Imperial College London

ProfessorDaniloMandic

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Professor of Signal Processing
 
 
 
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Contact

 

+44 (0)20 7594 6271d.mandic Website

 
 
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Assistant

 

Miss Vanessa Rodriguez-Gonzalez +44 (0)20 7594 6267

 
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Location

 

813Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
to

619 results found

Tonoyan Y, Looney D, Mandic DP, Van Hulle MMet al., 2014, PREDICTING SUBJECT PERFORMANCE LEVEL FROM EEG SIGNAL COMPLEXITY WHEN ENGAGED IN BCI PARADIGM, IEEE International Workshop on Machine Learning for Signal Processing (MLSP), Publisher: IEEE, ISSN: 2161-0363

Conference paper

Xia Y, Jahanchahi C, Xu D, Mandic DPet al., 2014, The ℍℂ calculus, quaternion derivatives and caylay-hamilton form of quaternion adaptive filters and learning systems, Pages: 3395-3401

© 2014 IEEE. We introduce a novel and unifying framework for the calculation of gradients of both quaternion holomorphic functions and nonholomorphic real functions of quaternion variables. This is achieved by considering the isomorphism between the quaternion domain ℍ and the bivariate complex domain ℂ× ℂ, and by exploiting complex calculus to simplify the quaternion gradient calculation. The validation of the proposed ℍℂ calculus is performed against the existing HR calculus, and its convenience is illustrated in the context of gradient-based quaternion optimisation as well as in adaptive learning systems. Quaternion adaptive filtering algorithms and a dynamical perceptron update are next derived based on the bivariate complex representation of quaternions and the HC calculus. Simulations on both synthetic and real-world multidimensional signals support the analysis.

Conference paper

Looney D, Kidmose P, Mandic DP, 2014, Ear-EEg: User-centered and wearable BCI, Biosystems and Biorobotics, Pages: 41-50

© Springer-Verlag Berlin Heidelberg 2014. We present a radically new solution for EEG-based brain computer interface (BCI) where electrodes are embedded on a customized earpiece, as typically used in hearing aids (Ear-EEG). This provides a noninvasive, minimally intrusive and user-friendly EEG platform suitable for long-term use (days) in natural environments. The operation of Ear-EEG is illustrated for al-pha-attenuation and responses to auditory stimuli, and its potential in BCI is evaluated on an SSVEP study. We show that Ear-EEG bitrate performances are comparable with those of on-scalp electrodes, thus promising a quantum step forward for wearable BCI.

Book chapter

Xia Y, Mandic DP, 2014, A widely linear least mean phase algorithm for adaptive frequency estimation of unbalanced power systems, INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, Vol: 54, Pages: 367-375, ISSN: 0142-0615

Journal article

Li L, Witon A, Marcora S, Bowman H, Mandic DPet al., 2014, EEG-based brain connectivity analysis of states of unawareness., Pages: 1002-1005

This work investigates phase synchrony as a neuro-marker for the identification of two brain states: coma and quasi-brain-death. Scalp electroencephalography (EEG) data of 34 patients were recorded in an intensive care unit (ICU), with 17 recordings for patients in a coma state, and 17 recordings for patients in a quasi-brain-death state. Phase synchrony was used for feature extraction from EEG recording by comparing the phase value between pairs of electrodes using an entropy based measure. In particular, we performed phase synchrony analysis in five standard frequency bands and provide visualization of the phase synchronies in matrices. The effectiveness of the phase synchrony features in each of the frequency bands are evaluated with statistical analysis. Results suggest phase synchrony for coma patients has a significant increase in the theta / alpha band compared to quasi-brain-death patients. Hence, we propose phase synchrony as a candidate for the identification of consciousness states between coma and quasi-brain-death.

