Browsing by Subject "Signal detection"
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Item Open Access Adaptive tracking of narrowband HF channel response(Wiley-Blackwell Publishing, 2003) Arikan, F.; Arıkan, OrhanEstimation of channel impulse response constitutes a first step in computation of scattering function, channel equalization, elimination of multipath, and optimum detection and identification of transmitted signals through the HF channel. Due to spatial and temporal variations, HF channel impulse response has to be estimated adaptively. Based on developed state-space and measurement models, an adaptive Kalman filter is proposed to track the HF channel variation in time. Robust methods of initialization and adaptively adjusting the noise covariance in the system dynamics are proposed. In simulated examples under good, moderate and poor ionospheric conditions, it is observed that the adaptive Kalman filter based channel estimator provides reliable channel estimates and can track the variation of the channel in time with high accuracy.Item Open Access Altçizge modellemesi kullanarak kolon bez tespiti(IEEE, 2011-04) Özgül, Etkin Barış; Sökmensüer, C.; Gündüz-Demir, ÇiğdemKolon adenokarsinomu, kolon bez yapılarında değişimlere yol açar. Patologlar bezlerdeki bu değişimleri değerlendirerek kolon adenokarsinom tanı ve derecelendirmesi yaparlar. Ancak değişimlerin değerlendirme süreci kaydadeğer öznellik taşıyabilir. Bezlerin matematiksel özniteliklerle karakterize edilmesiyle bu öznelliği azaltabilmek olasıdır. Bunun içinse ilk aşama, bezlerin yerlerinin otomatik olarak tespit edilmesidir. Literatürdeki bez tespit etme yöntemleri çoğunlukla piksel tabanlıdır. Ancak doku görüntüleri, doğaları gereği ve biyopsi hazırlama ve görüntü alma işlemlerindeki değişkenlik nedeni ile piksel bazında değişkenlik gösterebilir. Öte yandan, bu değişkenliğe rağmen, bezleri oluşturan doku bileşenlerinin uzaysal dağılımı benzer özellik gösterir. Bu dağılımı gözönüne alarak tasarlanan yöntemler, bölütleme başarısını artırma potansiyeline sahiptir. Bu çalışmada önerdiğimiz yöntem, ilk olarak, doku bileşenlerinin dağılımını, bu bileşenler üzerinde oluşturduğu bir çizge ile modeller. Daha sonra, oluşturduğu bu çizgeyi altçizgelere ayırır ve bu altçizgelerin öznitelikleri yardımıyla bezleri tespit eder. Kolon doku görüntüleri üzerinde yaptığımız çalışmalar, önerilen bu yöntemin bezlerin yüksek doğrulukta tespit edilmesinde umut verici sonuçlar verdiğini göstermiştir. The colon adenocarcinoma causes changes in glandular structures of colon tissues. Pathologists assess these changes to diagnose and grade the colon adenocarcinoma. However, this assessment may consist of a considerable amount of subjectivity. It is possible to reduce this subjectivity by characterizing the glands with mathematical features. For that, the first step is to detect gland locations. In literature, most of the gland detection methods are pixel-based. However, tissue images may show pixel-level variances due to their nature and differences in biopsy preparation and image acquisition procedures. On the other hand, in spite of these variances, the distribution of tissue components forming glands show similar properties. The methods that consider this distribution has the potential of improving the performance. The method proposed in this study first models the distribution of the components by constructing a graph on them. Then, it breaks the constructed graph down into subgraphs and detects the glands using the features of these subgraphs. The experiments conducted on colon tissue images show that the proposed method leads to promising results for detecting the glands. © 2011 IEEE.Item Open Access Bağlamsal çıkarımla nesne sezimi(IEEE, 2009-04) Kalaycılar, Fırat; Aksoy, SelimBu bildiride, sezim başarımını arttırmada tek tek sezilmiş nesneler arasındaki bağlamsal ilişkilerden yararlanan bir nesne sezim sistemi tanıtılmaktadır. Bu çalışmadaki ilk katkı, iki boyutlu görüntü uzayında yapılan ölçümlerden olasılıksal çıkarım yaparak nesneler arası gerçek dünya ilişkilerinin (çevresinde, yakınında, üzerinde vb.) modellenmesidir. Diğer bir katkı ise, bireysel nesne etiketlerine ve nesne ikilileri arasındaki ilişkilere bağlı olan sahne olasılık fonksiyonunun enbüyütülerek, nesnelerin en son etiketlerinin atanmasıdır. En tutarlı sahne duzenleşimini bulmak için bu enbüyütme problemi, doğrusal eniyileme kullanılarak çözülmüştür. Ofis görüntüleri içeren iki farklı veri kümesinde yapılan deneylerde, gerçek dünya uzamsal ilişkileri bağlamsal bilgi olarak kullanıldığında genel sezim başarımının arttığı gözlemlenmiştir. In this paper, an object detection system that utilizes contextual relationships between individually detected objects to improve the overall detection performance is introduced. The first contribution in this work is the modelling of real world object relationships (beside, on, near etc.) that can be probabilistically inferred using measurements in the 2D image space. The other contribution is the assignment offinol lobe/s to the detected objects by maximizing a scene probability function that is defined jointly using both individual object labels and their pairwise spatial relationships. The most consistent scene configuration is obtained by solving the maximization problem using linear optimization. Experiments on two different office data sets showed that incorporation of the real world spatial relationships as can textual information improved the overall detection performance. ©2009 IEEE.Item Open Access A blind adaptive decorrelating detector for CDMA systems(1998) Ulukus, S.; Yates, R.D.The decorrelating detector is known to eliminate multiaccess interference when the signature sequences of the users are linearly independent, at the cost of enhancing the Gaussian receiver noise. In this paper, we present a blind adaptive decorrelating detector which is based on the observation of readily available statistics. The algorithm recursively updates the filter coefficients of a desired user by using the output of the current filter. Due to the randomness of the information bits transmitted and the ambient Gaussian channel noise, the filter coefficients evolve stochastically. We prove the convergence of the filter coefficients to a decorrelating detector in the mean squared error (MSE) sense. We develop lower and upper bounds on the MSE of the receiver filter from the convergence point and show that with a fixed step size sequence, the MSE can be made arbitrarily small by choosing a small enough step size. With a time-varying step size sequence, the MSE converges to zero implying an exact convergence. The proposed algorithm is distributed, in the sense that no information about the interfering users such as their signature sequences or power levels is needed. The algorithm requires the knowledge of only two parameters for the construction of the receiver filter of a desired user: the desired user's signature sequence and the variance of the additive white Gaussian (AWG) receiver noise. This detector, for an asynchronous code division multiple access (CDMA) channel, converges to the one-shot decorrelating detector.Item Open Access Çarpıcıdan bağımsız ortak fark matrisi kullanarak video ve görüntü işleme(IEEE, 2009-04) Çetin, A. Enis; Duman, Kaan; Tuna, Hakan; Eryıldırım, AbdulkadirBu bildiride gerçel sayılar üzerinde yarı grup kuran yeni bir iletmen tanımlayarak elde edilen bir bölge betimleyicisi ile hareketli obje takibi, yüz sezimi, plaka bulma, bölge betimleme için kullanılabilecek hızlı bir algoritma sunuyoruz. Bu yeni iletmen hiçbir çarpma gerektirmez. Bu iletmeni kullanarak, imge bölgelerini nitelendiren ve ortak fark adı verilen bir matris tanımlıyoruz. Plaka bulma uygulamasında ortak fark matrislerinı plaka bölgelerinden kestirip, bunları bir veritabanında saklıyoruz. Plaka bölgelerini gerçek zamanlı videoda tanımlamak için ilk önce videodaki hareketli bölgeleri taşıyan imgeleri belirliyoruz, sonra hareketli bölgelerin içinde ya da bütün resim içinde plaka büyüklüğündeki bölgelerin ortak ayrık matrislerini veritabanındaki plaka ortak ayrık matrisleriyle karşılaştırarak bölge içinde plaka olup olmadığını belirliyoruz.Item Open Access Çizge kesit yöntemi ile hiperspektral görüntülerde anomali tabanlı hedef tespiti(IEEE, 2015-05) Batı, E.; Erdinç, Acar; Çeşmeci, D.; Çalışkan, A.; Koz, A.; Aksoy, Selim; Ertürk, S.; Alatan, A. A.Hiperspektral hedef tespiti için yürütülen çalışmalar genel olarak iki sınıfta degerlendirilebilir. İlk sınıf olan anomali tespit yöntemlerinde, hedefin görüntünün geri kalanından farklı oldugu bilgisi kullanılarak görüntü analiz edilmektedir. Diğer