Cluster analysis seeks to assign objects with similar characteristics into groups called clusters so that within a group are each other and dissimilar in groups. Spectral clustering has been shown perform well different scenarios on continuous data: it can detect convex non-convex clusters, overlapping clusters. However, the constraint data be limiting real applications where often of mixed-typ...

Ensemble clustering helps achieve fast under abundant computing resources by constructing multiple base clusterings. Compared with the standard single algorithm, ensemble integrates advantages of algorithms and has stronger robustness applicability. Nevertheless, most treat each result equally ignore difference clusters. If a cluster in is reliable/unreliable, it should play critical/uncritical...

The use of acoustic properties by French and German speakers in accentuating and de-accentuating words in accordance with changes in information weighting is examined. In particular, the role of duration is shown to differ for the two languages, confirming earlier findings. In addition, a difference in the relative contribution of F0, intensity and spectral balance is found for the prediction o...

We prove that there is a universal constant C > 0 with the following property. Suppose that n ∈ N and that A = (aij) ∈ Mn(R) is a symmetric stochastic matrix. Denote the second-largest eigenvalue of A by λ2(A). Then for any finite-dimensional normed space (X, ∥ · ∥) we have ∀x1, . . . , xn ∈ X, dim(X) > 1 2 exp ( C 1− λ2(A) √ n ( ∑n i=1 ∑n j=1 ∥xi − xj∥ 2 ∑n i=1 ∑n j=1 aij∥xi − xj∥ ) 1 2 )