Accession Number:

ADD019771

Title:

Neural Network Noise Anomaly Recognition System and Method

Descriptive Note:

Patent application, Filed 4 Oct 2000

Corporate Author:

DEPARTMENT OF THE NAVY WASHINGTON DC

Personal Author(s):

Report Date:

2000-10-04

Pagination or Media Count:

17.0

Abstract:

A system and method for a neural network is disclosed that is trained to recognize noise characteristics or other types of interference and to determine when an input waveform deviates from learned noise characteristics. A plurality of neural networks is preferably provided, which each receives a plurality of samples of intervals or windows of the input waveform. Each of the neural networks produces an output based on whether an anomaly is detected with respect to the noise, which the neural network is trained to detect. The plurality of outputs of the neural networks is preferably applied to a decision aid for deciding whether the input waveform contains a non-noise component. The decision aid may include a database, a computational section and a decision module. The system and method may provide a preliminary processing of the input waveform and is used to recognize the particular noise rather than a non-noise signal.

Subject Categories:

  • Cybernetics
  • Miscellaneous Detection and Detectors
  • Bionics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE