Browsing by Subject "Detectors"

Now showing 1 - 20 of 21

Open Access
Analytic thermal modeling for dc to midrange modulation frequency response for thin film high-Tc superconductive edge-transition bolometers
(OSA Publishing, 2001-03-01) Fardmanesh, M.
Thin-film superconductive edge-transition bolometers are modeled with a one-dimensional analytic thermal model with joule heating, film and substrate materials, and the physical interface effects taken into consideration. The results from the model agree well with the experimental results of samples made of large-meander-line Yba(2)Cu(3)O(7-x) films on crystalline SrTiO3, LaAlO3, and MgO substrates up to 100 kHz, the limits of the experimental setup. Compared with the results of the SrTiO3 substrate samples, the results from the model of the LaAlO3 and the MgO substrate samples deviate slightly from the measured values at very low modulation frequencies (below similar to 10 Hz). The deviation increases for higher thermal-conductive substrate materials. When the model was used, the substrate absorption and the thermal parameters of the devices could also be investigated. (C) 2001 Optical Society of America
Open Access
Detector randomization and stochastic signaling for minimum probability of error receivers
(Institute of Electrical and Electronics Engineers, 2012) Dulek, B.; Gezici, Sinan
Optimal receiver design is studied for a communications system in which both detector randomization and stochastic signaling can be performed. First, it is proven that stochastic signaling without detector randomization cannot achieve a smaller average probability of error than detector randomization with deterministic signaling for the same average power constraint and noise statistics. Then, it is shown that the optimal receiver design results in a randomization between at most two maximum a-posteriori probability (MAP) detectors corresponding to two deterministic signal vectors. Numerical examples are provided to explain the results.
Open Access
Effects of additional independent noise in binary composite hypothesis-testing problems
(IEEE, 2009-09) Bayram, Suat; Gezici, Sinan
Performance of some suboptimal detectors can be improved by adding independent noise to their observations. In this paper, the effects of adding independent noise to observations of a detector are investigated for binary composite hypothesistesting problems in a generalized Neyman-Pearson framework. Sufficient conditions are derived to determine when performance of a detector can or cannot be improved via additional independent noise. Also, upper and lower limits are derived on the performance of a detector in the presence of additional noise, and statistical characterization of optimal additional noise is provided. In addition, two optimization techniques are proposed to calculate the optimal additional noise. Finally, simulation results are presented to investigate the theoretical results. © 2009 IEEE.
Open Access
Mesoscopic Fano effect in an Aharonov-Bohm interferometer Coulomb-coupled to a nearby quantum dot
(Wiley, 2007) Tolea, M.; Moldoveanu, V.; Tanatar, Bilal
Motivated by the pionieering experiments of Buks et al. [Nature 391, 871 (1998)] we investigate the visibility of the Fano effect in a single-dot Aharonov-Bohm interferometer which is Coulomb-coupled to a nearby quantum dot. The latter acts as a 'Which Path Detector' and is coupled to two leads on which a finite bias is applied. Using the non-equilibrium Keldysh-Green function formalism we compute the currents through the detector and the interferometer. We take into account the first two contributions to the interaction selfenergy and emphasize the correction to the Landauer formula which appears beyond the single-particle approximation. Particular attention is given to the coherence properties of the interferometer in the presence of the electron-electron interaction between the embedded dot and the detector. We show that when the detector is subjected to a finite bias the amplitude of Aharonov-Bohm oscillations of the current through the interferometer decreases. The Fano line is in turn rather stable under interaction. Our results generalize an earlier work of Silva and Levit [Phys. Rev. B 63, 201309 (2001)] and complement the existing description of the controlled dephasing.
Open Access
A multi-modal video analysis approach for car park fire detection
(Elsevier, 2013) Verstockt, S.; Hoecke, S. V.; Beji, T.; Merci, B.; Gouverneur, B.; Çetin, A. Enis; Potter, P. D.; Walle, R. V. D.
