in intelligent tutoring systems using rough sets","authors":"S. S. Attia, H. Mahdi, H.K. Mohammad","doi":"10.1109/ICEEC.2004.1374414","DOIUrl":"https://doi.org/10.1109/ICEEC.2004.1374414","url":null,"abstract":"Data mining aims at searching for meaninghl injormation like patterns and rules in large volumes of data. Our objective is to mine the data of Intelligent Tutoring Systems (rrS). n e s e are tutoring systems which offer the ability to respond to individualized student ne&. An qweriment was conducted over a lesson for binary relatbns. Students’ answers to questions at the end of the lesson were collected. Data mining was implemented to extract important nrles @om the data (students’ answers) and hence the student can be directed to which parts of the lesson he should take again, thus heking to adopt the brtoring systems to each student individual needs nree approaches are applied to detect the decision nrles based on the Rough Sets and the Md$ed Rough &s. n e s e approaches provide a poweijid foundation to discover important structures in data. These approaches are unique in the sense that they onb use the injormation given by the data and do not rely on other model assumptions. f i e results obtained were in the form of rules that showed what concepts the student understood and which he did not understand depending on which questions he answered correct and which questions he answered wrong. Also some questions of the quizzes were found to be useless. It was concluded that data mining was able to extract some important patterns and rules >om the students’ answers which were hidden before and which are helpfir1 to both the students and the expert. Data mining is a set of methods used as a step in the Knowledge Discovery (KD) process to distinguish previously unknown relationships, rules and patterns within large volumes of data [l]. One of data mining tasks is &scription i.e. to describe databases in terms of patterns which human can understand and make use of In our research, we are trying to mine databases resulting from Intelligent Tutoring Systems (ITS). These are Computerbased tutoring systems which achieve their intelligence by representing pedagogical decisions about how to teach as well as information about the learner. This allows for greater versatility by altering t k system’s interactions with students. Intelligent tutoring systems have been shown to be highly effective at increasing student’s motivation and performance [2]. 0-7803-8575-6/04/$20.00 02004 IEEE The goal of data mining in ITS is to automatically assess student knowledge of the concepts underlying a tutorial topic, and use this assessment to direct remediation of knowledge. It does not require any knowledge about the subject being taught [3]. Thus our main objective is to investigate the application of data mining to provide a reliable way to determine a student knowledge status i.e. what a student does and does not know during the course of instruction. Once student knowledge can be assessed automatically without human intervention, computer4ased educational system can be individually tailored to each student’s leaming needs. This research investigates the application of ","PeriodicalId":180043,"journal":{"name":"International Conference on Electrical, Electronic and Computer Engineering, 2004. ICEEC '04.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121040640","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 : 2004-09-05DOI: 10.1109/ICEEC.2004.1374433
M. M. Hadhoud, N. A. Ismail, W. Shawkey, A. Mohammed
As presented in [1,2,3,4,5] the main requirements of data hiding technique is to be secure, high capacity, and perceptual transparency. Several approaches have been proposed in the literature to accomplish this target, all of these techniques are base on several approaches entropy calculations, the modeling of secure steganographic system and the use of secure generated keys the most poweifiul techniques available for the high capacity data hiding. Yet, authors have used only one of these approaches. In this paper, we propose a high capacity data hiding method based on all of these approaches. The proposed technique is characterized by high perceptual transparency and high security level.
