Pub Date : 2006-04-17DOI: 10.1109/SIU.2006.1659806
O. Kalenderli, B. Bolat, S. Bolat
In this study, a different signal recognition approximation is presented to determine applied voltage value using sound records of the electrical discharges (coronas) by a probabilistic neural network. Sound records are obtained experimentally from the electrical discharges at different 50 Hz AC high-voltage levels. Parts of the recording time on the recorded sound has been used to training and test sets of the probabilistic neural network. One of the goals of this work is to determine voltage value from the sound data, and other is optimization of data and diagnostic for less data used and to find correct voltage value. In the algorithmical method, linear prediction coefficients of the different degrees are used. It is shown that the results can be accepted for the work goals
{"title":"Determination of Voltage Level from Electrical Discharge Sound by Probabilistic Neural Network","authors":"O. Kalenderli, B. Bolat, S. Bolat","doi":"10.1109/SIU.2006.1659806","DOIUrl":"https://doi.org/10.1109/SIU.2006.1659806","url":null,"abstract":"In this study, a different signal recognition approximation is presented to determine applied voltage value using sound records of the electrical discharges (coronas) by a probabilistic neural network. Sound records are obtained experimentally from the electrical discharges at different 50 Hz AC high-voltage levels. Parts of the recording time on the recorded sound has been used to training and test sets of the probabilistic neural network. One of the goals of this work is to determine voltage value from the sound data, and other is optimization of data and diagnostic for less data used and to find correct voltage value. In the algorithmical method, linear prediction coefficients of the different degrees are used. It is shown that the results can be accepted for the work goals","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115764848","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 : 2006-04-17DOI: 10.1109/SIU.2006.1659784
B. Karakaya, H. A. Çırpan, E. Panayirci
Systems employing multiple transmit and receive antennas, known as multiple input multiple output (MIMO) systems can be used with OFDM to improve the resistance to channel impairments. Thus the technologies of OFDM and MIMO are equipped in fixed wireless applications with attractive features, including high data rates and robust performance. However, since different signals are transmitted from different antennas simultaneously, the received signal is the superposition of these signals, which implies new challenges for channel estimation. In this paper we propose a time domain MMSE based channel estimation approach for MIMO-OFDM systems. The proposed approach employs a convenient representation of the discrete multipath fading channel based on the Karhunen-Loeve (KL) orthogonal expansion and finds MMSE estimates of the uncorrelated KL series expansion coefficients. Based on such an expansion, no matrix inversion is required in the proposed MMSE estimator. Also the performance of the proposed approach is studied through the evaluation of minimum Bayesian MSE
{"title":"Channel Estimation for MIMO-OFDM in Fixed Broadband Wireless Applications","authors":"B. Karakaya, H. A. Çırpan, E. Panayirci","doi":"10.1109/SIU.2006.1659784","DOIUrl":"https://doi.org/10.1109/SIU.2006.1659784","url":null,"abstract":"Systems employing multiple transmit and receive antennas, known as multiple input multiple output (MIMO) systems can be used with OFDM to improve the resistance to channel impairments. Thus the technologies of OFDM and MIMO are equipped in fixed wireless applications with attractive features, including high data rates and robust performance. However, since different signals are transmitted from different antennas simultaneously, the received signal is the superposition of these signals, which implies new challenges for channel estimation. In this paper we propose a time domain MMSE based channel estimation approach for MIMO-OFDM systems. The proposed approach employs a convenient representation of the discrete multipath fading channel based on the Karhunen-Loeve (KL) orthogonal expansion and finds MMSE estimates of the uncorrelated KL series expansion coefficients. Based on such an expansion, no matrix inversion is required in the proposed MMSE estimator. Also the performance of the proposed approach is studied through the evaluation of minimum Bayesian MSE","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115325203","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 : 2006-04-17DOI: 10.1109/SIU.2006.1659789
I. Sen, Andreas Akun