In this paper a novel multi-modal flame and smoke detector is proposed for the detection of fire in large open spaces such as car parks. The flame detector is based on the visual and amplitude image of a time-of-flight camera. Using this multi-modal information, flames can be detected very accurately by visual flame feature analysis and amplitude disorder detection. In order to detect the low-cost flame related features, moving objects in visual images are analyzed over time. If an object possesses high probability for each of the flame characteristics, it is labeled as candidate flame region. Simultaneously, the amplitude disorder is also investigated. Also labeled as candidate flame regions are regions with high accumulative amplitude differences and high values in all detail images of the amplitude image's discrete wavelet transform. Finally, when there is overlap of at least one of the visual and amplitude candidate flame regions, fire alarm is raised. The smoke detector, on the other hand, focuses on global changes in the depth images of the time-of-flight camera, which do not have significant impact on the amplitude images. It was found that this behavior is unique for smoke. Experiments show that the proposed detectors improve the accuracy of fire detection in car parks. The flame detector has an average flame detection rate of 93%, with hardly any false positive detection, and the smoke detection rate of the TOF based smoke detector is 88%.
Open Access
Noise enhanced detection in multiple-access environments
(IEEE, 2009) Bayram, Suat; Gezici, Sinan
Under certain conditions, addition of noise can enhance performance of suboptimal detectors, which is called the stochastic resonance (SR) effect. In this paper, the effects of SR are investigated for conventional detectors in the presence of multiple-access interference. First, conditions under which probability of error performance of the detector can or cannot be improved are obtained. Then, performance of noise enhanced detectors are analyzed, and an upper bound on the amount of performance improvement that can be obtained via SR is derived. Numerical examples are presented to support the theoretical analysis.
Open Access
Noise enhanced detection in restricted Neyman-Pearson framework
(IEEE, 2012-06) Bayram, S.; Gültekin, San; Gezici, Sinan
Noise enhanced detection is studied for binary composite hypothesis-testing problems in the presence of prior information uncertainty. The restricted Neyman-Pearson (NP) framework is considered, and a formulation is obtained for the optimal additive noise that maximizes the average detection probability under constraints on worst-case detection and false-alarm probabilities. In addition, sufficient conditions are provided to specify when the use of additive noise can or cannot improve performance of a given detector according to the restricted NP criterion. A numerical example is presented to illustrate the improvements obtained via additive noise. © 2012 IEEE.
Open Access
Noise enhanced detection in the restricted Bayesian framework
(IEEE, 2010) Bayram, Suat; Gezici, Sinan; Poor H.V.
Effects of additive independent noise are investigated for sub-optimal detectors according to the restricted Bayes criterion. The statistics of optimal additive noise are characterized. Also, sufficient conditions for improvability or nonimprovability of detection via additive noise are obtained. A detection example is presented to study the theoretical results. ©2010 IEEE.
Open Access
Noise-enhanced M-ary hypothesis-testing in the minimax framework
(IEEE, 2009-09) Bayram, Suat; Gezici, Sinan
In this study, the effects of adding independent noise to observations of a suboptimal detector are studied for M-ary hypothesis-testing problems according to the minimax criterion. It is shown that the optimal additional noise can be represented by a randomization of at most M signal values under certain conditions. In addition, a convex relaxation approach is proposed to obtain an accurate approximation to the noise probability distribution in polynomial time. Furthermore, sufficient conditions are presented to determine when additional noise can or cannot improve the performance of a given detector. Finally, a numerical example is presented. © 2009 IEEE.
Open Access
Optimal channel switching for average capacity maximization
(IEEE, 2014-05) Sezer, Ahmet Dündar; Gezici, Sinan; İnaltekin, H.
Optimal channel switching is proposed for average capacity maximization in the presence of average and peak power constraints. A necessary and sufficient condition is derived in order to determine when the proposed optimal channel switching approach can or cannot outperform the optimal single channel approach, which performs no channel switching. Also, it is stated that the optimal channel switching solution can be realized by channel switching between at most two different channels. In addition, a low-complexity optimization problem is derived in order to obtain the optimal channel switching solution. Numerical examples are provided to exemplify the derived theoretical results. © 2014 IEEE.
Open Access
Optimal channel switching in the presence of stochastic signaling
(IEEE, 2013) Dulek, B.; Varshney P.K.; Tutay, Mehmet Emin; Gezici, Sinan
Optimal channel switching and detector design is studied for M-ary communication systems in the presence of stochastic signaling, which facilitates randomization of signal values transmitted for each information symbol. Considering the presence of multiple additive noise channels (which can have non-Gaussian distributions in general) between a transmitter and a receiver, the joint optimization of the channel switching (timesharing) strategy, stochastic signals, and detectors is performed in order to achieve the minimum average probability of error. It is proved that the optimal solution to this problem corresponds to either (i) switching between at most two channels with deterministic signaling over each channel, or (ii) time-sharing between at most two different signals over a single channel (i.e., stochastic signaling over a single channel). For both cases, the optimal solutions are shown to employ corresponding maximum a posteriori probability (MAP) detectors at the receiver. Numerical results are presented to investigate the proposed approach. © 2013 IEEE.
