Optimisation of Signal-to-Noise Ratio in Electrical and Electromagnetic Investigations. Electrical and electromagnetic geophysical methods have been used extensively for mineral exploration, and are developing a role in salinity mapping and contaminant identification. To enhance the utility of such methods for very shallow targets (in the case of salinity) and deep targets (minerals beneath regolith)improved signal processing methods are required. The project involves the development of time-ser ....Optimisation of Signal-to-Noise Ratio in Electrical and Electromagnetic Investigations. Electrical and electromagnetic geophysical methods have been used extensively for mineral exploration, and are developing a role in salinity mapping and contaminant identification. To enhance the utility of such methods for very shallow targets (in the case of salinity) and deep targets (minerals beneath regolith)improved signal processing methods are required. The project involves the development of time-series processing techniques using robust-statistical methods and remote-referencing to improve signal-to-noise data quality. Instrumentation hardware and software developments are required for in-field data acquisition and interpretation, applied to direct current (DC) resistivity, induced polarisation (IP) and time-domain EM (TEM).Read moreRead less
Optimal Transforms of Random Vectors. This proposal focusses on development of optimal transforms to describe and model nonlinear phenomena when only statistical information is known. An optimal transform is a mathematical procedure that enables us to process information in a way that is most suited to the task in hand. These transforms have been successfully used in approximation, information theory, communications, control theory and signal and image processing. Applications include modelli ....Optimal Transforms of Random Vectors. This proposal focusses on development of optimal transforms to describe and model nonlinear phenomena when only statistical information is known. An optimal transform is a mathematical procedure that enables us to process information in a way that is most suited to the task in hand. These transforms have been successfully used in approximation, information theory, communications, control theory and signal and image processing. Applications include modelling of physical, chemical and biological systems, filtering and compression of signals and data classification and clustering. We propose two new hybrid models for realistic transforms in a general structural framework.
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