We present and describe two new speaker adaptation methods which apply principal component analysis to maximum likelihood linear regression (MLLR). If we apply MLLR after transforming the baseline mean vectors by their eigenvectors, the contributions of these eigenvalues to the variance of the estimates for the MLLR matrix are inversely proportional to their corresponding eigenvalues. In the fi...

ABSTRACT We introduce a statistical method for the decomposition of data sets into planes. With the help of principal component analysis or factor analysis the data are presented in a lower-dimensional space. The factors spanning this new co-ordinate system are rotated afterwards in that sense to fulfill the idea of simple structure, extended to two dimensions. The resulting planes which are sp...

Group independent component analysis (ICA) with special assumptions is often used for analyzing functional magnetic resonance imaging (fMRI) data. Before ICA, dimension reduction is applied to separate signal and noise subspaces. For analyzing noisy fMRI data of individual participants in free-listening to naturalistic and long music, we applied individual ICA and therefore avoided the assumpti...

mobile ad-hoc networks (manets) by contrast of other networks have more vulnerability because of having nature properties such as dynamic topology and no infrastructure. therefore, a considerable challenge for these networks, is a method expansion that to be able to specify anomalies with high accuracy at network dynamic topology alternation. in this paper, two methods proposed for dynamic anom...

as widespread deserts is located in west and southwest of iran plateau, dust storms form due to west andsouthwest systems over syria or iraq as well as arabian peninsula. these systems severely affect west and southwestregions. sometimes the fine dusts transmit to central, north east, and east regions. in this study for investigating dustysynoptical patterns, meteorological data at 5 synoptic s...

background: in order to check the practicality of classification of universities of medical sciences (umss) based on their infrastructures, and scientific contributions, this study explored the most appropriate indicators to measure the size and productivity of umss. methods: in the first phase, we approached a group of experts who had a deep experience in the management of umss and in the mini...

This paper discusses the problem of automated lexicography. In the corpus-based approach, a lexicographer has to manually group contexts of a target word into clusters in order to identify word senses. When a large number of the contexts is given, this process becomes a tedious and time-consuming task. To overcome this problem, we propose an efficient technique based on unsupervised clustering....

We present herein an extension of an algebraic statistical method for inferring biochemical reaction networks from experimental data, proposed recently in [3]. This extension allows us to analyze reaction networks that are not necessarily full-dimensional, i.e., the dimension of their stoichiometric space is smaller than the number of species. Specifically, we propose to augment the original al...

A useful technique for the validation and verification of complex flight systems is Monte Carlo Filtering—a global sensitivity analysis that tries to find the inputs and ranges that are most likely to lead to a subset of the outputs. A thorough exploration of the parameter space for complex integrated systems may require thousands of experiments and hundreds of controlled and measured variables...

The 21-item version of the Peters et al. Delusions Inventory (PDI-21) is a commonly used tool to measure delusional ideation in the normal population. Two recent principal component analyses have concluded that the PDI-21 has a seven-factor structure. Although these studies found identical factors associated with religiosity and grandiosity, the items loading on the remaining five factors, and ...