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This paper considers the detection problem and its realistic implementation for multiple-input multiple-output (MIMO) radar with widely separated antennas. In particular, since the range cells of different transmit-receive channels are not in superposition, but intersecting with each other, it is difficult to determine, by gathering measurements from all transmit-receive channels, whether a target...
Atrial Fibrillation (AF) is the most common chronic arrhythmia. Effective detection of the AF would avoid serious consequences like stroke. Conventional AF detection methods need heuristic or hand-craft feature extraction. In this paper, A deep neural network named multi-scale convolutional neural networks (MCNN) based AF detector is proposed. Instant heart rate sequence is extracted from ECG signal,...
Detection with multiple distributions is considered. Rather than formulating the problem with multiple hypotheses, we formulate the problem in a binary hypothesis testing framework by a multiple model approach. Three classes of the Multi-Model Detection (MMD) problems are considered: simplex, compound, and mixture. Three concepts of optimality are given for these three problems, including Uniformly...
Edge detection is one of the most important tasks in image processing and pattern recognition. Edge detector with multiple color channels can provide more edge information. However, the uncertainty occurring with the edge detection in each single channel and the discordance existing in the fusion of multiple channels edge detectors make the detection difficult. In this paper, we propose a new edge...
Multi-resolution grid computation is a technique used to speed up source localization with a Maximum Likelihood Estimation (MLE) algorithm. In the case where the source is located midway between grid points, the MLE algorithm may choose an incorrect location, causing following iterations of the search to close in on an area that does not contain the source. To address this issue, we propose a modification...
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