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A non-parametric probability density function (pdf) estimation technique is presented. The estimation consists in approximating the unknown pdf by a network of Gaussian Radial Basis Functions (GRBFs). Complexity analysis is introduced in order to select the optimal number of GRBFs. Results obtained on real data show the potentiality of this technique.
In high technological complexity industrial systems, the operators' role is more and more critical. They need deeper and deeper specialization and a continuous monitoring of both process and plant to achieve high efficiency and proper working. That requires a continuous training and upgrading of the operator knowledge to react promptly and properly to the different plant/process situation to manage...
Previous results state that there is no single universal search algorithm which outperforms other algorithms in terms of search on functions over finite domains. We consider functions with countably infinite domains, that is functions which are mappings from the set of natural numbers to the set of natural numbers. A search algorithm samples points of a given function, producing a sequence of output...
Development of large projects is a knowledge intensive task. Applying knowledge management techniques to project activities can enhance productivity and reduce risks of failures. However, it has been observed that knowledge management activities suffer from problems such as unavailability of structured information and lack of incentives to put extra efforts for these activities. In this paper, we...
Most existing model-based approaches to anomaly detection construct a profile of normal instances, then identify instances that do not conform to the normal profile as anomalies. This paper proposes a fundamentally different model-based method that explicitly isolates anomalies instead of profiles normal points. To our best knowledge, the concept of isolation has not been explored in current literature...
This paper presents a pruned sets method (PS) for multi-label classification. It is centred on the concept of treating sets of labels as single labels. This allows the classification process to inherently take into account correlations between labels. By pruning these sets, PS focuses only on the most important correlations, which reduces complexity and improves accuracy. By combining pruned sets...
Kernel Fisher discriminant analysis (KFDA) has been widely used in fault diagnosis. In this paper, a feature vector selection (FVS) scheme based on a geometrical consideration is given to reduce the computational complexity of KFDA when the number of samples becomes large. Experimental results show the effectiveness of our method.
Fast and efficient discovery of all neighboring nodes by a node new to a neighborhood is critical to the deployment of wireless ad hoc networks. Different than the conventional ALOHA-type random access discovery schemes, this paper assumes that all nodes in the neighborhood simultaneously send their unique on-off signatures known to the receive node. In particular, a transmitter does not transmit...
In this paper, we present a scheme of steganalysis of JPEG images with the use of polynomial fitting and computational intelligence techniques. Based on the Generalized Gaussian Distribution (GGD) model in the quantized DCT coefficients, the errors between the logarithmic domain of the histogram of the DCT coefficients and the polynomial fitting are extracted as features to detect the adulterated...
In this paper, we propose a method that can generate new test data using the sample shift of starting frame for the sequential probability ratio test (SPRT) in automatic speaker verification (ASV). The SPRT is an effective algorithm that can reduce the computational complexity of test, but itpsilas not suitable method to apply for the short utterance. The proposed method is effective in applying the...
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