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In this paper, we propose a novel semisupervised Gaussian regression approach for the estimation of biophysical parameters from remote sensing data with limited training samples. During the learning phase, unlabeled samples are exploited to inflate the training set. The estimation of the targets associated with these samples is carried out by solving an optimization problem formulated within a genetic...
Orthogonal frequency division multiplexing (OFDM) has attracted much attention in wireless communications due to its many advantages. However, OFDM is very sensitive to carrier frequency offset (CFO) which can destroy the orthogonality among subchannels. For OFDMA uplink systems with generalized carrier assignment scheme (GCAS), there are multiple CFOs need to be estimated simultaneously. While ML...
Diversity maintenance of solutions is a crucial part in multi-objective optimization. However, most of existing studies show a good distribution with a large computational load or a comparative bad distribution quickly. In this paper, a method for pruning a set of non-dominated solutions using a spanning tree is proposed. This approach defines a density estimation metric - spanning tree crowding distance...
In order to design a multi-agent system with required emergent phenomena, evolutionary optimization can be used. The downside of this approach is large time needed to perform optimization due to the simulation of the multi-agent system that has to be carried out every time fitness function is evaluated. In the case when a single simulation result is not reliable, more than one simulation has to be...
Based upon the AMSAA model which has been widely used in engineering, a method of defining the time environmental conversion factor was proposed through optimization process, which made full used of the failure data from the same kind of products or the similar products in their development tests, and it made all the development test items into s few typical environment stress types in case the development...
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