Aeronautical Development Agency, Bangalore-560 017 E-mail: krishna@jetmail.ada.gov.in.
The error backpropagation multi-layer perceptron algorithm is revisited. This algorithm is used to train and validate two models of three-layer neural networks that can be used to calibrate a 5-hole pressure probe. This paper addresses Occam's Razor problem as it describes the adhoc training methodology applied to improve accuracy and sensitivity. The trained outputs from 5-4-3 feed-forward network architecture with jump connection are comparable to second decimal digit (∼0.05) accuracy, hitherto unreported in literature.
Back propagation, calibration, curve-fitting, error, inner product, logistic function, neuron, perceptron, pressure probe, training network, synaptic weights
