Pub Date : 2012-04-18DOI: 10.1109/SIU.2012.6204523
E. Mühendisliği, Bölümü Zonguldak, Karaelmas Üniversitesi, Özetçe Haberleşme, Gđrđş
The amplifiers that are used on communication systems in order to increase the productivity, are worked on the nonlinear region. Therefore, digital communication channel can be defined as a Wiener block structure that contains a linear dynamic system and a non-linear static block. In this study, the nonlinear channel equalization problem, a Wiener block structured communication channel is tried to equalize by using a Hammerstein block structure. In order to do that performance of the suggested approach is investigated with LMS and RLS algorithms. The convergence rates of these adaptive algorithms are compared on the real valued data transmission so that LMS algorithm is observed slower convergence but less complex, RLS algorithm is observed much faster convergence rate.
{"title":"Equalization of nonlinear communication channel based on Hammerstein block structure","authors":"E. Mühendisliği, Bölümü Zonguldak, Karaelmas Üniversitesi, Özetçe Haberleşme, Gđrđş","doi":"10.1109/SIU.2012.6204523","DOIUrl":"https://doi.org/10.1109/SIU.2012.6204523","url":null,"abstract":"The amplifiers that are used on communication systems in order to increase the productivity, are worked on the nonlinear region. Therefore, digital communication channel can be defined as a Wiener block structure that contains a linear dynamic system and a non-linear static block. In this study, the nonlinear channel equalization problem, a Wiener block structured communication channel is tried to equalize by using a Hammerstein block structure. In order to do that performance of the suggested approach is investigated with LMS and RLS algorithms. The convergence rates of these adaptive algorithms are compared on the real valued data transmission so that LMS algorithm is observed slower convergence but less complex, RLS algorithm is observed much faster convergence rate.","PeriodicalId":256154,"journal":{"name":"2012 20th Signal Processing and Communications Applications Conference (SIU)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123822800","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 : 2012-04-18DOI: 10.1109/SIU.2012.6204419
T. M. Sezgin
Summary form only given. Humans communicate through natural modalities such as speech, sketching, facial expressions and gestures. Even eye-gaze and forces felt through physical interaction supply subtle, but important, bits of information in human-human communication. However, our communication with computers is primarily over ancient hardware such as mice and keyboards. A new generation of user interfaces, called intelligent or natural user interfaces is on the rise. These interfaces advocate smart and natural interaction that are also engaging and fun. In this tutorial, we well briefly survey the filed of intelligent user interfaces, give examples of existing systems. We will discuss supporting technologies (such as classification, regression, computer vision, and tracking), and supporting hardware including haptic interfaces, pen-based devices, camera and microphone arrays. We will also cover interaction design tools, design principles and techniques including wizard-of-oz evaluations, and paper prototypes.
{"title":"Intelligent user interfaces","authors":"T. M. Sezgin","doi":"10.1109/SIU.2012.6204419","DOIUrl":"https://doi.org/10.1109/SIU.2012.6204419","url":null,"abstract":"Summary form only given. Humans communicate through natural modalities such as speech, sketching, facial expressions and gestures. Even eye-gaze and forces felt through physical interaction supply subtle, but important, bits of information in human-human communication. However, our communication with computers is primarily over ancient hardware such as mice and keyboards. A new generation of user interfaces, called intelligent or natural user interfaces is on the rise. These interfaces advocate smart and natural interaction that are also engaging and fun. In this tutorial, we well briefly survey the filed of intelligent user interfaces, give examples of existing systems. We will discuss supporting technologies (such as classification, regression, computer vision, and tracking), and supporting hardware including haptic interfaces, pen-based devices, camera and microphone arrays. We will also cover interaction design tools, design principles and techniques including wizard-of-oz evaluations, and paper prototypes.","PeriodicalId":256154,"journal":{"name":"2012 20th Signal Processing and Communications Applications Conference (SIU)","volume":"48 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131570690","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 : 2012-04-18DOI: 10.1109/SIU.2012.6204684
M. D. Elbi, Aydin Kizilkaya
In this study, the noise cancellation problem on noise corrupted low-frequency signals by using the Empirical Mode Decomposition (EMD) method is considered. For this aim, the Intrinsic Mode (IM) functions of the low-frequency signal corrupted by white Gaussian noise are obtained by applying EMD on this signal. Savitzky-Golay filter and Least Squares Support Vector Machine (LS-SVM) regression are separately applied to the signal reconstructed using the low-frequency ones of the IM functions, and the estimation performance of the original noiseless signal is examined. It is observed from the simulations that a satisfactory result is achieved via LS-SVM regression.
