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      An Incremental Design of Radial Basis Function Networks

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          LIBSVM

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            A tutorial on support vector regression

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              Training feedforward networks with the Marquardt algorithm.

              The Marquardt algorithm for nonlinear least squares is presented and is incorporated into the backpropagation algorithm for training feedforward neural networks. The algorithm is tested on several function approximation problems, and is compared with a conjugate gradient algorithm and a variable learning rate algorithm. It is found that the Marquardt algorithm is much more efficient than either of the other techniques when the network contains no more than a few hundred weights.
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                Author and article information

                Journal
                IEEE Transactions on Neural Networks and Learning Systems
                IEEE Trans. Neural Netw. Learning Syst.
                Institute of Electrical and Electronics Engineers (IEEE)
                2162-237X
                2162-2388
                October 2014
                October 2014
                : 25
                : 10
                : 1793-1803
                10.1109/TNNLS.2013.2295813
                © 2014
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