Functional near infrared spectroscopy (fNIRS) is an exciting, relatively new method to measure cognitive activity in the brain. Since the method measures blood oxygenation, it can be used for examining the differences between migraineurs and healthy people since migraine is a neurovascular disease. The aim of this study is to inspect the differences in neurovascular dynamics of healthy subjects and migraineurs. To achieve this aim, linear discriminant analysis (LDA) and principal component analysis (PCA) have been applied to acquired fNIRS signals, and parametric classification has been performed to quantify the separability
{"title":"Inspection of Separability of Normal and Migraine fNIRS Data using LDA and PCA","authors":"I. Sen, Andreas Akun","doi":"10.1109/SIU.2006.1659789","DOIUrl":"https://doi.org/10.1109/SIU.2006.1659789","url":null,"abstract":"Functional near infrared spectroscopy (fNIRS) is an exciting, relatively new method to measure cognitive activity in the brain. Since the method measures blood oxygenation, it can be used for examining the differences between migraineurs and healthy people since migraine is a neurovascular disease. The aim of this study is to inspect the differences in neurovascular dynamics of healthy subjects and migraineurs. To achieve this aim, linear discriminant analysis (LDA) and principal component analysis (PCA) have been applied to acquired fNIRS signals, and parametric classification has been performed to quantify the separability","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125608081","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 : 2006-04-17DOI: 10.1109/SIU.2006.1659888
C. Kavlak, I. Tekin
In this work, a 5 GHz radio frequency power amplifier for 802.11a wireless LAN applications has been designed in Austria Micro Systems (AMS) 0.35 mum SiGe BiCMOS (ft=60 GHz) technology. At 5 GHz frequency and 3.3 V supply voltage, output power of 16.364 dBm and power added efficiency (PAE) of 36.819 % are achieved from single discrete SiGe BiCMOS HBT (npn 254H5) with 0.35 mum emitter width. The output 1 dB compression point at 3.3 V is 11.86 dBm with a PAE of 21%
{"title":"5 GHz Power Amplifier Design with AMS 0.35 μm SiGe BiCMOS Technology for IEEE 802.11a WLAN","authors":"C. Kavlak, I. Tekin","doi":"10.1109/SIU.2006.1659888","DOIUrl":"https://doi.org/10.1109/SIU.2006.1659888","url":null,"abstract":"In this work, a 5 GHz radio frequency power amplifier for 802.11a wireless LAN applications has been designed in Austria Micro Systems (AMS) 0.35 mum SiGe BiCMOS (ft=60 GHz) technology. At 5 GHz frequency and 3.3 V supply voltage, output power of 16.364 dBm and power added efficiency (PAE) of 36.819 % are achieved from single discrete SiGe BiCMOS HBT (npn 254H5) with 0.35 mum emitter width. The output 1 dB compression point at 3.3 V is 11.86 dBm with a PAE of 21%","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125840823","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 : 2006-04-17DOI: 10.1109/SIU.2006.1659767
S. Aksoy, Bilgisayar Muihendisligi, Bilkent Universitesi
Content-based retrieval in news video databases has become an important task with the availability of large quantities of data in both public and proprietary archives. We describe a relevance feedback technique that captures the significance of different features at different spatial locations in an image. Spatial content is modeled by partitioning images into non-overlapping grid cells. Contributions of different features at different locations are modeled using weights defined for each feature in each grid cell. These weights are iteratively updated based on user's feedback in terms of positive and negative labeling of retrieval results. Given this labeling, the weight updating scheme uses the ratios of standard deviations of the distances between relevant and irrelevant images to the standard deviations of the distances between relevant images. The proposed technique is quantitatively and qualitatively evaluated using shots related to several sports from the news video collection of the TRECVID video retrieval evaluation where the weights could capture relative contributions of different features and spatial locations
