Algebraic Approach and Optimal Physical Clusterization in Interpolation Problems of Artificial Intelligence
Perceptron-type interpolation systems of artificial intelligence are considered. A concept of optimal physical clusterization allows us to divide a second layer of hidden units into the compact sets of units (clusters). Then, an algebraic approach developed for pattern recognition systems may be extended to other systems. To solve the problems of process forecasting, a data sample should be transformed into a single-moment sample.
A. G. Ivakhnenko et al., "Algebraic Approach and Optimal Physical Clusterization in Interpolation Problems of Artificial Intelligence," Pattern Recognition and Image Analysis, Springer, Jan 2003.
Electrical and Computer Engineering
Keywords and Phrases
Artificial Intelligence; Interpolation; Neural Network; Self-Organization
Article - Journal
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