是it f(z Figure 5.1 Single neuron model Network of neurons The basic structure for the multilayer perceptron is shown in Figure 5.2. There, the circles represent the neurons(weights bias, and activation function) and the lines represent the connections between the inputs and neurons, and between the neurons in one layer and those in the next layer. This is a three-layer perceptron since there are three stages of neural processing between the inputs and outputs. More layers can be added by concatenating additional"hidden"layers of neurons The multilayer perceptron has inputs, i=1, 2,,n, and outputs, j=1, 2,, m. The number of neurons in the first hidden layer(see Figure 5.2)is. In the second hidden layer there are neurons, and in the output layer there are m neure Hence, in an N layer perceptron there are "i neurons in the / hidden layer, i=1,2,N-I First Shead Output aidian nEde lasee Figure 5.2 multilayer perceptron models The neurons in the first layer of the multilayer perceptron perform computations, and the outputs of these neurons are x=f(∑vg"x)-6 with=1,2.n/. The neurons in the second layer of the multilayer perceptron perform computations, and the outputs of these neurons are given by x=°(∑x2)-02) withj=1,2,., nz. The neurons in the third layer of the multilayer perceptron perform computations, and the outputs of these neurons are given byFigure 5.1 Single neuron model Network of Neurons The basic structure for the multilayer perceptron is shown in Figure 5.2. There, the circles represent the neurons (weights, bias, and activation function) and the lines represent the connections between the inputs and neurons, and between the neurons in one layer and those in the next layer. This is a three-layer perceptron since there are three stages of neural processing between the inputs and outputs. More layers can be added by concatenating additional "hidden" layers of neurons. The multilayer perceptron has inputs, i = 1,2,..., n, and outputs , j =1,2,..., m. The number of neurons in the first hidden layer (see Figure 5.2) is . In the second hidden layer there are neurons, and in the output layer there are m neurons. Hence, in an N layer perceptron there are i neurons in the i n th hidden layer, i = 1,2,..., N- 1. Figure 5.2 multilayer perceptron models. The neurons in the first layer of the multilayer perceptron perform computations, and the outputs of these neurons are given by (1) (1) (1) (1) 1 (( ) ) n j j ij i j i x f wx θ = = − ∑ with j = 1,2.....n1. The neurons in the second layer of the multilayer perceptron perform computations, and the outputs of these neurons are given by 1 (2) (2) (2) (1) (2) 1 (( ) ) n j j ij i j i x f wx θ = = − ∑ with j = 1,2,..., n2. The neurons in the third layer of the multilayer perceptron perform computations, and the outputs of these neurons are given by