{"title":"Content-Based Retrieval of News Videos Using Relevance Feedback","authors":"S. Aksoy, Bilgisayar Muihendisligi, Bilkent Universitesi","doi":"10.1109/SIU.2006.1659767","DOIUrl":"https://doi.org/10.1109/SIU.2006.1659767","url":null,"abstract":"Content-based retrieval in news video databases has become an important task with the availability of large quantities of data in both public and proprietary archives. We describe a relevance feedback technique that captures the significance of different features at different spatial locations in an image. Spatial content is modeled by partitioning images into non-overlapping grid cells. Contributions of different features at different locations are modeled using weights defined for each feature in each grid cell. These weights are iteratively updated based on user's feedback in terms of positive and negative labeling of retrieval results. Given this labeling, the weight updating scheme uses the ratios of standard deviations of the distances between relevant and irrelevant images to the standard deviations of the distances between relevant images. The proposed technique is quantitatively and qualitatively evaluated using shots related to several sports from the news video collection of the TRECVID video retrieval evaluation where the weights could capture relative contributions of different features and spatial locations","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127242038","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 : 2006-04-17DOI: 10.1109/SIU.2006.1659807
Y. Dedeoglu, B. U. Toreyin, U. Gudukbay, A. E. Cetin
Ozetve Videoda insanlara ve ara,lara kar*ilik gelen hareketli Bu makalede akilli gozetleme sistemleri olu*turulmasina bolgelerin bulunmasi sonraki analiz adimlari i,in odaklanma yardimci olacak, ger,ek zamanda, videoda nesne saglamasi ve yapilacak i,leri azaltmasi bakimindan hemen siniflandirmasi yapabilen bir ornege dayali makina ogrenme hemen turm goruntu i,leme sistemlerinin ilk adimidir. Videoda yontemi sunulmaktadir. Sunulan yontem sabit kamerayla hareketli nesne tespiti dogal sahnelerde meydana gelen ani i*ik izlenen bir alanda bulunan nesnelerin siluetlerinden ve hava durumu degi,imi ve kari*ikliga neden olan tekrar eden yararlanarak nesneleri siniflandirmaktadir. Nesne bolutlemesi hareketler (rulzgarda salinan aga, yapraklari) gibi dinamik i,in uyarlanabilir bir arka plan kestirim modeli degi,ikliklerden dolayi gulvenilir bir ,ekilde ger,ekle,tirilmesi kullanilmaktadir. Nesneleri onceden belirlenmi, insan, insan zor olan bir problemdir. Hareketli nesne tespiti i,in siklikla grubu, ara, siniflarina ayirmak i,in ,ablon e,le,tirmeye dayali kullanilan yontemler arka plan kestirimi, istatistiksel metodlar, bir gudumlu siniflandirma yontemi kullanilmi*tir. zamansal farklama ve optik aki*tir [9, 11, 16, 20, 22]. Videoda tespit edilen hareketli bolgeler ger,ek dulnyada 1. GiriE insanlara, ara,lara, hayvanlara ya da karmakari*ik hareket eden Video kullanarak bir sahnede hareket eden nesneleri aga,, ,ali gibi farkli nesnelere kar*ilik gelir. Tespit edilen siniflandirmak zor oldugu kadar bir,ok uygulama vaadeden nesneyi dulzguln bir ,ekilde takip etmek ve faaliyetlerini saglikli dogurgan bir bilimsel problemdir. Bu problemi qali*maktaki bir ,ekilde ,cozumlemek i,in nesnenin tipini siniflandirmak amacimiz siradan bir goruntuye dayali gozetleme sistemine olduk,a onemlidir. Halihazirda ,ekil tabanli ve hareket tabanli eklenebilecek ger,ek zamanda nesne algilamasi ve olmak uzere iki ,e,it nesne siniflandirma yontemi vardir [22]. siniflandirmasi yapabilecek bir sistem geli,tirmektir. Zamana $ekil tabanli metodlar nesnelerin ku,atan kutusu, alani, bagli video bilgisinin ,oklugunu ve karma*ikligini goz onune siluetleri ve tespit edilen alanin gradyani gibi iki boyutlu alirsak ger,ek zamanda qali*acak bu sistemde kullanilacak bilgilerden yararlanirken; harekete dayali yontemler nesnelerin algoritmalarin ve metodlarin hizli ve gulvenilir qali*masi zamansal olarak izlenenozelliklerinden faydalanirlar. gerekmektedir. Bu bildiride bu ozelliklere sahip, sabit bir [14]'te anlatilan yontemde tespit edilen nesnelerin kamerayla elde edilen siyah beyaz video goruntusu uzerinde siluetlerinin uzunlugu ve alanlari kullanilarak nesneler insan, qali*an bir sistem sunulmaktadir. ara, ve diger grubuna siniflandirilmaktadir. Bu metod Sunulan sistemde, hareketli nesne tespiti i, ve di* insanlarin genel olarak ara,lardan daha ku,cuk olmalari ve mekanlarda ba*ariyla qali*an uyarlanabilir bir arka plan ,ekillerinin daha karma*ik olmasi varsayimina dayanmaktadir. kestirimi metodu
