消息中間件(Message—OrientedMiddleware，簡(jiǎn)稱(chēng)MOM)提供客戶(hù)和服務(wù)器的同步和異步連接，并且在任意的時(shí)刻對(duì)消息進(jìn)行傳送和存儲(chǔ)轉(zhuǎn)發(fā)。消息的傳輸一般都支持Point—to—Point模式和Publish／Subscribe模式。消息中間件為大規(guī)模分布式環(huán)境下應(yīng)用程序的集成提供了一種有力的集成工具。越來(lái)越多的分布式應(yīng)用采用消息中間件，通過(guò)消息中間件把應(yīng)用擴(kuò)展到不同的操作系統(tǒng)和不同的網(wǎng)絡(luò)環(huán)境。
標(biāo)簽： OrientedMiddleware Message
上傳時(shí)間： 2013-12-20
上傳用戶(hù)：天誠(chéng)24
遺傳算法和“貨郎擔(dān)” 問(wèn)題: "The traveling salesman problem, or TSP for short, is this: given a finite number of cities along with the cost of travel between each pair of them, find the cheapest way of visiting all the cities and returning to your starting point."
標(biāo)簽： traveling salesman problem finite
上傳時(shí)間： 2013-12-24
上傳用戶(hù)：watch100
This directory includes matlab interface of the curvelet transform using usfft. Basic functions fdct_usfft.m -- forward curvelet transform afdct_usfft.m -- adjoint curvelet transform ifdct_usfft.m -- inverse curvelet transform fdct_usfft_param.m -- returns the location of each curvelet in phase-space Useful tools fdct_usfft_dispcoef.m -- returns a matrix contains all curvelet coefficients fdct_usfft_pos2idx.m -- for fixed scale and fixed direction, returns the curvelet which is closest to a certain point on the image Demos fdct_usfft_demo_basic.m -- display the shape of a curvelet fdct_usfft_demo_recon.m -- partial reconstruction using curvelet fdct_usfft_demo_disp.m -- display all the curvelet coefficients of an image fdct_usfft_demo_denoise.m -- image denoising using curvelet
標(biāo)簽： directory functions interface transform
上傳時(shí)間： 2016-08-31
上傳用戶(hù)：cooran
CCE is a multi-instance learning method solving multi-instance problems through adapting multi-instance representation to single-instance algorithms, which is quite different from existing multi-instance learning algorithms which attempt to adapt single-instance algorithms to multi-instance representation
標(biāo)簽： multi-instance multi-insta adapting learning
上傳時(shí)間： 2014-01-14
上傳用戶(hù)：manlian
數(shù)值計(jì)算牛頓迭代法的matlab源程序 說(shuō)明如下： ％fun----input,the part as the form of f(x) in the equation f(x)=0 ％ ini----input,sets the starting point to ini ％ err----input,sets admissible error ％ sol----output,returns the root of equation
標(biāo)簽： the equation matlab input
上傳時(shí)間： 2014-01-12
上傳用戶(hù)：妄想演繹師
C programs for adding two matrices parallely usinf Parallel Virtual Machine(PVM).It is working and can be used as a starting point to familiarize PVM
標(biāo)簽： parallely programs Parallel matrices
上傳時(shí)間： 2014-01-12
上傳用戶(hù)：許小華
P3.20. Consider an analog signal xa (t) = sin (2πt), 0 ≤t≤ 1. It is sampled at Ts = 0.01, 0.05, and 0.1 sec intervals to obtain x(n). b) Reconstruct the analog signal ya (t) from the samples x(n) using the sinc interpolation (use ∆ t = 0.001) and determine the frequency in ya (t) from your plot. (Ignore the end effects.) C) Reconstruct the analog signal ya (t) from the samples x (n) using the cubic spline interpolation and determine the frequency in ya (t) from your plot. (Ignore the end effects.)
標(biāo)簽： Consider sampled analog signal
上傳時(shí)間： 2017-07-12
上傳用戶(hù)：咔樂(lè)塢
Use the fast Fourier transform function fft to analyse following signal. Plot the original signal, and the magnitude of its spectrum linearly and logarithmically. Apply Hamming window to reduce the leakage. . The hamming window can be coded in Matlab as for n=1:N hamming(n)=0.54+0.46*cos((2*n-N+1)*pi/N); end; where N is the data length in the FFT.
標(biāo)簽： matlab fft
上傳時(shí)間： 2015-11-23
上傳用戶(hù)：石灰?guī)r123
Use fft to analyse signal by plotting the original signal and its spectrum.
標(biāo)簽： matlab fft
上傳時(shí)間： 2015-11-23
上傳用戶(hù)：石灰?guī)r123
We introduce a sub-cell WENO reconstruction method to evaluate spatial derivatives in the high-order ADER scheme. The basic idea in our reconstruction is to use only r stencils to reconstruct the point-wise values of solutions and spatial derivatives for the 2r-1 th order ADER scheme in one dimension, while in two dimensions, the dimension-by-dimension sub-cell reconstruction approach for spatial derivatives is employed. Compared with the original ADER scheme of Toro and Titarev (2002) [2] that uses the direct derivatives of reconstructed polynomials for solutions to evaluate spatial derivatives, our method not only reduces greatly the computational costs of the ADER scheme on a given mesh, but also avoids possible numerical oscillations near discontinuities, as demonstrated by a number of one- and two-dimensional numerical tests. All these tests show that the 5th-order ADER scheme based on our sub-cell reconstruction method achieves the desired accuracy, and is essentially non-oscillatory and computationally cheaper for problems with discontinuities.
標(biāo)簽： 高精度格式
上傳時(shí)間： 2016-01-13
上傳用戶(hù)：ccsdcczd
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