1 February 1994 Large-scale holographic neuron system for multispectral sensor fusion and high-speed signal processing
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Proceedings Volume 2093, Substance Identification Analytics; (1994) https://doi.org/10.1117/12.172518
Event: Substance Identification Technologies, 1993, Innsbruck, Austria
One-dimensional (1D) and 2D sensor signals returned from the mass spectrometers, x-ray spectral analyzers, CT scanners, or vapor detectors present a major challenge for the detection and identification of illegal substances. Prompt and accurate identification and classification of detected signatures demands extremely high computation power and requires sophisticated signal processing. The paper presents the development of a real-time multispectral analysis system that performs high-speed neural operations and sensor fusion for feature extraction and trace identification. The system utilizes the technology of large-scale holographic optical neural networks being developed and demonstrated by Physical Optics Corporation (POC). This technology is based on fully parallel optical processing of spectral information to produce parallel spectral pattern recognition. In addition, POC's processing algorithm has demonstrated the ability to extract spectral information from extremely noisy backgrounds. This translates into very high instrument sensitivity.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thomas Taiwei Lu, Thomas Taiwei Lu, Freddie Shing-Hong Lin, Freddie Shing-Hong Lin, Andrew A. Kostrzewski, Andrew A. Kostrzewski, Jeremy M. Lerner, Jeremy M. Lerner, } "Large-scale holographic neuron system for multispectral sensor fusion and high-speed signal processing", Proc. SPIE 2093, Substance Identification Analytics, (1 February 1994); doi: 10.1117/12.172518; https://doi.org/10.1117/12.172518

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