{"title":"Videoda Nesne Siniflandirmasi için Siluet Tabanli Yöntem","authors":"Y. Dedeoglu, B. U. Toreyin, U. Gudukbay, A. E. Cetin","doi":"10.1109/SIU.2006.1659807","DOIUrl":"https://doi.org/10.1109/SIU.2006.1659807","url":null,"abstract":"Ozetve Videoda insanlara ve ara,lara kar*ilik gelen hareketli Bu makalede akilli gozetleme sistemleri olu*turulmasina bolgelerin bulunmasi sonraki analiz adimlari i,in odaklanma yardimci olacak, ger,ek zamanda, videoda nesne saglamasi ve yapilacak i,leri azaltmasi bakimindan hemen siniflandirmasi yapabilen bir ornege dayali makina ogrenme hemen turm goruntu i,leme sistemlerinin ilk adimidir. Videoda yontemi sunulmaktadir. Sunulan yontem sabit kamerayla hareketli nesne tespiti dogal sahnelerde meydana gelen ani i*ik izlenen bir alanda bulunan nesnelerin siluetlerinden ve hava durumu degi,imi ve kari*ikliga neden olan tekrar eden yararlanarak nesneleri siniflandirmaktadir. Nesne bolutlemesi hareketler (rulzgarda salinan aga, yapraklari) gibi dinamik i,in uyarlanabilir bir arka plan kestirim modeli degi,ikliklerden dolayi gulvenilir bir ,ekilde ger,ekle,tirilmesi kullanilmaktadir. Nesneleri onceden belirlenmi, insan, insan zor olan bir problemdir. Hareketli nesne tespiti i,in siklikla grubu, ara, siniflarina ayirmak i,in ,ablon e,le,tirmeye dayali kullanilan yontemler arka plan kestirimi, istatistiksel metodlar, bir gudumlu siniflandirma yontemi kullanilmi*tir. zamansal farklama ve optik aki*tir [9, 11, 16, 20, 22]. Videoda tespit edilen hareketli bolgeler ger,ek dulnyada 1. GiriE insanlara, ara,lara, hayvanlara ya da karmakari*ik hareket eden Video kullanarak bir sahnede hareket eden nesneleri aga,, ,ali gibi farkli nesnelere kar*ilik gelir. Tespit edilen siniflandirmak zor oldugu kadar bir,ok uygulama vaadeden nesneyi dulzguln bir ,ekilde takip etmek ve faaliyetlerini saglikli dogurgan bir bilimsel problemdir. Bu problemi qali*maktaki bir ,ekilde ,cozumlemek i,in nesnenin tipini siniflandirmak amacimiz siradan bir goruntuye dayali gozetleme sistemine olduk,a onemlidir. Halihazirda ,ekil tabanli ve hareket tabanli eklenebilecek ger,ek zamanda nesne algilamasi ve olmak uzere iki ,e,it nesne siniflandirma yontemi vardir [22]. siniflandirmasi yapabilecek bir sistem geli,tirmektir. Zamana $ekil tabanli metodlar nesnelerin ku,atan kutusu, alani, bagli video bilgisinin ,oklugunu ve karma*ikligini goz onune siluetleri ve tespit edilen alanin gradyani gibi iki boyutlu alirsak ger,ek zamanda qali*acak bu sistemde kullanilacak bilgilerden yararlanirken; harekete dayali yontemler nesnelerin algoritmalarin ve metodlarin hizli ve gulvenilir qali*masi zamansal olarak izlenenozelliklerinden faydalanirlar. gerekmektedir. Bu bildiride bu ozelliklere sahip, sabit bir [14]'te anlatilan yontemde tespit edilen nesnelerin kamerayla elde edilen siyah beyaz video goruntusu uzerinde siluetlerinin uzunlugu ve alanlari kullanilarak nesneler insan, qali*an bir sistem sunulmaktadir. ara, ve diger grubuna siniflandirilmaktadir. Bu metod Sunulan sistemde, hareketli nesne tespiti i, ve di* insanlarin genel olarak ara,lardan daha ku,cuk olmalari ve mekanlarda ba*ariyla qali*an uyarlanabilir bir arka plan ,ekillerinin daha karma*ik olmasi varsayimina dayanmaktadir. kestirimi metodu","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125081083","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 : 2006-04-17DOI: 10.1109/SIU.2006.1659875
T.C. Akinci, A. Albora
In recent years, geophysical approaches are being frequently used in modelling and in pre-process before the excavation of archeological ruins. Magnetic approach has been used in the archeological ruins in Sivas-Altinyayla, Turkey. The boundaries of the buried structure is being detected by wavelet methods to the total magnetic anomaly map
{"title":"The Research On The West Side Of The Hittite Emperial Ruins In Sivas-Altinyayla (Kuşakli-Sarissa)","authors":"T.C. Akinci, A. Albora","doi":"10.1109/SIU.2006.1659875","DOIUrl":"https://doi.org/10.1109/SIU.2006.1659875","url":null,"abstract":"In recent years, geophysical approaches are being frequently used in modelling and in pre-process before the excavation of archeological ruins. Magnetic approach has been used in the archeological ruins in Sivas-Altinyayla, Turkey. The boundaries of the buried structure is being detected by wavelet methods to the total magnetic anomaly map","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121949764","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 : 2006-04-17DOI: 10.1109/SIU.2006.1659871
F. Çağlak, A. Albora, O. Ucan
In this paper, we attempted to determine the location of fault zone using the genetic cellular neural network method (G-CNN) in the Thrace and the Marmara Sea regions. G-CNN is a method used to detect specific feature of the 2-D image in the image-processing technique. Genetic algorithm has been used for as learning algorithm in the G-CNN. The G-CNN method has been used for determining the fault zone, as detect regional and residual effect of the gravity anomaly map. Regional anomaly map has been modelled accordingly and compared to the available seismic data. The fault zones in these regions have been determined by way of companion of the fault model with geological data the outcome of which ultimately gives complete accord
