meshfree method lecture notes using Radial basis function
標簽： meshfree function lecture method
上傳時間： 2013-12-18
上傳用戶：qilin
meshfree method lecture notes using Radial basis function
標簽： meshfree function lecture method
上傳時間： 2014-01-17
上傳用戶：1966640071
meshfree method lecture notes using Radial basis function
標簽： meshfree function lecture method
上傳時間： 2013-12-23
上傳用戶：z1191176801
Using Radial Basis Probabilistic Neural Network for Speech Recognition
標簽： Probabilistic Recognition Network Radial
上傳時間： 2014-01-12
上傳用戶：fxf126@126.com
自適應(Adaptive)神經網絡源程序 The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring different adaptation algorithms.~..~ There are 11 blocks that implement basically these 5 kinds of neural networks: 1) Adaptive Linear Network (ADALINE) 2) Multilayer Layer Perceptron with Extended Backpropagation algorithm (EBPA) 3) Radial Basis Functions (RBF) Networks 4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN) 5) RBF and Piecewise Linear Networks with Dynamic Cell Structure (DCS) algorithm A simulink example regarding the approximation of a scalar nonlinear function of 4 variables
標簽： collection implement Adaptive adaptive
上傳時間： 2015-04-09
上傳用戶：ywqaxiwang
The adaptive Neural Network Library is a collection of blocks that implement several Adaptive Neural Networks featuring different adaptation algorithms.~..~ There are 11 blocks that implement basically these 5 kinds of neural networks: 1) Adaptive Linear Network (ADALINE) 2) Multilayer Layer Perceptron with Extended Backpropagation algorithm (EBPA) 3) Radial Basis Functions (RBF) Networks 4) RBF Networks with Extended Minimal Resource Allocating algorithm (EMRAN) 5) RBF and Piecewise Linear Networks with Dynamic Cell Structure (DCS) algorithm A simulink example regarding the approximation of a scalar nonlinear function of 4 variables is included
標簽： Neural collection implement Adaptive
上傳時間： 2013-12-23
上傳用戶：teddysha
annie is an ANN, ie, Artificial Neural Network library developed in C++. It can be used to implement various kinds of neural networks like Multi-Layer Perceptron, Radial basis function networks, Hopfield networks etc.
標簽： Artificial developed implement Network
上傳時間： 2014-08-17
上傳用戶：trepb001
北京大學ACM題 Here is a geometric problem. You have an angle and some squares in the first quadrant of the plane rectangular coordinates. The vertex of the angle is fixed on the origin O of the coordinates, and both of its Radial lines are specified by the input. The sizes of the squares are also specified by the input, and the squares can shift vertically and horizontally. Now your job is to use the squares and the Radial lines of the angle to enclose the maximum area, which excludes the area of the squares (see Figure 1). You should note that the edges of the squares must be parallel to the axes.
標簽： geometric quadrant problem squares
上傳時間： 2013-12-25
上傳用戶：ynzfm
關于swt的布局，Radial layout 很實用的。。。。。。
上傳時間： 2017-07-21
上傳用戶：x4587
ADIAL Basis Function (RBF) networks were introduced into the neural network literature by Broomhead and Lowe [1], which are motivated by observation on the local response in biologic neurons. Due to their better approximation capabilities, simpler network structures and faster learning algorithms, RBF networks have been widely applied in many science and engineering fields. RBF network is three layers feedback network, where each hidden unit implements a Radial activation function and each output unit implements a weighted sum of hidden units’ outputs.
標簽： introduced literature Broomhead Function
上傳時間： 2017-08-08
上傳用戶：lingzhichao
