الفهرس 
1 IntroductionOnly 14 pages are availabe for public view
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Abstract
rincipal Component Analysis (PCA) has been widely used as a data
reduction technique to overcome the curse of dimensionality. In this
research a different use for PCA technique as a tool for data fusion is
introduced.
Principal component analysis method and fuzzy principal component
analysis method have been described in this chapter to perform multisensor
data fusion with a confidence measure associated with each sensor
output. Although it was mentioned in chapter two, there is no perfect
algorithm that is optimal under all conditions, table (6-7) below shows
the simulation results comparison for all three approaches used to perform
multi-sensor data fusion for the instant navigation system described in
example 1 with minimum value of standard deviation for the error signal
achieved by applying FAKF.
Table (6-7). SIMULATION RESULTS COMPARISON
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Sensory Data Fusion Based Fuzzy Principal Component Analysis .6