jboss 開發(fā)人員 手冊 JBoss: A Developer s Notebook also introduces the management console, the web services messaging features, enhanced monitoring capabilities, and shows you how to improve performance. At the end of each lab, you ll find a section called "What about..." that anticipates and answers likely follow-up questions, along with a section that points you to articles and other resources if you need more information.
標(biāo)簽： introduces management Developer the
上傳時間： 2015-04-17
上傳用戶：dreamboy36
This program demonstrates some function approximation capabilities of a Radial Basis Function Network. The user supplies a set of training points which represent some "sample" points for some arbitrary curve. Next, the user specifies the number of equally spaced gaussian centers and the variance for the network. Using the training samples, the weights multiplying each of the gaussian basis functions arecalculated using the pseudo-inverse (yielding the minimum least-squares solution). The resulting network is then used to approximate the function between the given "sample" points.
標(biāo)簽： approximation demonstrates capabilities Function
上傳時間： 2014-01-01
上傳用戶：zjf3110
The EM algorithm is short for Expectation-Maximization algorithm. It is based on an iterative optimization of the centers and widths of the kernels. The aim is to optimize the likelihood that the given data points are generated by a mixture of Gaussians. The numbers next to the Gaussians give the relative importance (amplitude) of each component.
標(biāo)簽： algorithm Expectation-Maximization iterative optimi
上傳時間： 2015-06-17
上傳用戶：獨孤求源
This is SvmFu, a package for training and testing support vector machines (SVMs). It s written in C++. It uses templates. The advantage of templates is that the types of kernel values and data points can be varied to suit the problem.
標(biāo)簽： machines training package testing
上傳時間： 2015-07-03
上傳用戶：zhengzg
realize overlapped-add method ％[y]=overlpadd(x,h,Nfft) ％y:output sequence ％x:input sequence ％h:filter impulse response sequence ％Nfft:points of each DFT operation ％重疊相加法實現(xiàn)分段卷積
標(biāo)簽： sequence overlapped-add overlpadd realize
上傳時間： 2015-07-22
上傳用戶：as275944189
PIECEWISE_EVAL: evaluates a piecewise function of x usage: y = PIECEWISE_EVAL(x,breakpoints,funs) arguments (input) x - vector or array of points to evaluate though the function breakpoints - list of n breakpoints, -inf and +inf are implicitly
標(biāo)簽： PIECEWISE_EVAL breakpoints evaluates piecewise
上傳時間： 2014-01-25
上傳用戶：xyipie
/* * EULER S ALGORITHM 5.1 * * TO APPROXIMATE THE SOLUTION OF THE INITIAL VALUE PROBLEM: * Y = F(T,Y), A<=T<=B, Y(A) = ALPHA, * AT N+1 EQUALLY SPACED points IN THE INTERVAL [A,B]. * * INPUT: ENDpoints A,B INITIAL CONDITION ALPHA INTEGER N. * * OUTPUT: APPROXIMATION W TO Y AT THE (N+1) VALUES OF T. */
標(biāo)簽： APPROXIMATE ALGORITHM THE SOLUTION
上傳時間： 2015-08-20
上傳用戶：zhangliming420
support vector classification machine ％ soft margin ％ uses "kernel.m" ％ ％ xtrain: (Ltrain,N) with Ltrain: number of points N: dimension ％ ytrain: (Ltrain,1) containing class labels (-1 or +1) ％ xrun: (Lrun,N) with Lrun: number of points N: dimension ％ atrain: alpha coefficients (from svcm_train on xtrain and ytrain) ％ btrain: offest coefficient (from svcm_train on xtrain and ytrain) ％ ％ ypred: predicted y (Lrun,1) containing class labels (-1 or +1) ％ margin: (signed) separation from the separating hyperplane (Lrun,1
標(biāo)簽： classification support machine Ltrain
上傳時間： 2015-09-04
上傳用戶：問題問題
One-channel queuing system simulator (M/M/1) * Arrival and service times are random and distributed exponetially. * * The simulator is time-slice-driven, i.e. the system model is being * run at discrete time points, with constant increments deltaT. * At each such time moment, program checks if a new item arrival or * release has occurred during previus deltaT.
標(biāo)簽： One-channel distributed and simulator
上傳時間： 2014-01-15
上傳用戶：kr770906
This paper addresses a stochastic-#ow network in which each arc or node has several capacities and may fail. Given the demand d, we try to evaluate the system reliability that the maximum #ow of the network is not less than d. A simple algorithm is proposed "rstly to generate all lower boundary points for d, and then the system reliability can be calculated in terms of such points. One computer example is shown to illustrate the solution procedure.
標(biāo)簽： capacities stochastic addresses network
上傳時間： 2015-12-03
上傳用戶：xfbs821
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