1.4k citations · 3.2k across the 73 of their papers we have counts for
19 papers · 1 filter
Complexity-based Financial Stress Evaluation
Hongjian Xiao, Yao Lei Xu, Danilo P. Mandic
Financial markets typically exhibit dynamically complex properties as they undergo continuous interactions with economic and environmental factors. The Efficient Market Hypothesis…
Bayesian autoregressive spectral estimation
Alejandro Cuevas, Sebastián López, Danilo Mandic +1
Autoregressive (AR) time series models are widely used in parametric spectral estimation (SE), where the power spectral density (PSD) of the time series is approximated by that of…
Variational Embedding Multiscale Sample Entropy:complexity-based analysis for multichannel systems
Hongjian Xiao, Danilo P. Mandic
To quantify the complexity of a system, entropy-based methods have received considerable critical attentions in real-world data analysis. Among numerous entropy algorithms, amplitu…
In-Ear SpO2 for Classification of Cognitive Workload
Harry J. Davies, Ian Williams, Ghena Hammour +3
Classification of cognitive workload promises immense benefit in diverse areas ranging from driver safety to augmenting human capability through closed loop brain computer interfac…
A Probabilistic Spectral Analysis of Multivariate Real-Valued Nonstationary Signals
Bruno Scalzo, Ljubisa Stankovic, Danilo P. Mandic
A class of multivariate spectral representations for real-valued nonstationary random variables is introduced, which is characterised by a general complex Gaussian distribution. In…
In-Ear Measurement of Blood Oxygen Saturation: An Ambulatory Tool Needed To Detect The Delayed Life-Threatening Hypoxaemia in COVID-19
Harry J. Davies, Ian Williams, Nicholas S. Peters +1
Non-invasive ambulatory estimation of blood oxygen saturation has emerged as an important clinical requirement to detect hypoxemia in the delayed post-infective phase of COVID-19,…
Methods of Adaptive Signal Processing on Graphs Using Vertex-Time Autoregressive Models
Thiernithi Variddhisai, Danilo Mandic
The concept of a random process has been recently extended to graph signals, whereby random graph processes are a class of multivariate stochastic processes whose coefficients are…
Graph Theory and Metro Traffic Modelling
Bruno Scalzo Dees, Anthony G. Constantinides, Danilo P. Mandic
In this article we demonstrate how graph theory can be used to identify those stations in the London underground network which have the greatest influence on the functionality of t…
A Statistically Identifiable Model for Tensor-Valued Gaussian Random Variables
Bruno Scalzo Dees, Anh-Huy Phan, Danilo P. Mandic
Real-world signals typically span across multiple dimensions, that is, they naturally reside on multi-way data structures referred to as tensors. In contrast to standard ``flat-vie…
Portfolio Cuts: A Graph-Theoretic Framework to Diversification
Bruno Scalzo Dees, Ljubisa Stankovic, Anthony G. Constantinides +1
Investment returns naturally reside on irregular domains, however, standard multivariate portfolio optimization methods are agnostic to data structure. To this end, we investigate…
Unitary Shift Operators on a Graph
Bruno Scalzo Dees, Ljubisa Stankovic, Milos Dakovic +2
A unitary shift operator (GSO) for signals on a graph is introduced, which exhibits the desired property of energy preservation over both backward and forward graph shifts. For rig…
Tight Lower Bound on the Tensor Rank based on the Maximally Square Unfolding
Giuseppe G. Calvi, Bruno Scalzo Dees, Danilo P. Mandic
Tensors decompositions are a class of tools for analysing datasets of high dimensionality and variety in a natural manner, with the Canonical Polyadic Decomposition (CPD) being a m…
A Class of Doubly Stochastic Shift Operators for Random Graph Signals and their Boundedness
Bruno Scalzo Dees, Ljubisa Stankovic, Milos Dakovic +2
A class of doubly stochastic graph shift operators (GSO) is proposed, which is shown to exhibit: (i) lower and upper -boundedness for locally stationary random graph signals…
Vertex-Frequency Graph Signal Processing: A review
Ljubisa Stankovic, Danilo P. Mandic, Milos Dakovic +4
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…
An Example-Driven Introduction to Data Analytics on Graphs
Ljubisa Stankovic, Danilo Mandic, Milos Dakovic +3
Graphs are irregular structures which naturally account for data integrity, however, traditional approaches have been established outside Signal Processing, and largely focus on an…
Tensor Ensemble Learning for Multidimensional Data
Ilia Kisil, Ahmad Moniri, Danilo P. Mandic
In big data applications, classical ensemble learning is typically infeasible on the raw input data and dimensionality reduction techniques are necessary. To this end, novel framew…
A Data Analytics Perspective of the Clarke and Related Transforms in Power Grid Analysis
Danilo P. Mandic, Sithan Kanna, Yili Xia +2
Affordable and reliable electric power is fundamental to modern society and economy, with the Smart Grid becoming an increasingly important factor in power generation and distribut…
The sum of tensor networks
Giuseppe G. Calvi, Ilia Kisil, Danilo P. Mandic
Tensor networks (TNs) have been gaining interest as multiway data analysis tools owing to their ability to tackle the curse of dimensionality and to represent tensors as smaller-sc…
Tensor Valued Common and Individual Feature Extraction: Multi-dimensional Perspective
Ilia Kisil, Giuseppe G. Calvi, Danilo P. Mandic
A novel method for common and individual feature analysis from exceedingly large-scale data is proposed, in order to ensure the tractability of both the computation and storage and…