The FM24C256/C256L/C256LZ devices are 256 Kbits CMOS
nonvolatile electrically erasable memory. These devices offer the
designer different low voltage and low power options. They
conform to all requirements in the Extended IIC 2-wire protocol.
Furthermore, they are designed to minimize device pin count and
simplify PC board layout requirements.
k-step ahead predictions determined by simulation of the
％ one-step ahead neural network predictor. For NNARMAX
％ models the residuals are set to zero when calculating the
％ predictions. The predictions are compared to the observed output.
％
％ 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,
％ [W1,W2,critvec,iteration,lambda]=marq(NetDef,W1,W2,PHI,Y,trparms)
％ trains the network with the Levenberg-Marquardt method.
％
％ The activation functions can be either linear or tanh. The
％ network architecture is defined by the matrix NetDef which
％ has two rows. The first row specifies the hidden layer and the
％ second row specifies the output layer.
Train a two layer neural network with a recursive prediction error
％ algorithm ("recursive Gauss-Newton"). Also pruned (i.e., not fully
％ connected) networks can be trained.
％
％ The activation functions can either be linear or tanh. The network
％ architecture is defined by the matrix NetDef , which has of two
％ rows. The first row specifies the hidden layer while the second
％ specifies the output layer.
Java is the first language to provide a cross-platform I/O library that is powerful enough to handle all these diverse tasks. Java is the first programming language with a modern, object-oriented approach to input and output. Java s I/O model is more powerful and more suited to real-world tasks than any other major language used today. Java I/O is the first and still the only book to fully expose the power and sophistication of this library.
數(shù)值計算牛頓迭代法的matlab源程序
說明如下：
％fun----input,the part as the form of f(x) in the equation f(x)=0
％ ini----input,sets the starting point to ini
％ err----input,sets admissible error
％ sol----output,returns the root of equation
