&lt;title&gt;SDFs for sensor/data fusion&lt;/title&gt;

James D. Brasher; Charles F. Hester; Fred J. Selzer

doi:10.1117/12.138330

ScienceGate Book Chapters

JOURNAL ARTICLE

<title>SDFs for sensor/data fusion</title>

James D. Brasher Charles F. Hester Fred J. Selzer

Year: 1992 Journal: Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 1701 Pages: 212-216 Publisher: SPIE

DOI: 10.1117/12.138330

Get Full-Text PDF Get Analytical Report

Abstract

We describe how the synthetic discriminant function (SDF) can be employed in sensor/data fusion. This is accomplished by exploiting the isomorphism between the SDF formalism and the parallel distributed processing (PDP) architecture of neural networks.© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Keywords:

Upload Optical engineering Sensor fusion Computer science Fusion Isomorphism (crystallography) Architecture Artificial intelligence Formalism (music) Pattern recognition (psychology) Function (biology) Artificial neural network Data mining Operating system

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.20

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

Neural Networks and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Target Tracking and Data Fusion in Sensor Networks

Physical Sciences → Computer Science → Artificial Intelligence

Fault Detection and Control Systems

Physical Sciences → Engineering → Control and Systems Engineering

<title>SDFs for sensor/data fusion</title>

Abstract

Metrics

Topics

Related Documents

<title>Passive-sensor data fusion</title>

<title>Adaptive sensor fusion</title>

<title>Neural networks for sensor data fusion</title>

<title>Wavelet-based sensor fusion</title>

<title>Soldier systems sensor fusion</title>