sınıfta ise daha önceden bilgisi edinilmiş hedefe ait spektral imza ile görüntüdeki herbir piksel arasındaki benzerlik bulunarak hedefin konumu tespit edimektedir. Her iki sınıf yöntemin de önemli bir dezavantajı hiperspektral görüntü piksellerini bagımsız olarak degerlendirip, aralarındaki komşuluk ilişkilerini gözardı etmesidir. Bu makalede anomali tespit ve imza tabanlı tespit yakla¸sımlarını, pikseller arası komşuluk ilişkilerini de göz önünde bulundurarak birleştiren çizge yaklaşımına dayalı yeni bir yöntem önerilmiştir. Hedeflerin hem imza bilgisine sahip olundugu hem de anomali sayılabilecek ölçülerde olduğu varsayılarak önerilen çizge yaklaşımında önplan için imza bilgisi kullanan özgün bir türev tabanlı uyumlu filtre önerilmiştir. Arkaplan için ise seyreklik bilgisi kullanarak Gauss karışım bileşeni kestirimi yapan yeni bir anomali tespit yöntemi geliştirilmiştir. Son olarak komşular arası benzerligi tanımlamak için ise spektral bir benzerlik ölçütü olan spektral açı eleştiricisi kullanılmıştır. Önerilen çizge tabanlı yöntemin önplan, arkaplan ve komşuluk ilişkilerini uygun şekilde birleştirdigi ve önceki yöntemlere göre hedefi gürültüden arınmış bir bütün şeklinde başarıyla tespit edebildigi gözlemlenmiştir. The studies on hyperspectral target detection until now, has been treated in two approaches. Anomaly detection can be considered as the first approach, which analyses the hyperspectral image with respect to the difference between target and the rest of the hyperspectral image. The second approach compares the previously obtained spectral signature of the target with the pixels of the hyperspectral image in order to localize the target. A distinctive disadvantage of the aforementioned approaches is to treat each pixel of the hyperspectral image individually, without considering the neighbourhood relations between the pixels. In this paper, we propose a target detection algorithm which combines the anomaly detection and signature based hyperspectral target detection approaches in a graph based framework by utilizing the neighbourhood relations between the pixels. Assuming that the target signature is available and the target sizes are in the range of anomaly sizes, a novel derivative based matched filter is first proposed to model the foreground. Second, a new anomaly detection method which models the background as a Gaussian mixture is developed. The developed model estimates the optimal number of components forming the Gaussian mixture by means of utilizing sparsity information. Finally, the similarity of the neighbouring hyperspectral pixels is measured with the spectral angle mapper. The overall proposed graph based method has successfully combined the foreground, background and neighbouring information and improved the detection performance by locating the target as a whole object free from noises. © 2015 IEEE.Item Open Access Clutter detection algorithms for airborne pulse-Doppler radar(IEEE, 2010) Güngör, Ahmet; Gezici, SinanClutter detection is an important stage of target detection. Clutter may not always appear around zero Doppler frequency when realistic terrain models and moving platforms are considered. Two algorithms developed for clutter detection using range-Doppler matrix elements and their performance analysis are presented in this paper. The first algorithm has higher error rates but lower computational complexity whereas the second one has lower error rates but higher computational complexity. The algorithms detect clutter position by filtering range-Doppler matrix elements via non-linear filters. ©2010 IEEE.Item Open Access Compressed sensing on ambiguity function domain for high resolution detection(IEEE, 2010) Güldoǧan, Mehmet B.; Pilancı, Mert; Arıkan, OrhanIn this paper, by using compressed sensing techniques, a new approach to achieve robust high resolution detection in sparse multipath channels is presented. Currently used sparse reconstruction techniques are not immediately applicable in wireless channel modeling and radar signal processing. Here, we make use of the cross-ambiguity function (CAF) and transformed the reconstruction problem from time to delay-Doppler domain for efficient exploitation of the delay-Doppler diversity of the multipath components. Simulation results quantify the performance gain and