本文研究了利用经验模态分解(EMD)方法对噪声污染的低频信号进行消噪问题。为此，对被高斯白噪声破坏的低频信号进行EMD处理，得到其固有模态函数。分别采用Savitzky-Golay滤波和最小二乘支持向量机(Least Squares Support Vector Machine, LS-SVM)回归对IM函数的低频重构信号进行处理，并检验原始无噪声信号的估计性能。仿真结果表明，LS-SVM回归得到了满意的结果。
{"title":"Noise cancellation on low-frequency signals using Empirical Mode Decomposition","authors":"M. D. Elbi, Aydin Kizilkaya","doi":"10.1109/SIU.2012.6204684","DOIUrl":"https://doi.org/10.1109/SIU.2012.6204684","url":null,"abstract":"In this study, the noise cancellation problem on noise corrupted low-frequency signals by using the Empirical Mode Decomposition (EMD) method is considered. For this aim, the Intrinsic Mode (IM) functions of the low-frequency signal corrupted by white Gaussian noise are obtained by applying EMD on this signal. Savitzky-Golay filter and Least Squares Support Vector Machine (LS-SVM) regression are separately applied to the signal reconstructed using the low-frequency ones of the IM functions, and the estimation performance of the original noiseless signal is examined. It is observed from the simulations that a satisfactory result is achieved via LS-SVM regression.","PeriodicalId":256154,"journal":{"name":"2012 20th Signal Processing and Communications Applications Conference (SIU)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121272729","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 : 2012-04-18DOI: 10.1109/SIU.2012.6204825
M. Yağımlı, I. Altunbas
In this paper, two different physical layer network coding (PLNC) systems that apply antenna selection technique at the relay, consisting of two single-antenna terminals and a multi-antenna relay are proposed. The bound expressions of symbol error rate (SER) of the systems over frequency non-selective and slowly Rayleigh fading channels for M-PSK modulation are derived by using the moment generating function (MGF) method. In addition, Monte Carlo SER simulation results are given for both systems. According to the obtained theoretical and simulation results, diversity order of the systems is equal to the number of total antennas at the relay, and thus it is shown that error performance of the conventional PLNC system is significantly improved by the proposed systems. Also, SER performances of the proposed systems are compared with each other.
{"title":"Physical layer network coding with antenna selection","authors":"M. Yağımlı, I. Altunbas","doi":"10.1109/SIU.2012.6204825","DOIUrl":"https://doi.org/10.1109/SIU.2012.6204825","url":null,"abstract":"In this paper, two different physical layer network coding (PLNC) systems that apply antenna selection technique at the relay, consisting of two single-antenna terminals and a multi-antenna relay are proposed. The bound expressions of symbol error rate (SER) of the systems over frequency non-selective and slowly Rayleigh fading channels for M-PSK modulation are derived by using the moment generating function (MGF) method. In addition, Monte Carlo SER simulation results are given for both systems. According to the obtained theoretical and simulation results, diversity order of the systems is equal to the number of total antennas at the relay, and thus it is shown that error performance of the conventional PLNC system is significantly improved by the proposed systems. Also, SER performances of the proposed systems are compared with each other.","PeriodicalId":256154,"journal":{"name":"2012 20th Signal Processing and Communications Applications Conference (SIU)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128015628","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 : 2012-04-18DOI: 10.1109/SIU.2012.6204520
Huseyin Ozkan, Ozgun S. Pelvan, A. Akman, S. Kozat
In this paper, using “context tree weighting method”, a novel classification algorithm is proposed for real time machine learning applications, which is mathematically shown to be “competitive” with respect to a certain class of algorithms. The computational complexity of our algorithm is independent with the amount of data to be processed and linearly controllable. The proposed algorithm, hence, is highly scalable. In our experiments, our algorithm is observed to provide a comparable classification performance to the Support Vector Machines with Gaussian kernel with 40~1000× computational efficiency in the training phase and 5~35× in the test phase.