{"title":"Determination of the Fault Zone By Using Genetic Celluar Neular Network in the Thrace and the Marmara Sea","authors":"F. Çağlak, A. Albora, O. Ucan","doi":"10.1109/SIU.2006.1659871","DOIUrl":"https://doi.org/10.1109/SIU.2006.1659871","url":null,"abstract":"In this paper, we attempted to determine the location of fault zone using the genetic cellular neural network method (G-CNN) in the Thrace and the Marmara Sea regions. G-CNN is a method used to detect specific feature of the 2-D image in the image-processing technique. Genetic algorithm has been used for as learning algorithm in the G-CNN. The G-CNN method has been used for determining the fault zone, as detect regional and residual effect of the gravity anomaly map. Regional anomaly map has been modelled accordingly and compared to the available seismic data. The fault zones in these regions have been determined by way of companion of the fault model with geological data the outcome of which ultimately gives complete accord","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121801321","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 : 2006-04-17DOI: 10.1109/SIU.2006.1659720
O. Oruc, C.F. Kul, U. Aygolu
In this paper, a two-user cooperative diversity scheme with high rate and low decoding complexity is proposed where the cooperation is performed suitably to Alamouti's space-time block coding technique. The scheme does not require coding or differential modulation and the data bits are directly transmitted by MPSK modulation. The transmitted symbols are detected at the destination without any requirement of the state information of the channels between users and destination. The error performance of the proposed system is evaluated by computer simulations for BPSK modulation in quasi-static Rayleigh fading channel and the results are compared to the corresponding reference systems
{"title":"Differential Detection for Two-User Cooperative Diversity Systems","authors":"O. Oruc, C.F. Kul, U. Aygolu","doi":"10.1109/SIU.2006.1659720","DOIUrl":"https://doi.org/10.1109/SIU.2006.1659720","url":null,"abstract":"In this paper, a two-user cooperative diversity scheme with high rate and low decoding complexity is proposed where the cooperation is performed suitably to Alamouti's space-time block coding technique. The scheme does not require coding or differential modulation and the data bits are directly transmitted by MPSK modulation. The transmitted symbols are detected at the destination without any requirement of the state information of the channels between users and destination. The error performance of the proposed system is evaluated by computer simulations for BPSK modulation in quasi-static Rayleigh fading channel and the results are compared to the corresponding reference systems","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122184262","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 : 2006-04-17DOI: 10.1109/SIU.2006.1659799
M.S. Asian, A. Saranli, B. Baykal
A simulation environment for tracking of maneuvering targets in clutter is developed in MATLAB. The simulation environment allows to generate 2-dimensional surveillance radar measurements and to run various target tracking algorithms on these measurements. As a first simulation example, IMM-NNJPDA algorithm, which incorporates NNJPDA data association and IMM filter structure, is implemented and the performance of this algorithm is investigated in an example scenario. By this simulator, in the future, it is aimed that statistical test and evaluation of different radar sensors, scenarios, target tracking methods and data fusion architectures will be performed
{"title":"Development of a MATLAB Based Target Tracking Simulation Environment","authors":"M.S. Asian, A. Saranli, B. Baykal","doi":"10.1109/SIU.2006.1659799","DOIUrl":"https://doi.org/10.1109/SIU.2006.1659799","url":null,"abstract":"A simulation environment for tracking of maneuvering targets in clutter is developed in MATLAB. The simulation environment allows to generate 2-dimensional surveillance radar measurements and to run various target tracking algorithms on these measurements. As a first simulation example, IMM-NNJPDA algorithm, which incorporates NNJPDA data association and IMM filter structure, is implemented and the performance of this algorithm is investigated in an example scenario. By this simulator, in the future, it is aimed that statistical test and evaluation of different radar sensors, scenarios, target tracking methods and data fusion architectures will be performed","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125246034","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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