{"title":"Secure perceptual data hiding technique using information theory","authors":"M. M. Hadhoud, N. A. Ismail, W. Shawkey, A. Mohammed","doi":"10.1109/ICEEC.2004.1374433","DOIUrl":"https://doi.org/10.1109/ICEEC.2004.1374433","url":null,"abstract":"As presented in [1,2,3,4,5] the main requirements of data hiding technique is to be secure, high capacity, and perceptual transparency. Several approaches have been proposed in the literature to accomplish this target, all of these techniques are base on several approaches entropy calculations, the modeling of secure steganographic system and the use of secure generated keys the most poweifiul techniques available for the high capacity data hiding. Yet, authors have used only one of these approaches. In this paper, we propose a high capacity data hiding method based on all of these approaches. The proposed technique is characterized by high perceptual transparency and high security level.","PeriodicalId":180043,"journal":{"name":"International Conference on Electrical, Electronic and Computer Engineering, 2004. ICEEC '04.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128940054","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 : 2004-09-05DOI: 10.1109/ICEEC.2004.1374472
M. El-Bardini
The problem considered is that of identibing and control of an unknown rapidly time varying system from input-output data. In this paper a hybrid evolutionary algorithm is described which attempts to model the rapidly time varying parameters. The question of stabiliw is handled to show the converges condition of the proposed mtthod. Results show that this approach is capable of high accuracy for test problems. In recent years, there has been a rapid development of online process control technique. The use of process computers in the control and optimization of dynamic systems of many industrial application is increasing. This has attracted the attention of many researches toward online identification and control schemes. Much work has been done in the area of identifying time-invariant system. [l] An important application of on-line schemes is when the system parameters are time varying where is absolutely necessary to track parameters variation in real time. Some examples of such application are robotic systems, aerospace systems , chemical reactor system and others [2]. System modeling entails constructing a model which behaves similarly to a system whose structure is unknown based on observed data from systems. However , most of the identification methods , such as those based on least mean squares or maximum likelihood estimates, are search techniques based on gradient descent. It is well known that such approaches often fail to find the optimum solution if the parameters of the system are rapidly time varying [3] , the error function is also constructed to be differentiable. In recent years the capability of trained neural networks for approximating arbitrary input-output mapping can find an important application in devising procedures for the identification of unknown dynamical plants in order to control them. It is found in [4] that applying a neural network based controller could result in drastic over parameterization in the number of coefficient estimation made. Evolutionary algorithm differ from traditional methods. They are not fundamentally limited by restrictive assumptions about the search space , such as assumptions concerning continuity , existence of derivatives , and other matters [5-111. Therefore , Evolutionary algorithms are finding increasing applications in the area of system identification. but one of the significant draw back of these algorithms is the time computation in which limit their applications in real time system , for this reason this paper proposes a hybrid evolutionary algorithm has the ability to overcome the problem of identifying …
{"title":"Hybrid evolutionary algorithm for identification and control of time varying system","authors":"M. El-Bardini","doi":"10.1109/ICEEC.2004.1374472","DOIUrl":"https://doi.org/10.1109/ICEEC.2004.1374472","url":null,"abstract":"The problem considered is that of identibing and control of an unknown rapidly time varying system from input-output data. In this paper a hybrid evolutionary algorithm is described which attempts to model the rapidly time varying parameters. The question of stabiliw is handled to show the converges condition of the proposed mtthod. Results show that this approach is capable of high accuracy for test problems. In recent years, there has been a rapid development of online process control technique. The use of process computers in the control and optimization of dynamic systems of many industrial application is increasing. This has attracted the attention of many researches toward online identification and control schemes. Much work has been done in the area of identifying time-invariant system. [l] An important application of on-line schemes is when the system parameters are time varying where is absolutely necessary to track parameters variation in real time. Some examples of such application are robotic systems, aerospace systems , chemical reactor system and others [2]. System modeling entails constructing a model which behaves similarly to a system whose structure is unknown based on observed data from systems. However , most of the identification methods , such as those based on least mean squares or maximum likelihood estimates, are search techniques based on gradient descent. It is well known that such approaches often fail to find the optimum solution if the parameters of the system are rapidly time varying [3] , the error function is also constructed to be differentiable. In recent years the capability of trained neural networks for approximating arbitrary input-output mapping can find an important application in devising procedures for the identification of unknown dynamical plants in order to control them. It is found in [4] that applying a neural network based controller could result in drastic over parameterization in the number of coefficient estimation made. Evolutionary algorithm differ from traditional methods. They are not fundamentally limited by restrictive assumptions about the search space , such as assumptions concerning continuity , existence of derivatives , and other matters [5-111. Therefore , Evolutionary algorithms are finding increasing applications in the area of system identification. but one of the significant draw back of these algorithms is the time computation in which limit their applications in real time system , for this reason this paper proposes a hybrid evolutionary algorithm has the ability to overcome the problem of identifying …","PeriodicalId":180043,"journal":{"name":"International Conference on Electrical, Electronic and Computer Engineering, 2004. ICEEC '04.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114333803","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 : 2004-09-05DOI: 10.1109/ICEEC.2004.1374526
B. Almashary
In this paper, a genetic-based algorithm is proposed and implemented to extract diode circuit model parameters. Saturation current, ideality factor, and series resistance are extracted without a need for initial conditions. The proposed technique is found to be robust and capable to reach a solution that is characterized to be global and accurate. Compared with existing conventional techniques, the proposed one shows superior performance in terms of accuracy and being generic and applicable to extract parameters of other devices. The proposed technique performance has been tested using theoretical data, and used to extract real device parameters from its measured I-V characteristics.
