Principal Component Analysis (PCA) has many different important applications especially in pattern detection such as face detection / recognition. Therefore, for real time applications, the response time is required to be as small as possible. In this paper, new implementation of PCA for fast face detection is presented. Such new implementation is designed based on cross correlation in the freq...

Auditory processing of complex sources, after an initial peripheral spectro-temporal stage, is thought to have a more central stage identify in the output time segments and frequency regions of higher activity by way of a temporal and spectral modulation analysis. Such analysis broadens the view on perception, both that of complex signals and of auditory scene analysis (ASA). When resolution of...

We report explicit analytical and numerical results for the polarization resolved intensity noise of verticalcavity surface-emitting lasers operating in the fundamental transverse mode. We describe the fluctuations of the linear and circular polarization components of linearly polarized states on both sides of a nonthermal polarization switching. Our description is valid for small and large bir...

Music key, a high level feature of musical audio, is an effective tool for structural analysis of musical works. This paper presents a novel unsupervised approach for clustering music recordings by their keys. Based on chroma-based features extracted from acoustic signals, an inter-recording distance metric which characterizes diversity of pitch distribution together with harmonic center of mus...

In this paper, we present a fast numerical strategy for filtering stochastic differential equations with multiscale features. This method is designed such that it does not violate the practical linear observability condition and, more importantly, it does not require the computationally expensive cross correlation statistics between multiscale variables that are typically needed in standard fil...

Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying PCA to a set of sample points. Since PCA is rather sensitive to outliers, if a small fraction of these points does not correspond to the correct correlation of the cluster, the algorithms are usually misled or even fail to detec...

This paper explores the narration of Pushkin’s novel (in translation into English by James E. Falen) by Stephen Fry and Rafael Corkhill. The aim was to analyse the actors’ oral performance in terms of prosodic invariants as compared to the Russian original recited by two professional actors. An attempt was made to measure the ‘authenticity’ of the translation by application of cluster analysis....

In the present work a method is proposed for the estimation of the respiratory signal from the three ECG orthogonal leads. The vectorcardiogram loop was evaluated in correspondence of each QRS complex (in a time window of 120 ms centred around the R wave). The centre of gravity and the inertial axes of each loop were calculated. A set of 12 parameters (3 spatial coordinates of the centre of gra...

This paper addresses the task of analyzing the correlation between two related domains X and Y . Our research is motivated by an Earth Science task that studies the relationship between vegetation and precipitation. A standard statistical technique for such problems is Canonical Correlation Analysis (CCA). A critical limitation of CCA is that it can only detect linear correlation between the tw...

Bulking and foaming are two notorious problems in activated sludge wastewater treatment plants (WWTPs), which are mainly associated with the excessive growth of bulking and foaming bacteria (BFB). However, studies on affecting factors of BFB in full-scale WWTPs are still limited. In this study, data sets of high-throughput sequencing (HTS) of 16S V3-V4 amplicons of 58 monthly activated sludge s...