Danilo P. Mandic

Imperial College London

632Publications

44H-index

9,356Citations

Publications 632

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Published in Biomedical Engineering Letters

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Heart rate variability (HRV) is governed by the autonomic nervous system (ANS) and is routinely used to estimate the state of body and mind. At the same time, recorded HRV features can vary substantially between people. A model for HRV that (1) correctly simulates observed HRV, (2) reliably functions for multiple scenarios, and (3) can be personalised using a manageable set of parameters, would be a significant step forward toward understanding individual responses to external influences, such a...

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Background Despite the increasing interest in fetal and neonatal heart rate variability analysis and its potential use as a tool for early disease stratification, no studies have previously described the normal trends of heart rate variability in healthy babies during the first hours of postnatal life. Methods We prospectively recruited 150 healthy babies from the postnatal ward and continuously recorded their electrocardiogram (ECG) during the first 24 hours of postnatal life. Five-minute segme...

Published in arXiv: Signal Processing

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The maximum entropy principle is employed to introduce a general class of shift operators (GSO) for random signals on a graph. By virtue of the assumed probabilistic framework, the proposed GSO is shown to be both bounded and to exhibit the desired property of asymptotic power preservation over graph shifts. For rigour, the sensitivity of the GSO to a graph topology misspecification is also addressed. The advantages of the proposed operator are demonstrated in a real-world multi-sensor signal av...

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The unconstrained frequency-domain block least mean square (UFBLMS) algorithm is a de facto standard in frequency-domain adaptive filtering, owing to its fast convergence for correlated input signals. However, although many complex-valued signals in real-world applications are second-order noncircular (improper), for computational convenience, existing mean square analyses of UFBLMS assume second-order circular (proper) input data. This, in turn, makes conventional mean square evaluations of UFB...

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Abstract With their ability to cater for simultaneously for multifaceted information, multichannel (multivariate) signals have been used to solve problems that are normally not solvable with signals obtained from a single source. One such problem is the decomposition of signals which comprise several components for which the domains of support significantly overlap in both the time, frequency and the joint time-frequency domain. Earlier, we proposed a solution to this problem based on the Wigner...

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We provide a rigorous account of the equivalence between the complex-valued widely linear estimation method and the quaternion involution widely linear estimation method with their vector-valued real linear estimation counterparts. This is achieved by an account of degrees of freedom and by providing matrix mappings between a complex variable and an isomorphic bivariate real vector, and a quaternion variable versus a quadri-variate real vector. Furthermore, we show that the parameters in the com...

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Graph signal processing deals with signals which are observed on an irregular graph domain. While many approaches have been developed in classical graph theory to cluster vertices and segment large graphs in a signal independent way, signal localization based approaches to the analysis of data on graph represent a new research direction which is also a key to big data analytics on graphs. To this end, after an overview of the basic definitions in graphs and graph signals, we present and discuss ...

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