Open Access
Optimal detector randomization for multiuser communications systems
(IEEE, 2013) Tutay, M. E.; Gezici, Sinan; Arıkan, Orhan
Optimal detector randomization is studied for the downlink of a multiuser communications system, in which users can perform time-sharing among multiple detectors. A formulation is provided to obtain optimal signal amplitudes, detectors, and detector randomization factors. It is shown that the solution of this joint optimization problem can be calculated in two steps, resulting in significant reduction in computational complexity. It is proved that the optimal solution is achieved via randomization among at most min{K, Nd} detector sets, where K is the number of users and Nd is the number of detectors at each receiver. Lower and upper bounds are derived on the performance of optimal detector randomization, and it is proved that the optimal detector randomization approach can reduce the worst-case average probability of error of the optimal approach that employs a single detector for each user by up to K times. Various sufficient conditions are obtained for the improvability and nonimprovability via detector randomization. In the special case of equal crosscorrelations and noise powers, a simple solution is developed for the optimal detector randomization problem, and necessary and sufficient conditions are presented for the uniqueness of that solution. Numerical examples are provided to illustrate the improvements achieved via detector randomization.
Open Access
Optimal detector randomization in cognitive radio systems in the presence of imperfect sensing decisions
(2014) Sezer, A. D.; Gezici, Sinan; Gursoy, M. C.
In this study, optimal detector randomization is developed for secondary users in a cognitive radio system in the presence of imperfect spectrum sensing decisions. It is shown that the minimum average probability of error can be achieved by employing no more than four maximum a-posteriori probability (MAP) detectors at the secondary receiver. Optimal MAP detectors and generic expressions for their average probability of error are derived in the presence of possible sensing errors. Also, sufficient conditions are presented related to improvements due to optimal detector randomization.
Open Access
Optimal signaling and detector design for power constrained on-off keying systems in Neyman-Pearson framework
(IEEE, 2011) Dulek, Berkan; Gezici, Sinan
Optimal stochastic signaling and detector design are studied for power constrained on-off keying systems in the presence of additive multimodal channel noise under the Neyman-Pearson (NP) framework. The problem of jointly designing the signaling scheme and the decision rule is addressed in order to maximize the probability of detection without violating the constraints on the probability of false alarm and the average transmit power. Based on a theoretical analysis, it is shown that the optimal solution can be obtained by employing randomization between at most two signal values for the on-signal (symbol 1) and using the corresponding NP-type likelihood ratio test at the receiver. As a result, the optimal parameters can be computed over a significantly reduced optimization space instead of an infinite set of functions using global optimization techniques. Finally, a detection example is provided to illustrate how stochastic signaling can help improve detection performance over various optimal and sub-optimal signaling schemes. © 2011 IEEE.
Open Access
Optimal stochastic signal design and detector randomization in the Neyman-Pearson framework
(IEEE, 2012-03) Dülek, Berkan; Gezici, Sinan
Power constrained on-off keying communications systems are investigated in the presence of stochastic signaling and detector randomization. The joint optimal design of decision rules, stochastic signals, and detector randomization factors is performed. It is shown that the solution to the most generic optimization problem that employs both stochastic signaling and detector randomization can be obtained as the randomization among no more than three Neyman-Pearson (NP) decision rules corresponding to three deterministic signal vectors. Numerical examples are also presented. © 2012 IEEE.
Open Access
Scheduling beams with different priorities on a military surveillance radar
(Institute of Electrical and Electronics Engineers, 2012) Taner, M. R.; Karasan O. E.; Yavuzturk, E.
