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self-defined

  • 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 % architecture is defined by the matrix NetDef consisting of two % rows. The first row specifies the hidden layer while the second % specifies the output layer. %

    標(biāo)簽: back-propagation corresponding input-output algorithm

    上傳時(shí)間: 2016-12-27

    上傳用戶:exxxds

  • % 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, % [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(biāo)簽: Levenberg-Marquardt desired network neural

    上傳時(shí)間: 2016-12-27

    上傳用戶:jcljkh

  • Train a two layer neural network with a recursive prediction error % algorithm ("recursive Gauss-Ne

    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(biāo)簽: recursive prediction algorithm Gauss-Ne

    上傳時(shí)間: 2016-12-27

    上傳用戶:ljt101007

  • Quartz is a full-featured, open source job scheduling system that can be integrated with, or used al

    Quartz is a full-featured, open source job scheduling system that can be integrated with, or used along side virtually any J2EE or J2SE application - from the smallest stand-alone application to the largest e-commerce system. Quartz can be used to create simple or complex schedules for executing tens, hundreds, or even tens-of-thousands of jobs jobs whose tasks are defined as standard Java components or EJBs. The Quartz Scheduler includes many enterprise-class features, such as JTA transactions and clustering.

    標(biāo)簽: full-featured integrated scheduling Quartz

    上傳時(shí)間: 2014-01-07

    上傳用戶:龍飛艇

  • Excel的強(qiáng)大函數(shù)功能

    Excel的強(qiáng)大函數(shù)功能,為我們帶來(lái)了極大方便,雖然它有200多個(gè)函數(shù),但有時(shí)我們?yōu)閷?shí)現(xiàn)一項(xiàng)規(guī)定的功能,可能用到幾個(gè)函數(shù)或者采用嵌套函數(shù),這樣應(yīng)用起來(lái),也不太方便。其實(shí)對(duì)于我們經(jīng)常用到的功能,我們可以創(chuàng)建自定義函數(shù)UDF(User—defined function),它的運(yùn)行與Excel中自帶的函數(shù)完全相同。建立自定義函數(shù)有以下幾個(gè)優(yōu)點(diǎn):建立自己特殊的功能和名稱的函數(shù);能將復(fù)雜的、嵌套的、多個(gè)原有的函數(shù)組合在一起,發(fā)揮更大的威力。

    標(biāo)簽: Excel 函數(shù)

    上傳時(shí)間: 2013-12-24

    上傳用戶:gxrui1991

  • The Software Engineering Institute’s (SEI) Capability Maturity Model (CMM) provides a well-known ben

    The Software Engineering Institute’s (SEI) Capability Maturity Model (CMM) provides a well-known benchmark of software process maturity. The CMM has become a popular vehicle for assessing the maturity of an organization’s software process in many domains. This white paper describes how the Rational Unified Process can support an organization that is trying to achieve CMM Level-2, Repeatable, and Level-3, Defined, software process maturity levels.

    標(biāo)簽: Engineering Capability well-known Institute

    上傳時(shí)間: 2017-02-27

    上傳用戶:zhichenglu

  • Measuring Frequency Content in Signals I this section we will study some non parametric methods fo

    Measuring Frequency Content in Signals I this section we will study some non parametric methods for spectrum estimation of a stochastic process. These methods are described in the literature. All methods are based on the Periodogram which is defined for a sequence x[n] with length N according to

    標(biāo)簽: parametric Measuring Frequency Content

    上傳時(shí)間: 2017-03-20

    上傳用戶:秦莞爾w

  • This book is an introduction to Ada 95. It uses an example-driven approach which gradually develops

    This book is an introduction to Ada 95. It uses an example-driven approach which gradually develops small trivial programs into large case-study type programs. The main emphasis of this book is on maintenance problems, and using object-oriented technology to write maintainable, extensible programs. Program design is introduced throughout the book, with hypothetical maintenance scenarios used to shoe design shortcomings. and revise them to accomodate maintenance needs. Practical issues such as debugging programs are tackled, and important Ada features not found in other languages are dealt with practically and early on in the text. These include exception handling, user-defined types, procedures, functions, packages and child packages.

    標(biāo)簽: example-driven introduction gradually approach

    上傳時(shí)間: 2014-01-12

    上傳用戶:koulian

  • CalcExpress is an interpreter for quick and easy evaluation of mathematical expressions. It is a sm

    CalcExpress is an interpreter for quick and easy evaluation of mathematical expressions. It is a smart tool easy in use. Supports 5 operators, parenthesis, 18 mathematical functions and user-defined variables

    標(biāo)簽: mathematical CalcExpress interpreter expressions

    上傳時(shí)間: 2014-12-08

    上傳用戶:希醬大魔王

  • MATLAB implementation of time series prediction Based on the VQTAM method described in the following

    MATLAB implementation of time series prediction Based on the VQTAM method described in the following papers: G. A. Barreto & A. F. R. Araujo (2004) "Identification and Control of Dynamical Systems Using the Self-Organizing Map" IEEE Transactions on Neural Networks, vol. 15, no. 5.

    標(biāo)簽: implementation prediction described following

    上傳時(shí)間: 2013-12-22

    上傳用戶:windwolf2000

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