Titlebook: Supervised Learning with Complex-valued Neural Networks; Sundaram Suresh,Narasimhan Sundararajan,Ramasamy S Book 2013 Springer-Verlag Berl

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A Fully Complex-valued Radial Basis Function Network and Its Learning Algorithm,nt a complex-valued RBF network which is a direct extension of the real-valued RBF network. CRBF network is a single hidden layer networkwhich computes the output of the network as a linear combination of the hidden neuron outputs.

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Introduction, preserves the physical characteristics of these signals. Therefore, there is a widespread research interest in developing efficient complex-valued neural networks along with their learning algorithms. However, operating in the Complex domain presents new challenges; foremost among them being the ch

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A Fully Complex-valued Radial Basis Function Network and Its Learning Algorithm,e localization property of the Gaussian function. in this chapter, we study complex-valued RBF networks and their learning algorithms. First, we present a complex-valued RBF network which is a direct extension of the real-valued RBF network. CRBF network is a single hidden layer networkwhich compute

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Performance Study on Complex-valued Function Approximation Problems,valued multi-layer perceptron network described in Chapter 2, the fully complex-valued radial basis function network and the meta-cognitive fully complex-valued radial basis function network described in Chapter 3, and the fast learning fully complex valued relaxation network described in Chapter 4.

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Circular Complex-valued Extreme Learning Machine Classifier,rk, as investigated by the Neuroscience community. Ever since then, several tasks of human activity have been emulated by the ANNs. Classification is one such decision making task that occurs frequently in human activity and one that has been emulated in the artificial neural network framework. A cl