Results 251 to 260 of about 880,054 (288)
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2016 IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW), 2016
The article considers the development of an algorithm to detect targets in the presence of noise radar method using accumulation between periods.
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The article considers the development of an algorithm to detect targets in the presence of noise radar method using accumulation between periods.
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TEAM: ThrEshold Adaptive Memristor Model
IEEE Transactions on Circuits and Systems I: Regular Papers, 2013Memristive devices are novel devices, which can be used in applications ranging from memory and logic to neuromorphic systems. A memristive device offers several advantages: nonvolatility, good scalability, effectively no leakage current, and compatibility with CMOS technology, both electrically and in terms of manufacturing.
Shahar Kvatinsky +3 more
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Wavelet thresholding and adaptation
1998This chapter treats in more detail the adaptivity property of nonlinear (thresholded) wavelet estimates. We first introduce different modifications and generalizations of soft and hard thresholding. Then we develop the notion of adaptive estimators and present the results about adaptivity of wavelet thresholding for density estimation problems. Finally,
Wolfgang Härdle +3 more
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Adaptive thresholding for scene change detection
2013 IEEE Third International Conference on Consumer Electronics ¿ Berlin (ICCE-Berlin), 2013Increasing the demands of digital video by developing the Internet market and the multimedia technologies, video indexing technique such as scene change detection is required to manage the data efficiently. In conventional methods, scene change is detected by comparing the value of current detected measure with the fixed threshold induced from ...
Soongi Hong, Beobkeun Cho, Yoonsik Choe
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Analysis of an Adaptive Threshold Logic Unit
IEEE Transactions on Computers, 1970In this paper an adaptive threshold logic unit is analyzed. The unit consists of a set of self-adjusting weights, a summing device, and a comparator. Its dynamic and steady-state behavior is made clear by investigating the solutions of a system of nonlinear differential equations which describes changes in the weights.
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IEEE Transactions on Aerospace and Electronic Systems, 1977
The conditions under which adaptive thesholding should be employed are discussed. The three most important systems for accomplishing adaptive thresholding are the level adjuster, the constant-fraction discriminator, and the double differentiator. Practical implementations of these systems, including false alarm protection, are described in terms of ...
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The conditions under which adaptive thesholding should be employed are discussed. The three most important systems for accomplishing adaptive thresholding are the level adjuster, the constant-fraction discriminator, and the double differentiator. Practical implementations of these systems, including false alarm protection, are described in terms of ...
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Adaptive estimation of inlier and outlier threshold
2013 10th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), 2013One of the main problems relating RANSAC estimation is to determine the inlier threshold adaptively depending on the variance of inliers. In this paper, we propose a novel method that estimates the inlier threshold adaptively from the observations, giving a threshold-free RANSAC.
Jae-Yeong Lee, Wonpil Yu
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Adaptive estimation with soft thresholding penalties
Statistica Neerlandica, 2002We show that various robust nonparametric regression estimators, such as the least absolute deviations estimator, can be made adaptive (up to logarithmic factors), by adding a soft thresholding type penalty to the loss function. As an example, we consider the situation where the roughness of the regression function is described by a single parameter p.
Loubes, Jean-Michel, van de Geer, Sara
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Adaptive estimation of the threshold point in threshold regression
Journal of Econometrics, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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ADAPT: Adaptive Thresholds for Feature Extraction
2017Threshold-based feature definitions remain one of the most widely used and most intuitive choice in a wide range of scientific areas. However, it is well known that in many applications selecting a single optimal threshold is difficult or even impossible.
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