| Christopher W. Baxter - 2001 - 141 pages
...name implies, the neurons in multi-layer perceptron networks are organized into a number of layers: **an input layer, one or more hidden layers, and an output layer.** All neurons are connected to neurons in adjoining layers and communicate with each other via connection... | |
| Faruk Bozoglu, T. Faruk Bozoğlu, Tibor Deák, Bibek Ray - 2001 - 246 pages
...feedforward, also called multilayer perceptrons with the architecture of interconnected neurons in **an input layer, one or more ..hidden" layers, and an output layer** (see Fig. 5). Number of processing units corresponds to the desired model inputs and outputs. Optimal... | |
| Danuta Rutkowska - 2001 - 288 pages
...as a generalization of the single-layer perceptron, by connecting the single layers. Typically, the **network consists of an input layer, one or more hidden layers, and an output layer.** The input signal propagates through the network in a forward direction. The first hidden layer is fed... | |
| John A. Meech - 2002 - 952 pages
...multi-layer perceptron - MLP) network is the most commonly used neural network for modelling. A MLP typically **consists of an input layer, one or more hidden layers, and an output layer** [8]. Many workers have demonstrated the power of the MLP network and research indicates that it is... | |
| G. A. R. Parke, P. Disney - 2002 - 1613 pages
...learning is carried out when a set of training patterns is propagated through a network consisting **of an input layer, one or more hidden layers and an output layer.** Each layer has its corresponding units and weight connections. The topology of a BP network is illustrated... | |
| Sergey Ablameyko - 2003 - 329 pages
...MLP is a feed-forward network built up of perceptron -type neurons, arranged in layers. An MLP has **an input layer, one or more hidden layers and an output layer.** 1n Figure 5 a single hidden layer multi-input - multi-output MLP is shown. An MLP is a fully connected... | |
| Zhishen Wu, Masato Abe - 2003 - 1395 pages
...network model, because of its simplicity. The architecture of BP networks, shown in Fig. 1, includes **an input layer, one or more hidden layers and an output layer.** Every node in each layer is connected to every node in the adjacent layer. Notably, HechtNielsen (1989)... | |
| Zahir Tari - 2007 - 1860 pages
...is developed with multi-layer perceptron (MLP). This is a unidirectional model of neural net made up **of an input layer, one or more hidden layers and an output layer.** The activation function of the neurons belonging to the hidden layers must be nonlinear so that the... | |
| Anke Meyer-Bäse - 2004 - 386 pages
...applications are successful implementations of MLPs. The architecture of the MLP is completely defined by **an input layer, one or more hidden layers, and an output layer.** Each layer consists of at least one neuron. The input vector is processed by the MLP in a forward direction,... | |
| Martin Wieland, Qingwen Ren, John S.Y. Tan - 2014 - 1240 pages
...learning model, due to its simplicity. The architecture of BP networks, depicted in Figure 1, includes **an input layer, one or more hidden layers, and an output layer.** The nodes in each layer are connected to each node in the adjacent layer. Notably, Hecht-Nielsen proved... | |
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