Edge Enhancement and Exploratory Projection Pursuit
We present a neural network algorithm based on simple Hebbian learning which allows the finding of higher order structure in data. The neural network uses negative feedback of activation to self-organise; such networks have previously been shown to be capable of performing Principal Component Analysis (PCA). In this paper, this is extended to Exploratory Projection Pursuit (EPP) which is a statistical method for investigating structure in high-dimensional data sets.