“hidden layer”造句，怎麼用hidden layer造句

5、Yet with little damage the result is relatively low. To resolve the problem, augmenting node of hidden layer or number of hidden layer.

7、The method determining the number of hidden layer node is mainly studied in this paper.

9、Besides, the selection of nodal points of hidden layer neuron network based on BP is key to the performance of image network, so it is a must to select proper nodal points of the hidden layer.

11、First, the usual ways that are employed to choose the number of RBFNN's hidden layer nodes are analyzed and compared.

13、The choice of quantity and position of hidden layer radial basis functions is very important and directly affects the goodness of fit of overall network classification ability.

15、Meantime, the prediction error has a certain regularity of the change of hidden layer, so there is a best number to make the prediction error least.

17、This setting will create a neural network model that does not contain a hidden layer, and that therefore is equivalent to logistic regression.

19、The role of hidden layer neurons of a RBF neural network can be interpreted as a function which maps input patterns from a nonlinear separable space to a linear separable space.

2、We have studied that the variable structure neural network for single hidden layer and multi hidden layer.

4、The chosen neural network architecture consisted of one input layer, one hidden layer and the output layer.

8、A novel three-layer neural network with knowledge-based neurons (NNKBN) in hidden layer has been applied to model the crossover discontinuities in stripline circuits.

12、This paper investigates the identification of unknown nonlinear dynamical system using multilayered feedforward neural network with a single hidden layer.

16、The first network is BP network with one hidden layer, and the second network is linear status Neural network based on linear system dynamic equation.

1、Toggling layer visibility no longer makes a hidden layer active.

6、This paper proposes a hidden layer structure adaptive radial basis function (HSARBF) classifier.

14、The equalizer is constructed with decision feedback structure, and an immune algorithm is used to determine the structure and parameters of RBF nonlinear hidden layer.

3、Through the analysis of character features, confirm the input layer, hidden layer and the License of output layer units.

18、In this scheme, the inputs of hidden layer neurons are acquired by using the gradient descent method, and the weights and threshold of each neuron are trained using the linear least square method.

10、All hidden units in the last of the hidden layers are connected with units in the input layer. There are one or several nodal points in the output layer which generate output data.