％ 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.
標簽： Levenberg-Marquardt desired network neural
上傳時間： 2016-12-27
上傳用戶：jcljkh
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.
標簽： recursive prediction algorithm Gauss-Ne
上傳時間： 2016-12-27
上傳用戶：ljt101007
Free open-source disk encryption software for Windows Vista/XP, Mac OS X, and Linux Main Features: * Creates a virtual encrypted disk within a file and mounts it as a real disk. * Encrypts an entire partition or storage device such as USB flash drive or hard drive. * Encrypts a partition or drive where Windows is installed (pre-boot authentication). * Encryption is automatic, real-time (on-the-fly) and transparent. * Provides two levels of plausible deniability, in case an adversary forces you to reveal the password: 1) hidden volume (steganography) and hidden operating system. 2) No TrueCrypt volume can be identified (volumes cannot be distinguished from random data). * Encryption algorithms: AES-256, Serpent, and Twofish. Mode of operation: XTS. Further information regarding features of the software may be found in the:http://www.truecrypt.org/
標簽： open-source encryption Features software
上傳時間： 2013-12-20
上傳用戶：123啊
The BNL toolbox is a set of Matlab functions for defining and estimating the parameters of a Bayesian network for discrete variables in which the conditional probability tables are specified by logistic regression models. Logistic regression can be used to incorporate restrictions on the conditional probabilities and to account for the effect of covariates. Nominal variables are modeled with multinomial logistic regression, whereas the category probabilities of ordered variables are modeled through a cumulative or adjacent-categories response function. Variables can be observed, partially observed, or hidden.
標簽： estimating parameters functions defining
上傳時間： 2014-12-05
上傳用戶：天誠24
It is a dark time for the Rebellion. Although the Death Star has been destroyed, Imperial troops have driven the Rebel forces from their hidden base and pursued them across the galaxy."
標簽： Rebellion destroyed the Although
上傳時間： 2017-07-04
上傳用戶：yangbo69
Steganography is the art of communicating a message by embedding it into multimedia data. It is desired to maximize the amount of hidden information (embedding rate) while preserving security against detection by unauthorized parties. An appropriate information-theoretic model for steganography has been proposed by Cachin
標簽： Steganography communicating multimedia embedding
上傳時間： 2017-07-29
上傳用戶：
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
The software and hardware development fields evolved along separate paths through the end of the 20th century. We seem to have come full circle, however. The previously rigid hardware on which our programs run is softening in many ways. Embedded systems are largely responsible for this softening. These hidden computing systems drive the electronic products around us, including consumer products like digital cameras and personal digital assistants, office automation equipment like copy machines and printers, medical devices like heart monitors and ventilators, and automotive electronics like cruise controls and antilock brakes. Embedded systems force designers to work under incredibly tight time-tomarket, power consumption, size, performance, flexibility, and cost constraints. Many technologies introduced over the past two decades have sought to help satisfy these constraints. To understand these technologies, it is important to first distinguish the underlying embedded systems elements.
標簽： development the software hardware
上傳時間： 2017-08-15
上傳用戶：cjf0304
C++ From Scratch: An Object-Oriented Approach is designed to walk novice programmers through the analysis, design and implementation of a functioning object-oriented application using C++. You will learn all the critical programming concepts and techniques associated with the language in the context of creating a functioning application. Best selling C++ author Jesse Liberty shows you how to create "Decryptix", a game of decoding a hidden pattern as quickly as possible, using nothing but successive guesses and the application of logic. Every example and technique is put into the context of achieving a goal and accomplishing an end.
標簽： Object-Oriented programmers Approach designed
上傳時間： 2013-12-25
上傳用戶：225588
Windows CMD Emulator is Based Upon Creating a Pipe to Read and Write Data to, it Opens a CMD Window hidden and Starts Sending and Receiving Data from it using a simple SetTimer Event
標簽： CMD Emulator Creating Windows
上傳時間： 2014-01-03
上傳用戶：上善若水
