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This approach designs a deep neural network structure to provide a specific form of the nonlinear detector and trains the DNN model with knowledge of target ...
In this paper, by generalizing the classical constrained energy mini- mization (CEM) method, and considering the feature auto-extraction ability of deep neural ...
Constrained Energy Minimization with a DNN Detector. Xiaoli Yang 1. ,. Min Zhao 1. ,. Shuaikai Shi 1. ,. Jie Chen 1. Show full list: 4 authors. Hide authors ...
Constrained energy minimization (CEM) method is designed to minimize overall energy output at the constraint of priori target spectrum, highlighting the targets ...
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In this work, we propose a nonlinear detector formulation by generalizing the conventional constrained energy minimization (CEM) method, and then design novel ...
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CONSTRAINED ENERGY MINIMIZATION WITH A DNN DETECTOR · 1: RESEARCH OF FAST-ICA ALGORITHM AND ITS IMPROVEMENT · 2: OMNIDIRECTIONAL MIRROR GRADIENT DISSIMILARITY FOR ...
In this paper, we propose the Multiple Targets Inequality Constrained Energy Minimization (MTICEM) method to overcome the drawback of MTCEM.
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The Constrained Energy Minimization (CEM) [2,10] detection algorithm builds a linear filter that minimizes the total spectral output energy under the constraint ...
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Feb 2, 2022 · We propose an ensemble learning-based multi-objective constrained energy minimization (E-IMTCEM) for hyperspectral multi-target detection in this paper.
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Investigation of a kernel-based CEM, called Kernel CEM (K-CEM), which employs various kernels to expand the original data space to a higher dimensional ...