The problem of scheduling the searching, verification, and tracking tasks of a ground based, three-dimensional military surveillance radar is studied. Although the radar is mechanically steered in the sense that a servomechanism rotates the antenna at a constant turn rate, it has limited electronic steering capability in azimuth. The scheduling problem arises within a planning period during which the antenna scans a given physical range. A task/job corresponds to sending a transmission beam to hit a particular target. Targets are allowed to be hit with an angular deviation up to a predetermined magnitude. The steering mechanism of the radar helps alter these deviations by imposing a scan-off angle from broadside on the transmission beam. A list of jobs along with their priority weights, processing times, and ideal beam positions are given during a predetermined planning period. The ideal beam position for a given job allows hitting the corresponding target with zero deviation. Each job also has a set of available scan-off angles. It is possible to map the antennas physical position, beam positions, scan-off angles, and angular deviations to a time scale. The goal is to select the subset of jobs to be processed during the given planning period and determining the starting time and scan-off angle for each selected job. The objectives are to simultaneously minimize the weighted number of unprocessed jobs and the total weighted deviation. An integer programming model and two versions of a heuristic mechanism that relies on the exact solution of a special case are proposed. Results of a computational study are presented.
Open Access
Small moving object detection in video sequences
(IEEE, 2000-06) Zaibi, Rabi; Çetin, A. Enis; Yardımcı, Y.
In this paper, we propose a method for detection of small moving objects in video. We first eliminate the camera motion using motion compensation. We then use an adaptive predictor to estimate the current pixel using neighboring pixels in the motion compensated image and, in this way, obtain a residual error image. Small moving objects appear as outliers in the residual image and are detected using a statistical Gaussianity detection test based on higher order statistics. It turns out that in general, the distribution of the residual error image pixels is almost Gaussian. On the other hand, the distribution of the pixels in the residual image deviates from Gaussianity in the existence of outliers. Simulation examples are presented.
Open Access
Stochastic resonance in binary composite hypothesis-testing problems in the Neyman-Pearson framework
(Elsevier, 2012-02-20) Bayram, S.; Gezici, Sinan
Performance of some suboptimal detectors can be enhanced by adding independent noise to their inputs via the stochastic resonance (SR) effect. In this paper, the effects of SR are studied for binary composite hypothesis-testing problems. A Neyman-Pearson framework is considered, and the maximization of detection performance under a constraint on the maximum probability of false-alarm is studied. The detection performance is quantified in terms of the sum, the minimum, and the maximum of the detection probabilities corresponding to possible parameter values under the alternative hypothesis. Sufficient conditions under which detection performance can or cannot be improved are derived for each case. Also, statistical characterization of optimal additive noise is provided, and the resulting false-alarm probabilities and bounds on detection performance are investigated. In addition, optimization theoretic approaches to obtaining the probability distribution of optimal additive noise are discussed. Finally, a detection example is presented to investigate the theoretical results.
Open Access
A survey on optimal stochastic signaling and detector randomization
(IEEE, 2011) Dülek, Berkan; Göken, Çağrı; Gezici, Sinan; Arıkan, Orhan
In this paper, a survey on stochastic signaling and detector randomization is presented for average power-constrained binary communications systems. First, the case of a single fixed detector at the receiver is considered, and then the joint design of detector and optimal signaling is studied. In addition, the optimal receiver design is examined in the presence of detector randomization and stochastic signaling. It is observed that the average probability of error achieved via detector randomization cannot be larger than that achieved via stochastic signaling in the presence of optimal MAP detectors. Finally, a numerical study is presented to illustrate an example.
Open Access
Video copy detection using multiple visual cues and MPEG-7 descriptors
(Academic Press, 2010) Küçüktunç, O.; Baştan M.; Güdükbay, Uğur; Ulusoy, Özgür
We propose a video copy detection framework that detects copy segments by fusing the results of three different techniques: facial shot matching, activity subsequence matching, and non-facial shot matching using low-level features. In facial shot matching part, a high-level face detector identifies facial frames/shots in a video clip. Matching faces with extended body regions gives the flexibility to discriminate the same person (e.g., an anchor man or a political leader) in different events or scenes. In activity subsequence matching part, a spatio-temporal sequence matching technique is employed to match video clips/segments that are similar in terms of activity. Lastly, the non-facial shots are matched using low-level MPEG-7 descriptors and dynamic-weighted feature similarity calculation. The proposed framework is tested on the query and reference dataset of CBCD task of TRECVID 2008. Our results are compared with the results of top-8 most successful techniques submitted to this task. Promising results are obtained in terms of both effectiveness and efficiency. © 2010 Elsevier Inc. All rights reserved.