Results 221 to 230 of about 553,105 (269)

Optimal Detector Randomization in Cognitive Radio Systems in the Presence of Imperfect Sensing Decisions [PDF]

IEEE Communications Letters, 2014
In this study, optimal detector randomization is developed for secondary users in a cognitive radio system in the presence of imperfect spectrum sensing decisions.
Ahmet Sezer, Sinan Gezici, M Cenk Gursoy   +2 more
exaly   +2 more sources

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Low rank detectors for Gaussian random vectors

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1987
A constructive procedure is presented for designing low rank detectors which maximize the divergence between hypotheses about the covariance structure of Gaussian signals. The detectors are constructed from the eigenstructure of a "signal-to-noise ratio" matrix.
Louis L. Scharf, Barry D. Van Veen
openaire   +2 more sources

On Four Suboptimal Quadratic Detectors for Random Signals

IEICE Transactions on Communications, 2005
This paper tackles the problem of detecting a random signal embedded in additive white noise. Although the likelihood ratio test (LRT) is the well-known optimum detector for this problem, it may not be easily realized in applications such as radar, sonar, seismic, digital communications, speech analysis and automatic fault detection in machinery, for ...
H. C. SO, W. K. MA, A. FARINA, GINI, FULVIO, W. Y. TSUI   +4 more
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Array Detectors for Random Signals in Noise

IEEE Transactions on Sonics and Ultrasonics, 1976
Two schemes for the detection of a common random signal in an array of receivers with independent noise processes are considered. A nonparametric array detector using the Wilcoxon signed-rank statistic and a robust array detector extendingthe binary quantization of polarity coincidence arrays are described and analyzed for performance.
S.A. Kassam, J.B. Thomas
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Signal detectors for random ocean media

The Journal of the Acoustical Society of America, 1992
This paper reports on acoustic signal detection in a stationary random multipath environment. The multipath transmission channel is modeled considering that both multipath time delay and attenuation coefficients characterizing the emitter/receiver transfer function are random variables with an a priori given distribution. Under the above condition, and
Isabel M. G. Lourtie, G. Clifford Carter
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Randomized Approach to Nonlinear Inversion Combining Random and Optimized Simultaneous Sources and Detectors

SIAM Journal on Scientific Computing, 2019
Summary: In partial differential equation-based (PDE-based) inverse problems with many measurements, many large-scale discretized PDEs must be solved for each evaluation of the misfit or objective function. In the nonlinear case, evaluating the Jacobian requires solving an additional set of systems.
Selin S. Aslan, Eric de Sturler, Misha E. Kilmer   +2 more
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Randomized Spectrum Transformations for Adapting Object Detector in Unseen Domains

IEEE Transactions on Image Processing, 2023
We propose a Meta Learning on Randomized Transformations (MLRT) to learn domain invariant object detectors. Domain generalization is a problem about learning an invariant model from multiple source domains which can generalize well on unseen target domains.
Lei Zhang 0038, Lingyun Qin, Mingjun Xu, Weijie Chen 0006, Shiliang Pu, Wensheng Zhang 0002   +5 more
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Random-Selection-Based Anomaly Detector for Hyperspectral Imagery

IEEE Transactions on Geoscience and Remote Sensing, 2011
Anomaly detection in hyperspectral images is of great interest in the target detection domain since it requires no prior information and makes full use of the spectral differences revealed in hyperspectral images. The current anomaly detection methods are susceptible to anomalies in the processing window range or the image scope.
Bo Du 0001, Liangpei Zhang 0001
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Randomized SUSAN edge detector

Optical Engineering, 2011
A speed up technique for the SUSAN edge detec- tor based on random sampling is proposed. Instead of sliding the mask pixel by pixel on an image as the SUSAN edge detector does, the proposed scheme places the mask ran- domly on pixels to find edges in the image; we hereby name it randomized SUSAN edge detector (R-SUSAN).
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Randomized Low-Rank Nonlinear RX Detector

2023
Anomaly Detection is an important topic in various application areas, including image analysis and network intrusion detection. The Reed–Xiaoli (RX) detector is an efficient and accurate anomaly detector that can be used if analyzed data is Gaussian distributed. However, in the real-world, data is rarely Gaussian distributed. For nonlinear data, kernel
Selçuk Yapıcı, Fatih Nar
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