Conference paper

Ujang BC, Jahanchahi C, Took CC, Mandic DPet al., 2013, Adaptive Convex Combination Approach for the Identification of Improper Quaternion Processes, IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, Vol: 25, Pages: 172-182, ISSN: 2162-237X

Journal article

Williamon A, Aufegger L, Wasley D, Looney D, Mandic DPet al., 2013, Complexity of physiological responses decreases in high-stress musical performance, JOURNAL OF THE ROYAL SOCIETY INTERFACE, Vol: 10, ISSN: 1742-5689

Journal article

Peng B, Liu W, Mandic DP, 2013, Design of oversampled generalised discrete Fourier transform filter banks for application to subband-based blind source separation, IET SIGNAL PROCESSING, Vol: 7, Pages: 843-853, ISSN: 1751-9675

Journal article

Mandic DP, Rehman NU, Wu Z, Huang NEet al., 2013, Empirical Mode Decomposition-Based Time-Frequency Analysis of Multivariate Signals, IEEE SIGNAL PROCESSING MAGAZINE, Vol: 30, Pages: 74-86, ISSN: 1053-5888

Journal article

Took CC, Douglas SC, Mandic D, 2013, On intraference and its implications in complex-valued signal processing, Pages: 3934-3937, ISSN: 1520-6149

We introduce the concept of intra-ference in order to quantify the degree to which the integrity of bivariate (or complex) sources is preserved in applications based on matrix decompositions of bivariate data. This is achieved by examining the pseudocovariancematrix of noncircular complex sources, and by recognising that the pseudocovariance is intrinsically complex valued. We illuminate how the existing decompositions such as the strong uncorrelating transform (SUT) not only decorrelate the bivariate sources from one another, but also decorrelate and scatter the data channels within each bivariate source, thus violating source integrity. Examples showing that the intra-ference arises due to the phase ambiguity in the existing matrix decompositions support the approach. © 2013 IEEE.

Conference paper

Kidmose P, Looney D, Ungstrup M, Rank ML, Mandic DPet al., 2013, A Study of Evoked Potentials From Ear-EEG, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, Vol: 60, Pages: 2824-2830, ISSN: 0018-9294

Journal article

Dini DH, Djuric PM, Mandic DP, 2013, The Augmented Complex Particle Filter, IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol: 61, Pages: 4341-4346, ISSN: 1053-587X

Journal article

Navarro-Moreno J, Fernandez-Alcala RM, Took CC, Mandic DPet al., 2013, Prediction of wide-sense stationary quaternion random signals, SIGNAL PROCESSING, Vol: 93, Pages: 2573-2580, ISSN: 0165-1684

Journal article

Peng B, Liu W, Mandic DP, 2013, Subband-based joint blind source separation for convolutive mixtures employing M-CCA

This paper addresses the source separation problem for convolutive mixtures by employing the joint blind source separation (BSS) technique in the subband domain. The key to the proposed method is to decompose the time-domain mixed signals into subbands to generate the required related multiple data sets for the operation of joint BSS. To reduce the aliasing error after subband decimation, the oversampled generalized DFT filter banks are employed to maintain a sufficient level of correlation between the data sets. A recently proposed correlation optimisation method for the design of filter banks is adopted to enhance the correlation between adjacent subband signals, which leads to further improved separation results in terms of both signal to interference ratio and subband permutation alignment.

Conference paper

Aguilera P, Cruces S, Duran-Diaz I, Sarmiento A, Mandic DPet al., 2013, Blind Separation of Dependent Sources With a Bounded Component Analysis Deflationary Algorithm, IEEE SIGNAL PROCESSING LETTERS, Vol: 20, Pages: 709-712, ISSN: 1070-9908

Journal article

Xia Y, Mandic DP, 2013, Augmented MVDR Spectrum-Based Frequency Estimation for Unbalanced Power Systems, IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, Vol: 62, Pages: 1917-1926, ISSN: 0018-9456

Journal article

Mostafanezhad I, Yavari E, Boric-Lubecke O, Lubecke VM, Mandic DPet al., 2013, Cancellation of Unwanted Doppler Radar Sensor Motion Using Empirical Mode Decomposition, IEEE SENSORS JOURNAL, Vol: 13, Pages: 1897-1904, ISSN: 1530-437X

Journal article

Ahrabian A, Rehman NU, Mandic D, 2013, Bivariate Empirical Mode Decomposition for Unbalanced Real-World Signals, IEEE SIGNAL PROCESSING LETTERS, Vol: 20, Pages: 245-248, ISSN: 1070-9908

