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This paper performs further improvement to a distributed algorithm for solving linear algebraic equations via multi-agent networks recently developed by Mou et al., in which all agents’ states converge exponentially fast to the same solution to a group of linear equations by assuming each agent knows only part of the linear equations and its nearby neighbors’ states. We first prove that the algorithm...
A novel version of multi-class classification method based on fruit fly optimization algorithm (FOA) and relevance vector machine (RVM) is proposed. The one-against-one-against-rest (OAOAR) classification model based on the traditional one-against-one (OAO) and one-against-rest (OAR) algorithm is aimed at combining the advantages of them and translates the multi-class classification problem into multiple...
In order to solve the failure prognostics problem of electronic system, a method of fast relevance vector machine (FRVM) based on improved fruit fly optimization algorithm (FOA) is proposed. Grey data generation operation is introduced to process the original data and the output data for enhancing the regularity and reducing the randomness. Furthermore, the kernel function parameter of FRVM model...
With the rapid accumulation of high dimensional data, dimensionality reduction plays a more and more important role in practical data processing and analysing tasks. This paper studies semi-supervised dimensionality reduction using pair wise constraints. In this setting, domain knowledge is given in the form of pair wise constraints, which specifies whether a pair of instances belong to the same class...
This paper presents a novel multi-features fusion tracking algorithm based on local kernels learning. Histograms of multiple features are extracted based on sub image patches within the target region, and the features fusion weights are calculated respectively for each patch according to the discriminability of features. It means that the same feature employed in different sub image patches gets different...
The main purpose of the paper is to settle the stochastic linear quadratic control problem for systems with multiple input-delays (SDLQ) which is very intractable and remains to be solved. We introduce a different version of stochastic discrete-time maximum principle (SDMP) where it is shown that the auxiliary variable depends on the optimal system state through a stochastic matrix and the expectation...
Protein secondary structure prediction is an important step to understanding protein tertiary structure. Recent studies indicate that the correlation between neighboring secondary structures are beneficial to improve prediction performance. In this paper, we propose a new large margin approach for protein secondary structure prediction, which consider the problem as a sequence labeling problem like...
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