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Can I read Neural Networks Letter on EtoBox?
Neural Networks Letter by Andrew I. Hanna; Danilo P. Mandic is a Computer Science article available to read on EtoBox.
What is Neural Networks Letter about?
A complex-valued nonlinear gradient descent (CNGD) learning algorithm for a simple finite impulse response (FIR) nonlinear neural adaptive filter with an adaptive amplitude of the complex activation function is proposed. This way the amplitude of the complex-valued analytic nonlinear activation function of a neuron in the learning algorithm is made gradient adaptive to give the complex-valued adaptive amplitude nonlinear gradient descent (CAANGD). Such an algorithm is beneficial when dealing with signals that have rich dynamical behavior. Simulations on the prediction of complex-valued coloured and nonlinear input signals show the gradient adaptive amplitude, CAANGD, outperforming the standard CNGD algorithm.
Who reads Neural Networks Letter?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Andrew I. Hanna; Danilo P. Mandic
- Publisher
- Elsevier Science; Elsevier ; Elsevier Ltd.; Elsevier BV (ISSN 0893-6080)
- Published
- 2003
- Language
- EN
- Field
- Computer Science (Physical Sciences)