...Rumelhart et al. 1986b). 4.1 The Basic Idea A basic backward error propagation network consists of an input layer, an output layer, and one or more hidden layers connected in a feedforward fashion (figure 4.1). Before training, a set of desired input —> output...

...architecture of a feed-forward fully interconnected neural network is shown in Fig. l7-l6. The network has an input layer, an output layer, and one or more hidden layers. An input pattern is presented to the input layer. Each unit in the input layer outputs to each unit...

...propagation algorithm (BP network) is used widely. Figure 1 shows a typical BP network which consists of an input layer, an output layer, and one or more hidden layers. In this paper the BP network is employed. A detailed description of the BP network is beyond the scope...

...continued. This type of network, where data flow on way (forward), is known as a feed-forward network. A feed-forward ANN has an input layer, an output layer, and one or more hidden layers between the input and output layers. Each of the neurons in a layer is connected to all the neurons...

...combining many neurons in a layer or in many layers (Fig. 2). The different layers play different roles and an input layer, an output layer, and one or more hidden layers between them can be distinguished. It is notable that the output of a layer represents the input for...

...used forms of ANN is the multi-layer perceptron (MLP). Multilayer perceptrons typically consist of an input layer, an output layer, and one or more hidden layers (where a layer contains nodes or processing elements). Adjacent layers are fully interconnected by...

...contains possible solutions to the problem. Feed-forward network A *multilayer neural network with an input layer, an output layer, and one or more hidden layers. Filter A function that, when applied to an image, removes all undesired parts of the image. For example,...

...nonlinear processing elements referred to as neurons or nodes, arranged in several layers including an input layer, an output layer, and one or more hidden layer(s) in between. Each of the layers consists of one or more neurons and output of every neuron is fed to neurons in...

...specific function and are processed as a whole. The most common example is in a feedforward ANN that has an input layer, an output layer, and one or more hidden layers. Layer Diagram: An ANN architecture figure showing the layers and the weight matrices connecting them....

...of these outputs by finding the optimal weight values. The basic architecture of a BPNN consists of an input layer, an output layer, and one or more hidden layers of neurons. The training of the BPNN involves three phases: the feed forward of the input training...