Journal article

Kidmose P, Mandic D, Ungstrup M, Looney D, Park C, Rank MLet al., 2013, A Hearing Aid Adapted for Detection Brain Waves and a Method for Adapting Such a Hearing Aid

Patent

Dini DH, Mandic DP, 2013, Widely Linear Modeling for Frequency Estimation in Unbalanced Three-Phase Power Systems, IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, Vol: 62, Pages: 353-363, ISSN: 0018-9456

Journal article

Er W, Mandic DP, 2013, DYNAMICAL COMPLEXITY ANALYSIS OF MULTIVARIATE FINANCIAL DATA, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 8732-8736, ISSN: 1520-6149

Conference paper

Tobar FA, Mandic DP, 2013, THE QUATERNION KERNEL LEAST SQUARES, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 6128-6132, ISSN: 1520-6149

Conference paper

Zhao Q, Caiafa CF, Mandic D, Chao ZC, Nagasaka Y, Fujii N, Zhang L, Cichocki Aet al., 2013, Higher-Order Partial Least Squares (HOPLS): A Generalized Multi-Linear Regression Method, IEEE Transactions on Pattern Analysis and Machine Intelligence, Pages: 1-1, ISSN: 0162-8828

Journal article

Park C, Looney D, Rehman NU, Ahrabian A, Mandic DPet al., 2013, Classification of Motor Imagery BCI Using Multivariate Empirical Mode Decomposition, IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, Vol: 21, Pages: 10-22, ISSN: 1534-4320

Journal article

Rutkowski TM, Struzik ZR, Mandic DP, 2013, EEG Epileptic Seizures Separation with Multivariate Empirical Mode Decomposition for Diagnostic Purposes, 35th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC), Publisher: IEEE, Pages: 7128-7131, ISSN: 1557-170X

Conference paper

Dini DH, Mandic DP, 2013, Exploiting sparsity in widely linear estimation, Pages: 808-812, ISSN: 2154-0217

The distribution of complex random signals is typically improper. It has recently been established that conventional strictly linear models are only second order optimum for signals with proper distributions, while so called "widelylinear models" are optimum for the generality of complex signals, both proper and improper. Widely-linear models, however, are over-parameterised when the underlying system is strictly-linear, requiring twice the number of parameters to be estimated compared to strictly-linear models. This effects widely-linear adaptive algorithms, such as the augmented complex least mean square (ACLMS) and augmented complex recursive least squares (ACRLS), and leads to slow convergence. We here address the problem of the over-parameterisation of the ACLMS through the use of regularised cost error functions, and illustrate its effects through analysis and simulations. © VDE Verlag GMBH.

Conference paper

Jahanchahi C, Mandic DP, 2013, AN ADAPTIVE DIFFUSION QUATERNION LMS ALGORITHM FOR DISTRIBUTED NETWORKS OF 3D AND 4D VECTOR SENSORS, 21st European Signal Processing Conference (EUSIPCO), Publisher: IEEE

Conference paper

Took CC, Douglas SC, Mandic D, 2013, u ON INTRAFERENCE AND ITS IMPLICATIONS IN COMPLEX-VALUED SIGNAL PROCESSING, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 3934-3937, ISSN: 1520-6149

Conference paper

Jahanchahi C, Cheong Took C, Mandic DP, 2013, A class of quaternion valued affine projection algorithms, Signal Processing, ISSN: 0165-1684

Journal article

Kidmose P, Looney D, Jochumsen L, Mandic DPet al., 2013, Ear-EEG from generic earpieces: a feasibility study., Annu Int Conf IEEE Eng Med Biol Soc, Vol: 2013, Pages: 543-546

The use of brain monitoring based on EEG, in natural environments and over long time periods, is hindered by the limited portability of current wearable systems, and the invasiveness of implanted systems. To that end, we introduce an ear-EEG recording device based on generic earpieces which meets key patient needs (discreet, unobstrusive, user-friendly, robust) and that is low-cost and suitable for off-the-shelf use; thus promising great advantages for healthcare applications. Its feasibility is validated in a comprehensive comparative study with our established prototype, based on a personalized earpiece, for a key EEG paradigm.

Journal article

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