{"title":"A novel and incremental classification algorithm","authors":"Huseyin Ozkan, Ozgun S. Pelvan, A. Akman, S. Kozat","doi":"10.1109/SIU.2012.6204520","DOIUrl":"https://doi.org/10.1109/SIU.2012.6204520","url":null,"abstract":"In this paper, using “context tree weighting method”, a novel classification algorithm is proposed for real time machine learning applications, which is mathematically shown to be “competitive” with respect to a certain class of algorithms. The computational complexity of our algorithm is independent with the amount of data to be processed and linearly controllable. The proposed algorithm, hence, is highly scalable. In our experiments, our algorithm is observed to provide a comparable classification performance to the Support Vector Machines with Gaussian kernel with 40~1000× computational efficiency in the training phase and 5~35× in the test phase.","PeriodicalId":256154,"journal":{"name":"2012 20th Signal Processing and Communications Applications Conference (SIU)","volume":"42 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132536784","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 : 2012-04-18DOI: 10.1109/SIU.2012.6204501
I. Tunali, E. Kılıç
Removing the pectoral muscle from the mammogram images is a very important step for computer aided cancer diagnosis methods due to the fact that pectoral muscle having similar properties with the abnormal tissue. This is a hard task since the pectoral muscle can be in various shapes, sizes, and densities. In this paper; firstly Canny edge detection method was used to identify a reference area that covered a certain amount of the pectoral muscle. Afterwards, the average color values of the image remaining in the reference area is found which is converted to the L*a*b* color space before and the distance of all pixels from the this average value is computed. In this new image consisting of color differences, pixels that are close to the mean value are marked as the pectoral muscle. The study was done on 40 mammograms images taken from the Mini-MIAS database. The results obtained were evaluated by an expert radiologist and borders of pectoral muscle taking place in 36 mammograms were determined as acceptable.
{"title":"Detection of pectoral muscle boundary in mammograms","authors":"I. Tunali, E. Kılıç","doi":"10.1109/SIU.2012.6204501","DOIUrl":"https://doi.org/10.1109/SIU.2012.6204501","url":null,"abstract":"Removing the pectoral muscle from the mammogram images is a very important step for computer aided cancer diagnosis methods due to the fact that pectoral muscle having similar properties with the abnormal tissue. This is a hard task since the pectoral muscle can be in various shapes, sizes, and densities. In this paper; firstly Canny edge detection method was used to identify a reference area that covered a certain amount of the pectoral muscle. Afterwards, the average color values of the image remaining in the reference area is found which is converted to the L*a*b* color space before and the distance of all pixels from the this average value is computed. In this new image consisting of color differences, pixels that are close to the mean value are marked as the pectoral muscle. The study was done on 40 mammograms images taken from the Mini-MIAS database. The results obtained were evaluated by an expert radiologist and borders of pectoral muscle taking place in 36 mammograms were determined as acceptable.","PeriodicalId":256154,"journal":{"name":"2012 20th Signal Processing and Communications Applications Conference (SIU)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133616299","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 : 2012-04-18DOI: 10.1109/SIU.2012.6204487
Berkan Dulek, N. D. Vanli, S. Gezici
In this paper, convexity properties of outage probability are investigated under Rayleigh fading for an average power-constrained communications system that employs maximal-ratio combining (MRC) at the receiver. By studying the first and second order derivatives of the outage probability with respect to the transmitted signal power, it is found out that the outage probability is a monotonically decreasing function with a single inflection point. This observation suggests the possibility of improving the outage performance via on-off type power randomization/sharing under stringent average transmit power constraints. It is shown that the results can also be extended to the selection combining (SC) technique in a straightforward manner. Finally, a numerical example is provided to illustrate the theoretical results.
{"title":"Convexity properties of outage probability under rayleigh fading","authors":"Berkan Dulek, N. D. Vanli, S. Gezici","doi":"10.1109/SIU.2012.6204487","DOIUrl":"https://doi.org/10.1109/SIU.2012.6204487","url":null,"abstract":"In this paper, convexity properties of outage probability are investigated under Rayleigh fading for an average power-constrained communications system that employs maximal-ratio combining (MRC) at the receiver. By studying the first and second order derivatives of the outage probability with respect to the transmitted signal power, it is found out that the outage probability is a monotonically decreasing function with a single inflection point. This observation suggests the possibility of improving the outage performance via on-off type power randomization/sharing under stringent average transmit power constraints. It is shown that the results can also be extended to the selection combining (SC) technique in a straightforward manner. Finally, a numerical example is provided to illustrate the theoretical results.","PeriodicalId":256154,"journal":{"name":"2012 20th Signal Processing and Communications Applications Conference (SIU)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133911587","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 : 2012-04-18DOI: 10.1109/SIU.2012.6204703
Orhan Sonmez, A. Cemgil
Most of the state-of-the-art reinforcement learning algorithms are based on Bellman equations and make use of fixed-point iteration methods to converge to suboptimal solutions. However, some of the recent approaches transform the reinforcement learning problem into an equivalent likelihood maximization problem with using appropriate graphical models. Hence, it allows the adoption of probabilistic inference methods. Here, we propose an expectation-maximization method that employs importance sampling in its E-step in order to estimate the likelihood and then to determine the optimal policy.
