| L.A. Ayres de Silva, A.P. Chaves, W.T. Hennies - 1996 - 740 pages
...of training patterns. A neural network in its basic form is composed of several layers of neurons; an input layer, one or more hidden layers and an output layer. Each layer of neurons receives its input from the previous layer (referring to hidden layer and output... | |
| Kevin Swingler - 1996 - 348 pages
...in turn, used to predict the values on the output units. The network is arranged in layers of units: an input layer, one or more hidden layers, and an output layer. The value displayed by each unit is known as its activation and measures the degree to which it affects... | |
| P. Cheremisinoff - 1997 - 928 pages
...succeeding layer. Neural networks that are organized in layers typically consist of at least three layers: an input layer, one or more hidden layers, and an output layer. The input and output layers serve as interfaces that perform the appropriate scaling relationship between... | |
| Mo-Yuen Chow - 1997 - 162 pages
...Multi-layer Feedforward Neural Network Model The basic multi-layer feedforward net contains three components: an input layer, one or more hidden layers, and an output layer, as shown in Figure 2.3. Each network layer contains a set of processing units called nodes or neurons,... | |
| Ignazio Crivelli Visconti - 1998 - 694 pages
...neural network is so called the multi-layer perception (MLP) (Fig. l(b)). The architecture of an MLP consists of an input layer, one or more hidden layers and an output layer. Each neuron of the first hidden layer is connected either to all the neurons of the next hidden layer... | |
| Lakhmi C. Jain, R.P. Johnson, Yoshiyasu Takefuji, Lofti A. Zadeh - 1998 - 350 pages
...Feedforward Artificial Neural Networks The basic multi-layer feedforward net contains three components: an input layer, one or more hidden layers, and an output layer, as shown in Figure 12. Each network layer contains a set of processing units called nodes or neurons,... | |
| Max A. Bramer - 1999 - 334 pages
...was the type used in this analysis. Figure 12.1 shows the structure of a typical MLP. MLPs consist of an input layer, one or more hidden layers and an output layer. Data is fed into the input layer and transformed by weights and neurons as it flows through die network.... | |
| Ruguo Hu - 1999 - 248 pages
...into functional layers, which are organized groups of processing units. A neural network usually has an input layer, one or more hidden layers, and an output layer. The network topology is given by the number of processing units in each layer. Communication with the... | |
| 溝口理一郎 - 2000 - 858 pages
...procedure [15], a supervised mode of training. The architecture of a BP network, as shown in Figure 2, consists of an input layer, one or more hidden layers and an output layer. There are i input nodes, j hidden nodes and k output nodes. All input nodes are connected to all hidden... | |
| A. Jay White - 2000 - 224 pages
...called neurons, nodes, or cells) and connections which are organized in layers. Generally you have an input layer, one or more hidden layers and an output layer. A feedforward neural network has two or more layers, each of which gets input from the former layer.... | |
| |