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In this paper, we propose a multiclass classifier training method which reduces “fatal” misclassifications by cost-relaxation of “tolerable” misclassifications in one-against-all classifiers training, named misclassification tolerable learning. In a binary classifier in the one-against-all classifiers, we introduce a new class group “conceptually similar classes,” whose class labels are similar to...
The cognitive radio technology allows secondary user (SU) to share the licensed spectrum by adapting its transmission power in a sensing-based spectrum sharing manner. Reliable spectrum prediction and channel selection could alleviate the processing delays and enhance the spectrum utilization. In this paper, we propose a new strategy for spectrum prediction and channel selection using online machine...
The wireless sensor network is spatially disseminated independent sensors nodes to monitor wild environment monitoring, fire detection in forest, and militia surveillance. The sensor nodes are deployed to monitor themselves to communicate with each other. The sensor node collects the data from the network is shared between all the sensor nodes. Each sensor nodes of interpretation to be forwarded to...
The class imbalance problem is one of the new problems that emerged in activity recognition and that caused suboptimal classification performance. To deal this problem, we propose an efficient way of choosing the suitable regularization parameter C of the Soft-Support Vector Machines (C-SVM) method to perform automatic recognition of activities in a smart home environment. We also discuss how they...
A set of vectors (or signals) are jointly sparse if all their nonzero entries are found on a small number of rows (or columns). Consider a network of agents that collaboratively recover a set of jointly sparse vectors from their linear measurements . Assume that every agent collects its own measurement and aims to recover its own vector ...
Mill load (ML) estimation plays a major role in improving the grinding production rate (GPR) and the product quality of the grinding process. The ML parameters, such as mineral to ball volume ratio (MBVR), pulp density (PD) and charge volume ratio (CVR), reflect the load inside the ball mill accurately. The relative amplitudes of the high-dimensional frequency spectrum of shell vibration signals contain...
In order to improve the pressure sensor's current stability and temperature drift performance, a soft sensor regression model was modeled based on least square support vector machine (LS-SVM). According to the difficulty in selecting penalty factor and kernel parameter which are called hyper-parameters in LS-SVM when modeling, particle swarm optimization (PSO) algorithm and ergodicity search algorithm...
In this paper, we consider the distributed training of a SVM using measurements collected by the nodes of a Wireless Sensor Network in order to achieve global consensus with the minimum possible inter-node communications for data exchange. We derive a novel mathematical characterization for the optimal selection of partial information that neighboring sensors should exchange in order to achieve consensus...
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