Selected Works of Assoc. Prof. I. S. Burnett

Dr. Ian Burnett is an Associate Professor in the School of Electrical, Computer and Telecommunications Engineering at the University of Wollongong. His research interests extend from speech and audio compression and processing through to multimedia delivery and perception. He currently chairs the Multimedia Description Schemes subgroup at MPEG, and has been extensively involved in the standardisation of MPEG-21. For further information refer to Dr. Burnett's faculty page.

Documents by Subject Area

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• A new waveform interpolation coding scheme based on pitch synchronous wavelet transform decomposition
• A Protected Digital Item Declaration Language for MPEG-21
• A Sequential Approach to Sparse Component Analysis
• A Variable Length Linear Array for Smart Antenna Systems
• A Variable Length Linear Array for Smart Antenna Systems using Partial Optimization
• Accurate, critically sampled characteristic waveform surface construction for waveform interpolation decomposition
• Adaptive resource replication in a ubiquitous peertopeer based multimedia distribution environment
• An investigation of temporal modeling in blind signal separation
• Audio coding using sorted sinusoidal parameters
• Bitstream Binding Language – Mapping XML Multimedia Containers into Streams
• BitTorrent in a dynamic resource adapting peer-to-peer network
• Blind Separation of Speech with a Switched Sparsity and Temporal Criteria
• Blind speech separation using a joint model of speech production
• Blur retrieval via separation of zeros sheets from noisy blurred images
• Collaborative Editing using an XML Protocol
• Dynamic multimedia adaptation and updating of media streams with MPEG-21
• Dynamic resource adaptation in a heterogeneous peer-to-peer environment
• Efficient Delivery within the MPEG-21 Framework
• Enhancing Interoperability via Generic Multimedia Syntax Translation
• Exchanging XML Multimedia Containers Using a Binary XML Protocol
• Exploiting simultaneously masked linear prediction in a WI speech coder
• Exploring the characteristics of analytic decomposition of speech signals
• Extending waveform interpolation to wideband speech coding
• Facilitating Universal Multimedia Adaptation (UMA) in a Heterogeneous Peer-to-Peer Network
• Format-Independent Multimedia Streaming
• Fuzzy clustering evaluation of time-frequency distribution (TFD) schemes for audio stream segregation
• Improved Dynamic Multimedia Resource Adaptation-based Peer-to-Peer System through Locality-based Clustering and Service
• Improved signal analysis and time-synchronous reconstruction in waveform interpolation coding
• Is That a Fish in Your Ear? A Universal Metalanguage for Multimedia
• Lie analysis of the Webster horn equation with application to audio object recognition
• Linear prediction incorporating simultaneous masking
• Low bit rate wideband WI speech coding
• Low bit rate wideband WI speech coding
• Low rate WI SEW representation using a REW-implicit pulse model
• MPEG-21 digital item declaration and Identification-principles and compression
• MPEG-21 in backpack journalism scenario
• MPEG-21: goals and achievements
• Multi-rate and multi-resolution scalable to lossless audio compression using PSPIHT
• On-Demand Partial Schema Delivery for Multimedia Metadata
• Principles and Analysis of the Squeezing Approach to Low Bit Rate Spatial Audio Coding
• Role of wavelet transforms in image restoration
• Scalable audio coding employing sorted sinusoidal parameters
• Scalable decomposition of speech waveforms
• Scalable speech coding spanning the 4 Kbps divide
• Scalable to lossless audio compression based on perceptual set partitioning in hierarchical trees (PSPIHT)
• Scalable to lossless audio compression based on perceptual set partitioning in hierarchical trees (PSPIHT)
• Sew Representation for Low Rate WI Coding
• Spanning the 4 kbps divide using pulse modeled residual
• Temporal decomposition for low rate wideband speech compression
• The analysis of speech codecs using psychoacoustic measures
• Universal multimedia experiences for tomorrow
• Using spatial cues for meeting speech segmentation
• Very low rate speech coding using temporal decomposition and waveform interpolation