Two scripts are included here. 1. convsys.m - combines the state space representation of two systems connected in series. [Ao,Bo,Co,Do]=convsys(A1,B1,C1,D1,A2,B2,C2,D2) This algorithm gives the convolution of two state space representations | A1 B1 | | A2 B2 | u ==> | | ==> | | ==> y | C1 D1 | | C2 D2 | The algorithm also accepts state space objects as inputs and gives out a state space object as output. 2. sysfeedbk.m [Ao,Bo,Co,Do]=convsys(A1,B1,C1,D1,A2,B2,C2,D2) Gives the closed loop state space representation for two systems connected with negative feedback in the following manner. | A1 B1 | u ==> | | ==> y + o | C1 D1 | | - | | | | A2 B2 | | |= | |= | | C2 D2 | The zip file also contains checkcompatibility.m , which checks the compatibility of matrix DIMENSIONS in the system and cleanss.m which can be used to clean a state space representation.
标签： representation included combines scripts
上传时间： 2017-07-25
上传用户：semi1981
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.
标签： 高精度格式
上传时间： 2016-01-13
上传用户：ccsdcczd
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
标签： Optimization and Uncertainty Quantification
上传时间： 2016-04-08
上传用户：huhu123456
Computes all eigenvalues and eigenvectors of a real symmetric matrix a, ! which is of size n by n, stored in a physical np by np array. ! On output, elements of a above the diagonal are destroyed. ! d returns the eigenvalues of a in its first n elements. ! v is a matrix with the same logical and physical DIMENSIONS as a, ! whose columns contain, on output, the normalized eigenvectors of a. ! nrot returns the number of Jacobi rotations that were required. ! Please notice that the eigenvalues are not ordered on output. ! If the sorting is desired, the addintioal routine "eigsrt" ! can be invoked to reorder the output of jacobi.
上传时间： 2016-06-04
上传用户：1512313
3 DIMENSIONS TV (3DTV) became commercially available in the United States in 2010 and service in other countries was expected to follow soon thereafter. 3DTV is a subset of a larger discipline known as 3D Video (3DV). There are now many routine vendor announcements related to 3DTV/3DV, and there are also conferences wholly dedicated to the topic.
标签： Transmission Encoding Content Capture 3DTV and
上传时间： 2020-05-23
上传用户：shancjb
The challenges associated with the design and implementation of Electro- static Discharge (ESD) protection circuits become increasingly complex as technology is scaled well into nano-metric regime. One must understand the behavior of semiconductor devices under very high current densities, high temperature transients in order to surmount the nano-meter ESD challenge. As a consequence, the quest for suitable ESD solution in a given technology must start from the device level. Traditional approaches of ESD design may not be adequate as the ESD damages occur at successively lower voltages in nano-metric DIMENSIONS.
标签： Protection Circuit Device Design ESD and
上传时间： 2020-06-05
上传用户：shancjb
Microengineering and Microelectromechanical systems (MEMS) have very few watertight definitions regarding their subjects and technologies. Microengineering can be described as the techniques, technologies, and practices involved in the realization of structures and devices with DIMENSIONS on the order of micrometers. MEMS often refer to mechanical devices with DIMENSIONS on the order of micrometers fabricated using techniques originating in the integrated circuit (IC) industry, with emphasis on silicon-based structures and integrated microelectronic circuitry. However, the term is now used to refer to a much wider range of microengineered devices and technologies.
标签： Microengineering Interfacing MEMS and
上传时间： 2020-06-06
上传用户：shancjb
