搜索结果
找到约 6 项符合
input-output 的查询结果
matlab例程 To estimate the input-output mapping with inputs x % and outputs y generated by the following nonli
To estimate the input-output mapping with inputs x
% and outputs y generated by the following nonlinear,
% nonstationary state space model:
% x(t+1) = 0.5x(t) + [25x(t)]/[(1+x(t))^(2)]
% + 8cos(1.2t) + process noise
% y(t) = x(t)^(2) / 20 + 6 squareWave(0.05(t-1)) + 3
% + time varying measur ...
数值算法/人工智能 Batch version of the back-propagation algorithm. % Given a set of corresponding input-output pairs
Batch version of the back-propagation algorithm.
% Given a set of corresponding input-output pairs and an initial network
% [W1,W2,critvec,iter]=batbp(NetDef,W1,W2,PHI,Y,trparms) trains the
% network with backpropagation.
%
% The activation functions must be either linear or tanh. The network
...
VxWorks Demo Source Code VxDemo Groups: 1. Multi-Processing 2. Networking 3. Input-Output
Demo Source Code
VxDemo Groups:
1. Multi-Processing
2. Networking
3. Input-Output
4. File System
5. MMU
6. Multi-Tasking
7. ANSI-C
8. POSIX
9. ExecHandling
Java书籍 The book presents the entire Java programming language and essential parts of the class libraries: t
The book presents the entire Java programming language and essential parts of the class libraries: the collection classes and the input-output classes.
电子书籍 This book gives a concise description of the Java 2 programming language. They give a quick referen
This book gives a concise description of the Java 2 programming language. They give a quick reference for the reader who has already learned (or is learning) Java from a standard textbook
and who wants to know the language in more detail. These book presents the entire Java programming language an ...
人工智能/神经网络 % Train a two layer neural network with the Levenberg-Marquardt % method. % % If desired, it is p
% Train a two layer neural network with the Levenberg-Marquardt
% method.
%
% If desired, it is possible to use regularization by
% weight decay. Also pruned (ie. not fully connected) networks can
% be trained.
%
% Given a set of corresponding input-output pairs and an initial
% network,
% ...