Titlebook: Neural Networks and Statistical Learning; Ke-Lin Du,M. N. S. Swamy Textbook 20141st edition Springer-Verlag London 2014 Data Mining, Data

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Perceptrons,The perceptron [.], also referred to as a McCulloch-Pitts neuron or linear threshold gate, is the earliest and simplest neural network model. Rosenblatt used a single-layer perceptron for the classification of linearly separable patterns.

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Multilayer Perceptrons: Architecture and Error Backpropagation,MLPs are feedforward networks with one or more layers of units between the input and output layers. The output units represent a hyperplane in the space of the input patterns. The architecture of MLP is illustrated in Fig.?..

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Hopfield Networks, Simulated Annealing, and Chaotic Neural Networks,The Hopfield model [., .] is the most popular dynamic model. It is biologically plausible since it functions like the human retina [.].

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Independent Component Analysis,Imagine that you are attending a cocktail party, the surrounding is full of chatting and noise, and somebody is talking about you. In this case, your ears are particularly sensitive to this speaker. This is the cocktail-party problem, which can be solved by blind source separation (BSS).

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Other Kernel Methods,The kernel method was originally invented in Aizerman et al. (Autom. Remote Control, 25, 821–837, 1964). The key idea is to project the training set in a lower-dimensional space into a high-dimensional kernel (feature) space by means of a set of nonlinear kernel functions.