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The problem of ¯ nding a linear discriminant function will be formulated as a problem of minimizing a criterion function
標(biāo)簽： problem discriminant formulated function
上傳時(shí)間： 2014-11-30
上傳用戶(hù)：15071087253
二維SIMPLEC程序，包含三個(gè)project:二維穩(wěn)態(tài)傳熱，常粘度系數(shù)湍流的動(dòng)態(tài)模擬，湍流中被動(dòng)標(biāo)量擴(kuò)散（基于時(shí)均的 k –ε方程． 同時(shí)壓縮包中還有詳細(xì)的說(shuō)明文檔． 注意：本程序只限于學(xué)習(xí)用途，切勿作商業(yè)用途，作者享有對(duì)此代碼及使用目的的最終解釋權(quán)！ Cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc Cccc This computer program was copied from the graduate student course program Cccc of the University of Minnesota. Part of it was re-formulated to meet the Cccc personal computer environment. Some inappropriate expressions were also Cccc corrected. The program is used only for teaching purpose. No part of it Cccc may be published. You may use it as a frame to re-develop your own code Cccc for research purpose. XJTU Instructor, 1995.11 Cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc
上傳時(shí)間： 2015-12-10
上傳用戶(hù)：大三三
這是一個(gè)模擬第3類(lèi)模式地震波的matlab腳本。 This a collection of Matlab scripts that solve the antiplane (mode III) earthquake dynamic problem with slip-weakening friction, on a 1D fault embedded in a 2D homogeneous elastic unbounded medium. The problem is formulated as a boundary integral equation and the elastodynamic kernels are analytically derived in the spectral domain (spatial wavenumber). The method is explained e.g. by Morrysey and Geubelle (1997), and has been improved and extensively used by Nadia Lapusta, Alain Cochard, etc.
標(biāo)簽： collection antiplane scripts matlab
上傳時(shí)間： 2013-12-26
上傳用戶(hù)：遠(yuǎn)遠(yuǎn)ssad
The Hilbert Transform is an important component in communication systems, e.g. for single sideband modulation/demodulation, amplitude and phase detection, etc. It can be formulated as filtering operation which makes it possible to approximate the Hilbert Transform with a digital filter. Due to the non-causal and infinite impulse response of that filter, it is not that easy to get a good approximation with low hardware resource usage. Therefore, different filters with different complexities have been implemented. The detailed discussion can be found in "Digital Hilbert Transformers or FPGA-based Phase-Locked Loops" (http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=4629940). The design is fully pipelined for maximum throughput.
標(biāo)簽： e.g. communication Transform important
上傳時(shí)間： 2017-06-25
上傳用戶(hù)：gxf2016
Computational models are commonly used in engineering design and scientific discovery activities for simulating complex physical systems in disciplines such as fluid mechanics, structural dynamics, heat transfer, nonlinear structural mechanics, shock physics, and many others. These simulators can be an enormous aid to engineers who want to develop an understanding and/or predictive capability for complex behaviors typically observed in the corresponding physical systems. Simulators often serve as virtual prototypes, where a set of predefined system parameters, such as size or location dimensions and material properties, are adjusted to improve the performance of a system, as defined by one or more system performance objectives. Such optimization or tuning of the virtual prototype requires executing the simulator, evaluating performance objective(s), and adjusting the system parameters in an iterative, automated, and directed way. System performance objectives can be formulated, for example, to minimize weight, cost, or defects; to limit a critical temperature, stress, or vibration response; or to maximize performance, reliability, throughput, agility, or design robustness. In addition, one would often like to design computer experiments, run parameter studies, or perform uncertainty quantification (UQ). These approaches reveal how system performance changes as a design or uncertain input variable changes. Sampling methods are often used in uncertainty quantification to calculate a distribution on system performance measures, and to understand which uncertain inputs contribute most to the variance of the outputs. A primary goal for Dakota development is to provide engineers and other disciplinary scientists with a systematic and rapid means to obtain improved or optimal designs or understand sensitivity or uncertainty using simulationbased models. These capabilities generally lead to improved designs and system performance in earlier design stages, alleviating dependence on physical prototypes and testing, shortening design cycles, and reducing product development costs. In addition to providing this practical environment for answering system performance questions, the Dakota toolkit provides an extensible platform for the research and rapid prototyping of customized methods and meta-algorithms
標(biāo)簽： Optimization and Uncertainty Quantification
上傳時(shí)間： 2016-04-08
上傳用戶(hù)：huhu123456
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