The main objective of this work is to present an exploratory approach on electroencephalographic (EEG) signal, analyzing the patterns on the time-frequency plane. This work also aims to optimize the EEG signal analysi...
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ISBN:
(纸本)9781424417780
The main objective of this work is to present an exploratory approach on electroencephalographic (EEG) signal, analyzing the patterns on the time-frequency plane. This work also aims to optimize the EEG signal analysis through the improvement of classifiers and, eventually, of the BCI performance. In this paper a novel exploratory approach for datamining on EEG signal based on continuous wavelet transformation (CWT) and wavelet coherence (WC) statistical analysis is introduced and applied. The CWT allows the signal underlying information content illustration by representing time-frequency patterns on Wavelet Coherence qualitative analysis. Results suggest that the proposed methodology is capable of identifying regions on time-frequency spectrum during the specified task on BCI. Furthermore, an example of a region is identified, and the patterns were classified using a radial basis function neural network (RBF-NN). This innovative characteristic of the process justify the feasibility of the proposed approach on another datamining applications. It can open new physiologic researches on this field and researches on different non-stationary time series analysis.
The main objective of this work is to present an exploratory approach on electroencephalographic (EEG) signal, analyzing the patterns on the time-frequency plane. This work also aims to optimize the EEG signal analysi...
详细信息
The main objective of this work is to present an exploratory approach on electroencephalographic (EEG) signal, analyzing the patterns on the time-frequency plane. This work also aims to optimize the EEG signal analysis through the improvement of classifiers and, eventually, of the BCI performance. In this paper a novel exploratory approach for datamining on EEG signal based on continuous wavelet transformation (CWT) and wavelet coherence (WC) statistical analysis is introduced and applied. The CWT allows the signal underlying information content illustration by representing time-frequency patterns on Wavelet Coherence qualitative analysis. Results suggest that the proposed methodology is capable of identifying regions on time-frequency spectrum during the specified task on BCI. Furthermore, an example of a region is identified, and the patterns were classified using a radial basis function neural network (RBF-NN). This innovative characteristic of the process justify the feasibility of the proposed approach on another datamining applications. It can open new physiologic researches on this field and researches on different non-stationary time series analysis.
Causal structure-discovery techniques usually assume that all causes of more than one variable are observed. This is the so-called causal sufficiency assumption. In practice, it is untestable, and often violated. In t...
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ISBN:
(纸本)9781605609492
Causal structure-discovery techniques usually assume that all causes of more than one variable are observed. This is the so-called causal sufficiency assumption. In practice, it is untestable, and often violated. In this paper, we present an efficient causal structure-learning algorithm, suited for causally insufficient data. Similar to algorithms such as IC* and FCI, the proposed approach drops the causal sufficiency assumption and learns a structure that indicates (potential) latent causes for pairs of observed variables. Assuming a constant local density of the data-generating graph, our algorithm makes a quadratic number of conditional-independence tests w.r.t. the number of variables. We show with experiments that our algorithm is comparable to the state-of-the-art FCI algorithm in accuracy, while being several orders of magnitude faster on large problems. We conclude that MBCS* makes a new range of causally insufficient problems computationally tractable.
Spam-unsolicited commercial e-mail-is a complex and growing problem, and threatens to derail the internet revolution. Joshua Goodman and David Heckerman of Microsoft research describe some statistics-based methods for...
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