{"title":"Genetic algorithm based diode model prameters extraction","authors":"B. Almashary","doi":"10.1109/ICEEC.2004.1374526","DOIUrl":"https://doi.org/10.1109/ICEEC.2004.1374526","url":null,"abstract":"In this paper, a genetic-based algorithm is proposed and implemented to extract diode circuit model parameters. Saturation current, ideality factor, and series resistance are extracted without a need for initial conditions. The proposed technique is found to be robust and capable to reach a solution that is characterized to be global and accurate. Compared with existing conventional techniques, the proposed one shows superior performance in terms of accuracy and being generic and applicable to extract parameters of other devices. The proposed technique performance has been tested using theoretical data, and used to extract real device parameters from its measured I-V characteristics.","PeriodicalId":180043,"journal":{"name":"International Conference on Electrical, Electronic and Computer Engineering, 2004. ICEEC '04.","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125953276","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 : 2004-09-05DOI: 10.1109/ICEEC.2004.1374554
M. Swillam, A. H. Morshed, D. Khalil
The design of a 3-dB multimode-inter$erencebased symmetrical optical splitter for realization by ion exchange on glass substrates is optimized for wide band peformance taking the graded-index side diffusions into consideration. The depth of diffusion and width of the multimode waveguide section for best coupler performance are determined based on a modified model of ion-e.xchanged waveguides which takes into account the effective index grading in the lateral direction due to the finite width of the waveguide and the presence of side diffusions. The performance of the devices is simulated using the beam propagation method and compared to that of a conventional step-index design. Couplers with larger bandwidths are obtained using optimized designs. Index Terms 3-dB symmetrical optical splitter, multimodeinterference, wide band performance, ion exchange on glass, graded-index side diffusions.
{"title":"Optimization of optical wide band 3-dB MMI splitter with graded-index side diffusions","authors":"M. Swillam, A. H. Morshed, D. Khalil","doi":"10.1109/ICEEC.2004.1374554","DOIUrl":"https://doi.org/10.1109/ICEEC.2004.1374554","url":null,"abstract":"The design of a 3-dB multimode-inter$erencebased symmetrical optical splitter for realization by ion exchange on glass substrates is optimized for wide band peformance taking the graded-index side diffusions into consideration. The depth of diffusion and width of the multimode waveguide section for best coupler performance are determined based on a modified model of ion-e.xchanged waveguides which takes into account the effective index grading in the lateral direction due to the finite width of the waveguide and the presence of side diffusions. The performance of the devices is simulated using the beam propagation method and compared to that of a conventional step-index design. Couplers with larger bandwidths are obtained using optimized designs. Index Terms 3-dB symmetrical optical splitter, multimodeinterference, wide band performance, ion exchange on glass, graded-index side diffusions.","PeriodicalId":180043,"journal":{"name":"International Conference on Electrical, Electronic and Computer Engineering, 2004. ICEEC '04.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131567656","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 : 2004-09-05DOI: 10.1109/ICEEC.2004.1374537
S. Abrar
Blind equalization (BE) is a technique for adaptive equalization of a communication channel without the aid of the usual training sequence. Stochastic gradient based BE algorithm equalize the dispersive signals by exploiting the high-order statistics of the transmitted signal using some pre-calculated constants. These constants, usually termed as dispersion constants, contain the information about the size, shape, and energy of the transmitted signal. In this work, closed form expressions are obtained for the dispersion constant used in Weerackody-Kassam hard limited algorithm (WKA) for square and symmetric quadrature amplitude modulation (QAM) signals. (a): y = 9, 128QAM 1 5 1 1 5 -10 0 10 aR (b): y = 13,256-QAM 10 15 -10 0 10 a Fig. 1. Zero-error contours for WKA.
