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

von Rosenberg W, Chanwimalueang T, Goverdovsky V, Mandic DPet al., 2015, Smart helmet: Monitoring brain, cardiac and respiratory activity., 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Publisher: IEEE, Pages: 1829-1832, ISSN: 1557-170X

The timing of the assessment of the injuries following a road-traffic accident involving motorcyclists is absolutely crucial, particularly in the events with head trauma. Standard apparatus for monitoring cardiac activity is usually attached to the limbs or the torso, while the brain function is routinely measured with a separate unit connected to the head-mounted sensors. In stark contrast to these, we propose an integrated system which incorporates the two functionalities inside an ordinary motorcycle helmet. Multiple fabric electrodes were mounted inside the helmet at positions featuring good contact with the skin at different sections of the head. The experimental results demonstrate that the R-peaks (and therefore the heart rate) can be reliably extracted from potentials measured with electrodes on the mastoids and the lower jaw, while the electrodes on the forehead enable the observation of neural signals. We conclude that various vital sings and brain activity can be readily recorded from the inside of a helmet in a comfortable and inconspicuous way, requiring only a negligible setup effort.

Conference paper

Goverdovsky V, Looney D, Kidmose P, Mandic DPet al., 2015, In-Ear EEG From Viscoelastic Generic Earpieces: Robust and Unobtrusive 24/7 Monitoring, IEEE Sensors Journal, Vol: 16, Pages: 271-277, ISSN: 1558-1748

We introduce a novel in-ear sensor which satisfieskey design requirements for wearable electroencephalography(EEG)—it is discreet, unobtrusive, and capable of capturinghigh-quality brain activity from the ear canal. Unlike our initialdesigns, which utilize custom earpieces and require a costlyand time-consuming manufacturing process, we here introducethe generic earpieces to make ear-EEG suitable for immediateand widespread use. Our approach represents a departure fromsilicone earmoulds to provide a sensor based on a viscoelasticsubstrate and conductive cloth electrodes, both of which areshown to possess a number of desirable mechanical and electricalproperties. Owing to its viscoelastic nature, such an earpieceexhibits good conformance to the shape of the ear canal, thusproviding stable electrode–skin interface, while cloth electrodesrequire only saline solution to establish low impedance contact.The analysis highlights the distinguishing advantages comparedwith the current state-of-the-art in ear-EEG. We demonstratethat such a device can be readily used for the measurement ofvarious EEG responses.

Journal article

Chanwimalueang T, von Rosenberg W, Mandic DP, 2015, Enabling R-peak detection in wearable ECG: Combining matched filtering and Hilbert transform., IEEE International Conference on Digital Signal Processing (DSP), Publisher: IEEE, Pages: 134-138

Conference paper

Abdullah SMU, Rehman NU, Khan MM, Mandic DPet al., 2015, A Multivariate Empirical Mode Decomposition Based Approach to Pansharpening, IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, Vol: 53, Pages: 3974-3984, ISSN: 0196-2892

Journal article

Xu D, Xia Y, Mandic DP, 2015, Optimization in quaternion dynamic systems: gradient, Hessian, and learning algorithms, IEEE Transactions on Neural Networks and Learning Systems, Vol: 27, Pages: 249-261, ISSN: 2162-2388

The optimization of real scalar functions of quaternion variables, such as the mean square error or array output power, underpins many practical applications. Solutions typically require the calculation of the gradient and Hessian. However, real functions of quaternion variables are essentially nonanalytic, which are prohibitive to the development of quaternion-valued learning systems. To address this issue, we propose new definitions of quaternion gradient and Hessian, based on the novel generalized Hamilton-real (GHR) calculus, thus making a possible efficient derivation of general optimization algorithms directly in the quaternion field, rather than using the isomorphism with the real domain, as is current practice. In addition, unlike the existing quaternion gradients, the GHR calculus allows for the product and chain rule, and for a one-to-one correspondence of the novel quaternion gradient and Hessian with their real counterparts. Properties of the quaternion gradient and Hessian relevant to numerical applications are also introduced, opening a new avenue of research in quaternion optimization and greatly simplified the derivations of learning algorithms. The proposed GHR calculus is shown to yield the same generic algorithm forms as the corresponding real- and complex-valued algorithms. Advantages of the proposed framework are illuminated over illustrative simulations in quaternion signal processing and neural networks.

