Large-scale holographic neuron system for multispectral sensor fusion and high-speed signal processing

Thomas Taiwei Lu; Freddie Shing-Hong Lin; Andrew A. Kostrzewski; Jeremy M. Lerner

doi:10.1117/12.172518

1 February 1994 Large-scale holographic neuron system for multispectral sensor fusion and high-speed signal processing

Thomas Taiwei Lu, Freddie Shing-Hong Lin, Andrew A. Kostrzewski, Jeremy M. Lerner

Proceedings Volume 2093, Substance Identification Analytics; (1994) https://doi.org/10.1117/12.172518
Event: Substance Identification Technologies, 1993, Innsbruck, Austria

Abstract

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.

Citation Download Citation

Thomas Taiwei Lu, Freddie Shing-Hong Lin, Andrew A. Kostrzewski, and 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); https://doi.org/10.1117/12.172518

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