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We report an experimental study of the three-dimensional spatial structure of the low-frequency temperature oscillations in a cylindrical Rayleigh-Bénard convection cell. Through simultaneous multipoint temperature measurements it is found that, contrary to the popular scenario, thermal plumes are emitted neither periodically nor alternately, but randomly(More)
Automated personal identification using localized ear images has wide range of civilian and law-enforcement applications. This paper investigates a new approach for more accurate ear recognition and verification problem using the sparse representation of local gray-level orientations. We exploit the computational simplicity of localized Radon transform for(More)
A new algorithm is proposed for robust principal component analysis with predefined sparsity patterns. The algorithm is then applied to separate the singing voice from the instrumental accompaniment using vocal activity information. To evaluate its performance, we construct a new publicly available iKala dataset that features longer durations and higher(More)
Personal identification from the iris images acquired under less-constrained imaging environment is highly challenging problem but with several important applications in surveillance, image forensics, search for missing children and wandering elderly. In this paper, we develop and formulate a new approach for the iris recognition using hypercomplex(More)
— Computational modellers are becoming increasingly interested in building large, eclectic, biological models. These may integrate nervous system components at various levels of description, other biological components (e.g. muscles), non-biological components (e.g. statistical discriminators or control software) and, in embodied modelling, even hardware(More)
Recently, the principal component pursuit has received increasing attention in signal processing research ranging from source separation to video surveillance. So far, all existing formulations are real-valued and lack the concept of phase, which is inherent in inputs such as complex spectrograms or color images. Thus, in this letter, we extend principal(More)
Informed by recent work on tensor singular value decomposition and circulant algebra matrices, this paper presents a new theoretical bridge that unifies the hypercomplex and tensor-based approaches to singular value decomposition and robust principal component analysis. We begin our work by extending the principal component pursuit to Olariu's polar(More)
Singing voice separation attempts to separate the vocal and instrumental parts of a music recording, which is a fundamental problem in music information retrieval. Recent work on singing voice separation has shown that the low-rank representation and informed separation approaches are both able to improve separation quality. However, low-rank optimizations(More)