Journal article

Rehman NU, Ehsan S, Abdullah SMU, Akhtar MJ, Mandic DP, McDonald-Maier KDet al., 2015, Multi-Scale Pixel-Based Image Fusion Using Multivariate Empirical Mode Decomposition, SENSORS, Vol: 15, Pages: 10923-10947

Journal article

Ahrabian A, Mandic DP, 2015, A Class of Multivariate Denoising Algorithms Based on Synchrosqueezing, IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol: 63, Pages: 2196-2208, ISSN: 1053-587X

Journal article

von Rosenberg W, Chanwimalueang T, Looney D, Mandic DPet al., 2015, Vital signs from inside a helmet: A multichannel face-lead study., IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Publisher: IEEE, Pages: 982-986

It is essential to measure physiological parameters such as heart rate variability and respiratory rate of drivers to evaluate their performance. The results from this measurement can be used to assess the state of body and mind, for instance concentration and stress. However, current systems only work in controlled environments, or sensors obstruct and interfere with operations of the driver. In this study, a face-lead ECG is placed inside a helmet to enhance comfort and convenience in racing scenarios. Multiple electrodes were attached to facial locations, which exhibit good contact with a helmet, and bipolar configurations were examined between the left and right side of the subject's face. Standard and data-driven filtering algorithms were employed to improve the extraction of R peaks from the ECG data. The so-extracted R peaks were subsequently used to estimate heart activity and respiration effort, and the results were compared with standard recording protocols. It is shown that ECG recordings obtained from locations on the lower jaw match closely with conventional recording paradigms (limb-lead ECG), highlighting the potential of vital sign monitoring from within a racing helmet.

Conference paper

Xia Y, Jahanchahi C, Mandic DP, 2015, Quaternion-Valued Echo State Networks, IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, Vol: 26, Pages: 663-673, ISSN: 2162-237X

Journal article

Xu D, Mandic DP, 2015, The Theory of Quaternion Matrix Derivatives, IEEE TRANSACTIONS ON SIGNAL PROCESSING, Vol: 63, Pages: 1543-1556, ISSN: 1053-587X

Journal article

Kanna S, Dini DH, Xia Y, Hui SY, Mandic DPet al., 2015, Distributed Widely Linear Kalman Filtering for Frequency Estimation in Power Networks, IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, Vol: 1, Pages: 45-57, ISSN: 2373-776X

Journal article

Took CC, Douglas SC, Mandic DP, 2015, Maintaining the Integrity of Sources in Complex Learning Systems: Intraference and the Correlation Preserving Transform, IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, Vol: 26, Pages: 500-509, ISSN: 2162-237X

Journal article

Xia Y, Blazic Z, Mandic DP, 2015, Complex-Valued Least Squares Frequency Estimation for Unbalanced Power Systems, IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, Vol: 64, Pages: 638-648, ISSN: 0018-9456

Journal article

Jaksic V, O'Shea R, Cahill P, Murphy J, Mandic DP, Pakrashi Vet al., 2015, Dynamic response signatures of a scaled model platform for floating wind turbines in an ocean wave basin, PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, Vol: 373, ISSN: 1364-503X

Journal article

Jaksic V, Wright CS, Murphy J, Afeef C, Ali SF, Mandic DP, Pakrashi Vet al., 2015, Dynamic response mitigation of floating wind turbine platforms using tuned liquid column dampers, PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, Vol: 373, ISSN: 1364-503X

Journal article

Cichocki A, Mandic DP, Anh HP, Caiafa CF, Zhou G, Zhao Q, De Lathauwer Let al., 2015, Tensor decompositions for signal processing applications: from two-way to multiway component analysis, IEEE Signal Processing Magazine, Vol: 32, Pages: 145-163, ISSN: 1053-5888

The widespread use of multisensor technology and the emergence of big data sets have highlighted the limitations of standard flat-view matrix models and the necessity to move toward more versatile data analysis tools. We show that higher-order tensors (i.e., multiway arrays) enable such a fundamental paradigm shift toward models that are essentially polynomial, the uniqueness of which, unlike the matrix methods, is guaranteed under very mild and natural conditions. Benefiting from the power of multilinear algebra as their mathematical backbone, data analysis techniques using tensor decompositions are shown to have great flexibility in the choice of constraints which match data properties and extract more general latent components in the data than matrix-based methods.

Journal article

Looney D, Hemakom A, Mandic DP, 2015, Intrinsic multi-scale analysis: a multi-variate empirical mode decomposition framework., Proc Math Phys Eng Sci, Vol: 471, ISSN: 1364-5021

A novel multi-scale approach for quantifying both inter- and intra-component dependence of a complex system is introduced. This is achieved using empirical mode decomposition (EMD), which, unlike conventional scale-estimation methods, obtains a set of scales reflecting the underlying oscillations at the intrinsic scale level. This enables the data-driven operation of several standard data-association measures (intrinsic correlation, intrinsic sample entropy (SE), intrinsic phase synchrony) and, at the same time, preserves the physical meaning of the analysis. The utility of multi-variate extensions of EMD is highlighted, both in terms of robust scale alignment between system components, a pre-requisite for inter-component measures, and in the estimation of feature relevance. We also illuminate that the properties of EMD scales can be used to decouple amplitude and phase information, a necessary step in order to accurately quantify signal dynamics through correlation and SE analysis which are otherwise not possible. Finally, the proposed multi-scale framework is applied to detect directionality, and higher order features such as coupling and regularity, in both synthetic and biological systems.

