*** *** *** *** *** *** *****
** Two wire/I2C Bus READ/WRITE Sample Routines of Microchip s
** 24Cxx / 85Cxx serial CMOS EEPROM interfacing to a
** PIC16C54 8-bit CMOS single chip microcomputer
** Revsied Version 2.0 (4/2/92).
**
** Part use = PIC16C54-XT/JW
** Note: 1) All timings are based on a reference crystal frequency of 2MHz
** which is equivalent to an instruction cycle time of 2 usec.
** 2) Address and literal values are read in octal unless otherwise
** specified.
measure through
the cross-entropy of test data. In addition,
we introduce two novel smoothing techniques,
one a variation of Jelinek-Mercer
smoothing and one a very simple linear interpolation
technique, both of which outperform
existing methods.
％ 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.
This work briefly explains common cryptosystems and details two most popular private-key ciphers: DES ,which is probably the most widely used, and AES, which is intended to replace DES.
This paper studies the problem of tracking a ballistic object in
the reentry phase by processing radar measurements. A suitable
(highly nonlinear) model of target motion is developed and the
theoretical Cramer—Rao lower bounds (CRLB) of estimation
error are derived. The estimation performance (error mean and
This paper studies the problem of tracking a ballistic object in
the reentry phase by processing radar measurements. A suitable
(highly nonlinear) model of target motion is developed and the
theoretical Cramer—Rao lower bounds (CRLB) of estimation
error are derived. The estimation performance (error mean and
