Accession Number:

ADA276445

Title:

Smart Environmental Monitor Based on Neural Networks and Multi-Spectral Pattern Recognition

Descriptive Note:

Final rept. Mar-Sep 1993

Corporate Author:

PHYSICAL OPTICS CORP TORRANCE CA

Personal Author(s):

Report Date:

1993-09-01

Pagination or Media Count:

20.0

Abstract:

In Phase I of this project, Physical Optics Corporation POC accomplished the goal of the original proposal which was to develop and optimize a unique neural network NN algorithm that performs rapid spectral signal processing and identification. POCs NN algorithm was tested with extremely noisy Raman spectra from Lawrence Livermore National Laboratory and experimentally showed at least ten times better sensitivity and reliability than conventional spectral signal processing methods. POC built a portable demonstration system with POCs NN and successfully demonstrated real-time spectral signature identification operations. POC proposed, for Phase II implementation, a holographic optical neural network HONN system that is capable of rapid hyperspectral imaging through an acoustic-optic tunable filter AOTF, real-time spectral feature identification, and mapping. The success of the Phase II project will make automatic and rapid hyperspectral image analysis and feature location possible. Neural networks, Holographic optical spectral feature identification, Portable smart spectrometer, Hyperspectral image processing.

Subject Categories:

  • Electrooptical and Optoelectronic Devices

Distribution Statement:

APPROVED FOR PUBLIC RELEASE