Journal article

Tobar F, Mandic DP, 2015, High-dimensional kernel regression: A guide for practitioners, Trends in Digital Signal Processing: A Festschrift in Honour of A. G. Constantinides, Pages: 287-310, ISBN: 9789814669504

© 2016 Pan Stanford Publishing Pte. Ltd. We provide a rigorous account of high-dimensional kernels (HDK), and illuminate their theoretical and practical advantages in nonlinear regression of multivariate signals. Our emphasis is on signal processing applications, supported by deep insight into the existence of higher-dimensional feature spaces, including complex, quaternion, and vector-valued reproducing kernel Hilbert spaces. Next, these existence conditions are used to elucidate the ability of kernel regression algorithms to extract rich relationships from available data. Practical examples of the advantages of the HDK paradigm include multimodal wind prediction, body sensor trajectory tracking, and nonlinear function approximation.

Book chapter

Zhou G, Cichocki A, Mandic DP, 2015, COMMON COMPONENTS ANALYSIS VIA LINKED BLIND SOURCE SEPARATION, 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 2150-2154, ISSN: 1520-6149

Conference paper

Mandic DP, Kanna S, Douglas SC, 2015, MEAN SQUARE ANALYSIS OF THE CLMS AND ACLMS FOR NON-CIRCULAR SIGNALS: THE APPROXIMATE UNCORRELATING TRANSFORM APPROACH, 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 3531-3535, ISSN: 1520-6149

Conference paper

Thanthawaritthisai T, Tobar F, Constantinides AG, Mandic DPet al., 2015, THE WIDELY LINEAR QUATERNION RECURSIVE TOTAL LEAST SQUARES, 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 3357-3361, ISSN: 1520-6149

Conference paper

Hemakom A, Ahrabian A, Looney D, Rehman NU, Mandic DPet al., 2015, NONUNIFORMLY SAMPLED TRIVARIATE EMPIRICAL MODE DECOMPOSITION, 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 3691-3695, ISSN: 1520-6149

Conference paper

von Rosenberg W, Chanwimalueang T, Looney D, Mandic DPet al., 2015, VITAL SIGNS FROM INSIDE A HELMET: A MULTICHANNEL FACE-LEAD STUDY, 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 982-986, ISSN: 1520-6149

Conference paper

Talebi SP, Kanna S, Mandic DP, 2015, Real-Time Estimation of Quaternion Impropriety, IEEE International Conference on Digital Signal Processing (DSP), Publisher: IEEE, Pages: 557-561

Conference paper

Kanna S, Xiang M, Mandic DP, 2015, Real-Time Detection of Rectilinear Sources for Wireless Communication Signals, 12th International Symposium on Wireless Communication Systems (ISWCS), Publisher: IEEE

Conference paper

Zhou G, Cichocki A, Mandic DP, 2015, COMMON COMPONENTS ANALYSIS VIA LINKED BLIND SOURCE SEPARATION, 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 2150-2154, ISSN: 1520-6149

Conference paper

Talebi SP, Mandic DP, 2015, A QUATERNION FREQUENCY ESTIMATOR FOR THREE-PHASE POWER SYSTEMS, 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 3956-3960, ISSN: 1520-6149

Conference paper

Mandic DP, Kanna S, Douglas SC, 2015, MEAN SQUARE ANALYSIS OF THE CLMS AND ACLMS FOR NON-CIRCULAR SIGNALS: THE APPROXIMATE UNCORRELATING TRANSFORM APPROACH, 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 3531-3535, ISSN: 1520-6149

Conference paper

Hemakom A, Ahrabian A, Looney D, Rehman NU, Mandic DPet al., 2015, NONUNIFORMLY SAMPLED TRIVARIATE EMPIRICAL MODE DECOMPOSITION, 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 3691-3695, ISSN: 1520-6149

Conference paper

Thanthawaritthisai T, Tobar F, Constantinides AG, Mandic DPet al., 2015, THE WIDELY LINEAR QUATERNION RECURSIVE TOTAL LEAST SQUARES, 40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Publisher: IEEE, Pages: 3357-3361, ISSN: 1520-6149

Conference paper

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