robustness obtained by this new CAF based compressed sensing approach. ©2010 IEEE.Item Open Access Compressive sensing based target detection in delay-doppler radars(IEEE, 2013) Teke, Oguzhan; Arıkan, Orhan; Gürbüz, A.C.Compressive Sensing theory shows that, a sparse signal can be reconstructed from its sub-Nyquist rate random samples. With this property, CS approach has many applications. Radar systems, which deal with sparse signal due to its nature, is one of the important application of CS theory. Even if CS approach is suitable for radar systems, classical detections schemes under Neyman-Pearson formulations may result high probability of false alarm, when CS approach is used, especially if the target has off-grid parameters. In this study, a new detection scheme which enables CS techniques to be used in radar systems is investigated. © 2013 IEEE.Item Open Access Contact-free measurement of respiratory rate using infrared and vibration sensors(Elsevier BV, 2015) Erden, F.; Alkar, A. Z.; Çetin, A. EnisRespiratory rate is an essential parameter in many practical applications such as apnea detection, patient monitoring, and elderly people monitoring. In this paper, we describe a novel method and a contact-free multi-modal system which is capable of detecting human breathing activity. The multimodal system, which uses both differential pyro-electric infrared (PIR) and vibration sensors, can also estimate the respiratory rate. Vibration sensors pick up small vibrations due to the breathing activity. Similarly, PIR sensors pick up the thoracic movements. Sensor signals are sampled using a microprocessor board and analyzed on a laptop computer. Sensor signals are processed using wavelet analysis and empirical mode decomposition (EMD). Since breathing is almost periodic, a new multi-modal average magnitude difference function (AMDF) is used to detect the periodicity and the period in the processed signals. By fusing the data of two different types of sensors we achieve a more robust and reliable contact-free human breathing activity detection system compared to systems using only one specific type of sensors.Item Open Access Convexity properties of detection probability under additive Gaussian noise: optimal signaling and jamming strategies(IEEE, 2013) Dulek, B.; Gezici, Sinan; Arıkan, OrhanIn this correspondence, we study the convexity properties for the problem of detecting the presence of a signal emitted from a power constrained transmitter in the presence of additive Gaussian noise under the Neyman-Pearson (NP) framework. It is proved that the detection probability corresponding to the α-level likelihood ratio test (LRT) is either strictly concave or has two inflection points such that the function is strictly concave, strictly convex, and finally strictly concave with respect to increasing values of the signal power. In addition, the analysis is extended from scalar observations to multidimensional colored Gaussian noise corrupted signals. Based on the convexity results, optimal and near-optimal time sharing strategies are proposed for average/peak power constrained transmitters and jammers. Numerical methods with global convergence are also provided to obtain the parameters for the proposed strategies.Item Open Access A delay-tolerant asynchronous two-way-relay system over doubly-selective fading channels(Institute of Electrical and Electronics Engineers Inc., 2015) Salim, A.; Duman, T. M.We consider design of asynchronous orthogonal frequency division multiplexing (OFDM) based diamond two-way-relay (DTWR) systems in a time-varying frequency-selective (doubly-selective) fading channel. In a DTWR system, two users exchange their messages with the help of two relays. Most of the existing works on asynchronous DTWR systems assume only small relative propagation delays between the received signals at each node that do not exceed the length of the cyclic-prefix (CP). However, in certain practical communication systems, significant differences in delays may take place, and hence existing solutions requiring excessively long CPs may be highly inefficient. In this paper, we propose a delay-independent CP insertion mechanism in which the CP length depends only on the number of subcarriers and the maximum delay spread of the corresponding channels. We also propose a symbol