Signal Processing Research Topics

7/31/2019 Signal Processing Research Topics

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Signal Processing Research Topics

Current research topics in signal processing include the design of multi-sensor

arrays that in-corporate steering and adaptive filtering in their internal

structure; quadratic and parametric spectrum analysis; modal analysis;

wavelets and orthogonal filters; the design and analysis of new adaptive

structures and algorithms; the development of fast algorithms; the design of

digital controllers which minimize finite register effects; multiscale and time

frequency representations of images and multi-dimensional signals which

involves the development of new mathematical and computational algorithms

in the area of applied harmonic analysis. Applications are in biomedical signal

and image analysis, and audio and image compression. Research in speech

signal processing includes analysis and modeling of speech and speaker

traits, speech pathology and voice assessment, speech enhancement andfeature estimation in noise, robust speech recognition, and speech feature

enhancement in hands-free environments for human-computer interaction.

Nonlinear System Identification, Signal and Information Processing

The derivation of system identification and information processing algorithmsto identify both the system structure and estimate the unknown parameters ina wide class of nonlinear models including polynomial and wavelet narmaxmodels, radial basis function and wavelet network models is being

investigated. The focus is on model structure selection and the identification ofmodels that are transparent, which can be related back to the underlyingsystem, and which generalise well. The derivation of generic model validationand model analysis methods for all classes of nonlinear models are also beingstudied.

Subharmonics and Severely Nonlinear Systems

Severely nonlinear systems, which generate sub-harmonics, are being studiedin both the time and the frequency domain. The Response Spectrum Map,which is a frequency domain equivalent to the Bifurcation Diagram, hasrecently been introduced as a powerful new tool for analysing this importantclass of systems.


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Nonlinear Systems in the Frequency Domain

A complete theory for the analysis of nonlinear systems in the frequencydomain has been developed. This consists of analytic methods for mappingrom nonlinear discrete and continuous time nonlinear differential equation

models to the multi-dimensional generalised frequency response functions andvisa versa. A new class of filters, called energy transfer filters, has recently

been derived which allows energy to be moved to new frequency locations orspread over a band of frequencies.

Non-linear Damping

A new class of nonlinear passive and active damping methods are beinginvestigated. The new methods damp the resonance effects withoutintroducing power into the frequency response tails.

Spatio-Temporal Systems and Cellular Automata

Spatio-temporal systems are systems that evolve over both space and time.The realisation, identification, prediction and analysis of this class of systemsare being studied using both partial differential equation and latticedynamical system models. Cellular automata (CA) and excitable mediamodels are also being studied.


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Modelling the Magnetosphere and Solar Wind

The identification and analysis of data sets relating to the magnetosphere andthe solar wind, based on data recorded from satellites, is being studied inboth the time and the frequency domain to forecast geomagnetic indices andto predict disturbances of the magnetic field such as storms and sub-storms.

Neuro-Imaging and Systems Neuroscience

Models relating the Blood Oxygenated Level Dependent (BOLD) signal fromunctional magnetic resonance imaging (fMRI) and hemodynamic response to

changes in neural activity, and for determining inter-regional neuronalinteractions are being studied. Neuro imaging has become an importantscientific technique for the investigation of brain function, and is an importantexample of a spatio-temporal system that has enormous potential foraddressing significant issues in neuroscience and medicine. Diffuse OpticalTomography (DOT) imaging methods are also being developed.

Modelling and Identification for Mobile Robots

An investigation to determine how robot attributes, sensor properties andenvironmental characteristics influence robot behaviour, and the developmentof a theoretical framework to describe robot environment interaction is beingstudied.


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Metabolic Systems Engineering

Metabolic engineering involves the modelling and identification of metabolicpathways found in an organism to better understand and utilise cellularpathways for chemical transformation.

Systems and Synthetic Biology

Whereas systems biology is essentially reverse engineering of biologicalsystems synthetic biology is the design and construction of new biologicalparts, devices, and systems. Ultimately the aim of synthetic biology is to beable to manipulate biological systems in a similar way that is now possiblewith physics and chemistry systems.

Stem Cell Dynamics

Research on stem cell population dynamics and cell lineage, including themodelling and identification of stem cell behaviour is being investigated.


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Bio-Imaging

Bio-Imaging techniques for application in the medical, pharma, biotech andhealthcare sectors are being studied.

Identification and Analysis of Neural Activity and the Visual Systemin Drosophila

The neural processing of the visual system of Drosophila or fruit flies is beinginvestigated to understand how fly brains process information about thevisual environment.

Reaction Diffusion Systems and Crystal Growth

The identification, modelling and analysis of chemical non-equilibrium growthprocesses, including reaction-diffusion systems, crystal growth and bacterialcolonies, is being investigated.

Neutrophil

Spatio-temporal modelling and analysis of neutrophil, associated with theinflammatory response in zebra fish tails, is being studied as part of a widerinvestigation into chemotaxis.


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EEG

New wavelet adaptive tracking algorithms are being developed to track bothlinear and nonlinear frequency domain behaviours as a new tool to aidclinicians in the interpretation of EEG's.

Modelling Financial Systems

The identification and analysis of financial market models associated withmarket risk and volatility are being studied.

Machine Vision

The development of computer vision systems for autonomous guided vehicles

(agv's) and robotics is being studied, including stereo algorithms, objectsurveillance and collision avoidance strategies.

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Signal Processing Research Topics