盲均衡是一种不借助常规训练序列对通信信道进行自适应均衡的技术。基于随机梯度的BE算法利用发射信号的高阶统计量，利用一些预先计算的常数来均衡色散信号。这些常数，通常被称为色散常数，包含有关传输信号的大小、形状和能量的信息。在这项工作中，得到了Weerackody-Kassam硬限制算法(WKA)中用于方形和对称正交调幅(QAM)信号的色散常数的封闭表达式。(a): y = 9,128 qam 15 15 5 -10 0 10 aR (b): y = 13,256-QAM 10 15 -10 0 10 a图1。WKA的零错误轮廓。
{"title":"Closed form expressions for the dispersion constant of weerackody-kassam algorithm for blind equalization","authors":"S. Abrar","doi":"10.1109/ICEEC.2004.1374537","DOIUrl":"https://doi.org/10.1109/ICEEC.2004.1374537","url":null,"abstract":"Blind equalization (BE) is a technique for adaptive equalization of a communication channel without the aid of the usual training sequence. Stochastic gradient based BE algorithm equalize the dispersive signals by exploiting the high-order statistics of the transmitted signal using some pre-calculated constants. These constants, usually termed as dispersion constants, contain the information about the size, shape, and energy of the transmitted signal. In this work, closed form expressions are obtained for the dispersion constant used in Weerackody-Kassam hard limited algorithm (WKA) for square and symmetric quadrature amplitude modulation (QAM) signals. (a): y = 9, 128QAM 1 5 1 1 5 -10 0 10 aR (b): y = 13,256-QAM 10 15 -10 0 10 a Fig. 1. Zero-error contours for WKA.","PeriodicalId":180043,"journal":{"name":"International Conference on Electrical, Electronic and Computer Engineering, 2004. ICEEC '04.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130214200","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 : 2004-09-05DOI: 10.1109/ICEEC.2004.1374495
N.B. El Feki, D. Masmoudi, N. Derbel
In this paper, we introduce a new frequency compensation method of the CCII based floating inductance. In order to get tunable characteristics of the proposed inductance, a translinear CCII is implemented for its controllable series parasitic resistance at port X. After achieving a frequency characterization of the proposed CCII, we analyze the frequency limitations of the conventional CCII based tunable floating simulated inductance which is independent of tuning current. To overcome these limitations, a pole/zero compensation strategy is applied. Therefore, a series passive resistance Rs=650Q is used and a high active negative resistance is introduced by means of CCII's. Simulation results show that the proposed compensation technique enlarges the tuning range of the inductance. Moreover, a special arrangement is proposed so that the compensation solution is insensitive to the control current tuning the inductance value.
{"title":"On the frequency compensation of simulated CCII based tunable floating inductance for LC ladder filters applications","authors":"N.B. El Feki, D. Masmoudi, N. Derbel","doi":"10.1109/ICEEC.2004.1374495","DOIUrl":"https://doi.org/10.1109/ICEEC.2004.1374495","url":null,"abstract":"In this paper, we introduce a new frequency compensation method of the CCII based floating inductance. In order to get tunable characteristics of the proposed inductance, a translinear CCII is implemented for its controllable series parasitic resistance at port X. After achieving a frequency characterization of the proposed CCII, we analyze the frequency limitations of the conventional CCII based tunable floating simulated inductance which is independent of tuning current. To overcome these limitations, a pole/zero compensation strategy is applied. Therefore, a series passive resistance Rs=650Q is used and a high active negative resistance is introduced by means of CCII's. Simulation results show that the proposed compensation technique enlarges the tuning range of the inductance. Moreover, a special arrangement is proposed so that the compensation solution is insensitive to the control current tuning the inductance value.","PeriodicalId":180043,"journal":{"name":"International Conference on Electrical, Electronic and Computer Engineering, 2004. ICEEC '04.","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134101818","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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