{"title":"Importance sampling for model-based reinforcement learning","authors":"Orhan Sonmez, A. Cemgil","doi":"10.1109/SIU.2012.6204703","DOIUrl":"https://doi.org/10.1109/SIU.2012.6204703","url":null,"abstract":"Most of the state-of-the-art reinforcement learning algorithms are based on Bellman equations and make use of fixed-point iteration methods to converge to suboptimal solutions. However, some of the recent approaches transform the reinforcement learning problem into an equivalent likelihood maximization problem with using appropriate graphical models. Hence, it allows the adoption of probabilistic inference methods. Here, we propose an expectation-maximization method that employs importance sampling in its E-step in order to estimate the likelihood and then to determine the optimal policy.","PeriodicalId":256154,"journal":{"name":"2012 20th Signal Processing and Communications Applications Conference (SIU)","volume":"30 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122178505","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 : 2012-04-18DOI: 10.1109/SIU.2012.6204807
M. Ersen, Sanem Sariel
In this study, we present how interactions among objects are learned from a given set of actions without any intermediate information about the states of objects. We have used The Incredible Machine game as a suitable test bed to analyze these types of interactions. When a knowledge base about relations among objects is provided, the interactions to devise new plans are learned to a desired extent. Moreover, using spatial information of objects or temporal information of actions makes it feasible to learn the effects of objects on each other. Integrating spatial and temporal data in a spatio-temporal learning approach gives closer results to that of the knowledge-based approach. This is promising because gathering spatio-temporal information does not require great amount of knowledge.
{"title":"Learning interactions among objects through spatio-temporal reasoning","authors":"M. Ersen, Sanem Sariel","doi":"10.1109/SIU.2012.6204807","DOIUrl":"https://doi.org/10.1109/SIU.2012.6204807","url":null,"abstract":"In this study, we present how interactions among objects are learned from a given set of actions without any intermediate information about the states of objects. We have used The Incredible Machine game as a suitable test bed to analyze these types of interactions. When a knowledge base about relations among objects is provided, the interactions to devise new plans are learned to a desired extent. Moreover, using spatial information of objects or temporal information of actions makes it feasible to learn the effects of objects on each other. Integrating spatial and temporal data in a spatio-temporal learning approach gives closer results to that of the knowledge-based approach. This is promising because gathering spatio-temporal information does not require great amount of knowledge.","PeriodicalId":256154,"journal":{"name":"2012 20th Signal Processing and Communications Applications Conference (SIU)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131724557","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 : 2012-04-18DOI: 10.1109/SIU.2012.6204512
K. Küçük, N. Bandirmali, A. Kavak
This paper presents a modified sectoral sweeper based localization estimation (SSLE) method which is improved version of our previously proposed SSLE technique and it's modeling in OPNET. Simplified message formats are required by this technique. Only a central node estimates locations of sensor nodes, which needs to have smart antenna processing capability. The modified SSLE is modeled using OPNET modeler with log-normal shadowing effects. The present OPNET wireless module uses standard log-distance model without any shadowing effects. We add log-normal shadowing effects by providing an user with ability to choose shadowing effects from 0 dB to 5 dB according to the wireless environment. The detailed implementation methodology in OPNET is presented in terms of process models. The performance of modified SSLE is evaluated through different network and channel parameters in terms of localization error and average energy consuming.
{"title":"Using OPNET for performance evaluation of modified SSLE in sensor networks","authors":"K. Küçük, N. Bandirmali, A. Kavak","doi":"10.1109/SIU.2012.6204512","DOIUrl":"https://doi.org/10.1109/SIU.2012.6204512","url":null,"abstract":"This paper presents a modified sectoral sweeper based localization estimation (SSLE) method which is improved version of our previously proposed SSLE technique and it's modeling in OPNET. Simplified message formats are required by this technique. Only a central node estimates locations of sensor nodes, which needs to have smart antenna processing capability. The modified SSLE is modeled using OPNET modeler with log-normal shadowing effects. The present OPNET wireless module uses standard log-distance model without any shadowing effects. We add log-normal shadowing effects by providing an user with ability to choose shadowing effects from 0 dB to 5 dB according to the wireless environment. The detailed implementation methodology in OPNET is presented in terms of process models. The performance of modified SSLE is evaluated through different network and channel parameters in terms of localization error and average energy consuming.","PeriodicalId":256154,"journal":{"name":"2012 20th Signal Processing and Communications Applications Conference (SIU)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133231111","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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