detection algorithm that is able to tolerate very long relative delays, that even exceed the length of the OFDM block itself, without a large increase in complexity. The proposed system is shown to significantly outperform other alternatives in the literature through a number of specific examples. © 2015 IEEE.Item Open Access Detection of empty hazelnuts from fully developed nuts by impact acoustics(IEEE, 2005) Onaran, İbrahim; Dülek, Berkan; Pearson, T. C.; Yardımcı, Y.; Çetin, A. EnisShell-kernel weight ratio is the main determinate of quality and price of hazelnuts. Empty hazelnuts and nuts containing undeveloped kernels may also contain mycotoxin producing molds, which can cause cancer. A prototype system was set up to detect empty hazelnuts by dropping them onto a steel plate and processing the acoustic signal generated when kernels impact the plate. The acoustic signal was processed by five different methods: 1) modeling of the signal in the time domain, 2) computing time domain signal variances in short time windows, 3) analysis of the frequency spectra magnitudes, 4) maximum amplitude values in short time windows, and 5) line spectral frequencies (LSFs). Support Vector Machines (SVMs) were used to select a subset of features and perform classification. 98% of fully developed kernels and 97% of empty kernels were correctly classified.Item Open Access Detection of epileptic indicators on clinical subbands of EEG(IEEE, 2008-08) Yücel, Zeynep; Özgüler, A. BülentSymptoms of epilepsy, which is characterized by abnormal brain electrical activity, can be observed on electroencephalography (EEG) signal. This paper employs models of chaotic measures on standard clinical subbands of EEG and aims to help detection of epilepsy seizures and diagnosis of epileptic indicators in interictal signals. copyright by EURASIP.Item Open Access Detection of heterogeneous structures using hierarchical segmentation(IEEE, 2011) Akçay, H. Gokhan; Aksoy, SelimWe present an unsupervised hierarchical segmentation algorithm for detecting complex heterogeneous image structures that are comprised of simpler homogeneous primitive objects. The first step segments primitive objects with uniform spectral content. Then, the co-occurrence information between neighboring regions is modeled and clustered. We assume that dense clusters of this co-occurrence space can be considered significant. Finally, the neighboring regions within these clusters are merged to obtain the next level in the segmentation hierarchy. The experiments show that the algorithm that iteratively clusters and merges region groups is able to segment heterogeneous structures in a hierarchical manner. © 2011 IEEE.Item Open Access Detection of insect damaged wheat kernels by impact acoustics(IEEE, 2005-03) Pearson, T. C.; Çetin, A. Enis; Tewfik, A. H.Insect damaged wheat kernels (IDK) are characterized by a small hole bored into the kernel by insect larvae. This damage decreases flour quality as insect proteins interfere with the bread-making biochemistry and insect fragments are very unsightly. A prototype system was set up to detect IDK by dropping them onto a steel plate and processing the acoustic signal generated when kernels impact the plate. The acoustic signal was processed by three different methods: 1) modeling of the signal in the time domain, 2) computing time domain signal variances in short time windows, and 3), analysis of the frequency spectra magnitudes. Linear discriminant analysis was used to select a subset of features and perform classification. 98% of un-damaged kernels and 84.4% of IDK were correctly classified.Item Open Access Diferansiyel PIR algılayıcılarla dalgacık tabanlı alev tespiti(IEEE, 2012-04) Erden, F.; Töreyin, B. U.; Soyer, E. B.; İnaç, İ.; Günay, O.; Köse, K.; Çetin, A. EnisBu makalede, diferansiyel kızılberisi algılayıcı (PIR) kullanılarak geliştirilen bir alev tespit sistemi önerilmektedir. Diferansiyel kızılberisi algılayıcılar, yalnızca görüş alanlarındaki ani sıcaklık değişikliklerine duyarlıdır ve zamanla değişen sinyaller üretir. Algılayıcı sinyaline ait dalgacık dönüşümü, öznitelik çıkarmak için kullanılır ve bu öznitelik vektörü hızlı titreşen kontrolsüz bir ateşin alevi ve bir kişinin yürümesi olaylarıyla eğitilmiş Markov modellerine sokulur. En yüksek olasılıkla sonuçlanan modele