Neural network systems for chemical and biological pattern recognition via the Mueller matrix
AssigneeThe United States of America as represented by the Secretary of the Army
InventorArthur H. Carrieri
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Abstract
A neural network pattern recognition system for remotely sensing and identifying chemical and biological materials having a software component having an adaptive gradient descent training algorithm capable of performing backward-error-propagation and an input layer that is formatted to accept differential absorption Mueller matrix spectroscopic data, a filtering weight matrix component capable of filtering pattern recognition from Mueller data for specific predetermined materials and a processing component capable of receiving the pattern recognition from the filtering weight matrix component and determining the presence of specific predetermined materials. A method for sensing and identifying chemical and biological materials also is disclosed.
Claims12
A neural network pattern recognition system for remotely sensing and identifying chemical and biological materials comprising:
- a software component having an adaptive gradient descent training algorithm capable of performing backward-error-propagation and an input layer that is formatted to accept differential absorption Mueller matrix spectroscopic data;
- a filtering weight matrix component capable of filtering pattern recognition from Mueller data for specific predetermined materials;
- a processing component capable of receiving the pattern recognition from the filtering weight matrix component and determining the presence of specific predetermined materials;
- and
- an alarm set within a scalar product value.
A method for sensing and identifying chemical and biological materials comprising the steps of:
- providing a software component having an adaptive gradient descent training algorithm capable of performing backward-error-propagation and an input layer that is formatted to accept differential absorption Mueller matrix spectroscopic data, a filtering weight matrix component capable of filtering pattern recognition from Mueller data for specific predetermined materials, and, a processing component capable of receiving the pattern recognition from the filtering weight matrix component and determining the presence of specific predetermined materials;
- building artificial neural network systems for detecting specific solid organic compounds by pattern recognition of their polarized light scattering signatures;
- discerning the presence of specific analytes within a sample based upon cued susceptive Mueller matrix difference elements;
- and
- retraining the weight matrix component to add additional chemical/biological compounds.
Dependencies are inferred from the claim text.