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.
標簽： capacities stochastic addresses network
上傳時間： 2014-01-09
上傳用戶：二驅蚊器
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.
標簽： capacities stochastic addresses network
上傳時間： 2013-12-28
上傳用戶：獨孤求源
Techniques for storing and processing data are at the heart of all programs. The term data structure is used to describe the way data is stored, and the term algorithm is used to describe the way data is processed.
標簽： data Techniques processing structure
上傳時間： 2014-03-10
上傳用戶：cc1
The problem of image registration subsumes a number of problems and techniques in multiframe image analysis, including the computation of optic flow (general pixel-based motion), stereo correspondence, structure from motion, and feature tracking. We present a new registration algorithm based on spline representations of the displacement field which can be specialized to solve all of the above mentioned problems. In particular, we show how to compute local flow, global (parametric) flow, rigid flow resulting from camera egomotion, and multiframe versions of the above problems. Using a spline-based description of the flow removes the need for overlapping correlation windows, and produces an explicit measure of the correlation between adjacent flow estimates. We demonstrate our algorithm on multiframe image registration and the recovery of 3D projective scene geometry. We also provide results on a number of standard motion sequences.
標簽： image registration multiframe techniques
上傳時間： 2016-01-20
上傳用戶：520
Using Jacobi method and Gauss-Seidel iterative methods to solve the following system The required precision is =0.00001, and the maximum iteration number N=25. Compare the number of iterations and the convergence of these two methods
標簽： Gauss-Seidel iterative following methods
上傳時間： 2016-02-06
上傳用戶：zmy123
Generate 100 samples of a zero-mean white noise sequence with variance , by using a uniform random number generator. a Compute the autocorrelation of for . b Compute the periodogram estimate and plot it. c Generate 10 different realizations of , and compute the corresponding sample autocorrelation sequences , and . Compute the average autocorrelation sequence as and the corresponding periodogram for . d Compute and plot the average periodogram using the Bartlett method. e Comment on the results in parts (a) through (d).
標簽： zero-mean Generate sequence variance
上傳時間： 2016-03-04
上傳用戶：朗朗乾坤
(1) 、用下述兩條具體規則和規則形式實現.設大寫字母表示魔王語言的詞匯 小寫字母表示人的語言詞匯 希臘字母表示可以用大寫字母或小寫字母代換的變量.魔王語言可含人的詞匯. (2) 、B→tAdA A→sae (3) 、將魔王語言B(ehnxgz)B解釋成人的語言.每個字母對應下列的語言.
上傳時間： 2013-12-30
上傳用戶：ayfeixiao
In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets.
標簽： Rauch-Tung-Striebel algorithm smoother which
上傳時間： 2016-04-15
上傳用戶：zhenyushaw
北京大學ACM題 Here is a geometric problem. You have an angle and some squares in the first quadrant of the plane rectangular coordinates. The vertex of the angle is fixed on the origin O of the coordinates, and both of its radial lines are specified by the input. The sizes of the squares are also specified by the input, and the squares can shift vertically and horizontally. Now your job is to use the squares and the radial lines of the angle to enclose the maximum area, which excludes the area of the squares (see Figure 1). You should note that the edges of the squares must be parallel to the axes.
標簽： geometric quadrant problem squares
上傳時間： 2013-12-25
上傳用戶：ynzfm
First of all we would like to thank God Almighty for giving us the strength and confidence in pursing the ambitions. We would like to thank our Examiner Professor Axel Jantsch for allowing us to do this under his guidance and encouragement. At the same time we would like to mention our sincere thanks to Mr. Said Zainali, Manager of FRAME ACCESS AB for giving all the required equipment and the technical support which helped us to finish this thesis. We would like to mention our gratitude to our fellow VACS team members who helped us a lot during difficult times.
標簽： confidence Almighty strength giving
上傳時間： 2013-12-01
上傳用戶：小碼農lz