karar verilir. Karşılaştırmalı sonuçlar, sistemin geniş odalarda ateş tespiti için kullanılabileceğini düşündürmektedir.Item Open Access EEG sinyallerinde gamma tepkisinin tespiti(IEEE, 2006-04) Tüfekçi, D. İlhan; Karakaş, S.; Arıkan, OrhanIn the detection of the existence of the early gamma response, subjective methods have been used. In this study, an automated gamma detection technique is developed based on the features obtained from the time - frequency representation of the EEG signal in the gamma frequency band. The technique easily discriminates the gamma response existing and non-existing cases for the generated synthetic data. The classification of the technique and that of the expert opinion coincide %77 for real EEG data. © 2006 IEEE.Item Open Access Femtosecond laser fabrication of fiber based optofluidic platform for flow cytometry applications(SPIE, 2017) Serhatlioglu, Murat; Elbuken, Çağlar; Ortac, Bülend; Solmaz, Mehmet E.Miniaturized optofluidic platforms play an important role in bio-analysis, detection and diagnostic applications. The advantages of such miniaturized devices are extremely low sample requirement, low cost development and rapid analysis capabilities. Fused silica is advantageous for optofluidic systems due to properties such as being chemically inert, mechanically stable, and optically transparent to a wide spectrum of light. As a three dimensional manufacturing method, femtosecond laser scanning followed by chemical etching shows great potential to fabricate glass based optofluidic chips. In this study, we demonstrate fabrication of all-fiber based, optofluidic flow cytometer in fused silica glass by femtosecond laser machining. 3D particle focusing was achieved through a straightforward planar chip design with two separately fabricated fused silica glass slides thermally bonded together. Bioparticles in a fluid stream encounter with optical interrogation region specifically designed to allocate 405nm single mode fiber laser source and two multi-mode collection fibers for forward scattering (FSC) and side scattering (SSC) signals detection. Detected signal data collected with oscilloscope and post processed with MATLAB script file. We were able to count number of events over 4000events/sec, and achieve size distribution for 5.95μm monodisperse polystyrene beads using FSC and SSC signals. Our platform shows promise for optical and fluidic miniaturization of flow cytometry systems. © 2017 SPIE.Item Open Access Fizik tedavi egzersizlerinin giyilebilir hareket algılayıcıları işaretlerinden dinamik zaman bükmesiyle sezimi ve değerlendirilmesi(IEEE, 2014-04) Yurtman, Aras; Barshan, BillurGiyilebilir hareket algılayıcılarından kaydedilen sinyalleri işleyerek fizik tedavi egzersizlerini algılamak ve değerlendirmek için özerk bir sistem geliştirilmiştir. Bir fizik tedavi seansındaki bir ya da birden fazla egzersiz tipini algılamak için, temeli dinamik zaman bükmesi (DZB) benzeşmezlik ölçütüne dayanan bir algoritma geliştirilmiştir. Algoritma, egzersizlerin doğru ya da yanlış yapıldığını değerlendirmekte ve varsa hata türünü saptamaktadır. Algoritmanın başarımını degerlendirmek için, beş katılımcı tarafından yapılan sekiz egzersiz hareketinin üç yürütüm türü için birer şablon ve 10’ar sınama yürütümünden oluşan bir veri kümesi kaydedilmiştir. Dolayısıyla, eğitim ve sınama kümelerinde sırasıyla 120 ve 1,200 egzersiz yürütümü bulunmaktadır. Sınama kümesi, boş zaman dilimleri de içermektedir. Öne sürülen algoritma, sınama kümesindeki 1,200 yürütümün % 8.58’ini kaçırmakta ve boş zaman dilimlerinin % 4.91’ini yanlış sezim olarak değerlendirerek toplam 1,125 yürütüm algılamaktadır. Doğruluk, sadece egzersiz sınıflandırması ele alındığında ˘ % 93.46, hem egzersiz hem de yürütüm türü sınıflandırması içinse % 88.65’tir. Sistemin bilinmeyen egzersizlere karşı davranışını sınamak için, algoritma, her egzersiz için, o egzersizin şablonları dışarıda bırakılarak çalıştırılmış ve 1,200 egzersizin sadece 10’u yanlış sezilmiştir. Bu sonuç, sistemin bilinmeyen hareketlere karşı gürbüz olduğunu göstermektedir. Öne sürülen sistem, hem bir fizik tedavi seansının yoğunluğunu kestirmek, hem de hastaya ve fizik tedavi uzmanına geribildirim vermek amacıyla egzersiz hareketlerini değerlendirmek için kullanılabilir.
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