Network Learning Algorithm

Neural network learning algorithms BP = Back-Propagation Delta = Delta Rule QP = Quick-Propagation RP = Rprop ART = Adaptive Resonance Theory, CP = Counter-Propagation. 

A general form of a neural network learning algorithm is given by ... 

Feedforward Neural Networks Learning Algorithms for Neural Networks Special Feedforward Networks... 

Learning in the context of a neural network is the process of adjusting the weights and biases in such a manner that for given inputs, the correct responses, or outputs are achieved. Learning algorithms include ... 

A. Sankar and R. Mammone, A fast learning algorithm for tree neural networks. In Proc. 1990 Conf. on Information Sciences and Systems, Princeton, NJ, 1990, pp. 638-642. 

B. Walczak, Neural networks with robust backpropagation learning algorithm. Anal. Chim. Acta, 322 (1996) 21-30. 

Chen, S., Cowan, C. F. N., and Grant, P. M., Orthogonal least squares learning algorithm for radial basis function networks, IEEE Trans. Neur. Net. 2(2), 302-309 (1991). 

Artificial neural networks often have a layered structure as shown in Figure 8.2 (b). The first layer is the input layer. The second layer is the hidden layer. The third layer is the output layer. Learning algorithms such as back-propagation that are described in many textbooks on neural networks (Kosko 1992 Rumelhart and McClelland 1986 Zell 1994) may be used to train such networks to compute a desired output for a given input. The networks are trained by adjusting the weights as well as the thresholds. 

Stanton DT, Jurs PC (1990) Development and use of charged partial surface area structural descriptors in computer-assisted quantitative structure-property relationship studies. Anal Chem 62 2323—2329. Tetko iy Kovalishyn Vy Livingstone DJ (2001) Volume learning algorithm artificial neural networks for 3D-QSAR studies. J Med Chem 44 2411-2420. 

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