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FFNNFeed Forward Neural Network
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Reddy and Raju used single layer feed forward neural network with back propagation learning algorithm and resilient back propagation algorithm for predicting the software development effort accurately [10].
Two-layer feed forward neural network with LM Back-Propagation training algorithm was used for approximation of measured CO/lambda dependence.
It becomes clear that a feed forward neural network can replace the linear function [F.sup.L] in equation (7) by an arbitrary non-linear function [F.sup.NN] as in equation (8) (K.G.
Their wavenet consists of a single layer feed forward neural network with hidden nodes of adaptive wavelet functions followed by an infinite impulse response (IIR) recurrent structure.
In a feed forward neural network with BP algorithm, a set of input data is introduced to the network and the outputs are estimated by back propagation algorithm.
The input configuration is tested by Feed forward neural network with number of hidden neurons i.e., 1-30.
According to Kolmogorov theorem, as to any given L2 type continuous function f: [0, 1] n [right arrow] Rm, f can be accurately realized by three-layer feed forward neural network, thus it can only consider the weighted value and nodes of evolving network while not affecting evolution results.
Chien, "Feed forward neural network and feedback linearization control design of BILSAT-1 satellite system," International Journal of Innovative Computig, Information and Control, vol.
They used back-propagation feed forward neural network to predict hardness and grain size.
It occurs in most of the methods including template matching and LVQ based Feed Forward Neural Network.