matlab有限元网格划分程序 DistMesh is a simple MATLAB code for generation of unstructured triangular and tetrahedral meshes. It was developed by Per-Olof Persson (now at UC Berkeley) and Gilbert Strang in the Department of Mathematics at MIT. A detailed description of the program is provided in our SIAM Review paper, see documentation below. One reason that the code is short and simple is that the geometries are specified by Signed Distance Functions. These give the shortest distance from any point in space to the boundary of the domain. The sign is negative inside the region and positive outside. A simple example is the unit circle in 2-D, which has the distance function d=r-1, where r is the distance from the origin. For more complicated geometries the distance function can be computed by interpolation between values on a grid, a common REPRESENTATION for level set methods. For the actual mesh generation, DistMesh uses the Delaunay triangulation routine in MATLAB and tries to optimize the node locations by a force-based smoothing procedure. The topology is regularly updated by Delaunay. The boundary points are only allowed to move tangentially to the boundary by projections using the distance function. This iterative procedure typically results in very well-shaped meshes. Our aim with this code is simplicity, so that everyone can understand the code and modify it according to their needs. The code is not entirely robust (that is, it might not terminate and return a well-shaped mesh), and it is relatively slow. However, our current research shows that these issues can be resolved in an optimized C++ code, and we believe our simple MATLAB code is important for demonstration of the underlying principles. To use the code, simply download it from below and run it from MATLAB. For a quick demonstration, type "meshdemo2d" or "meshdemond". For more details see the documentation.
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INTRODUCTION In the past, adding speech recording and playback capability to a product meant using a digital signal processor or a specialized audio chip. Now, using a simplified Adaptive Differential Pulse Code Modulation(ADPCM) algorithm, these audio capabilities can be added to any PICmicro device. This application note will cover the ADPCM compression and decompression algorithms, performance comparison of all PICmicro devices, and an application using a PIC16C72 micro-controller.DEFINITION OF TERMS step size -value of the step used for quantization of ana-log signals and inverse quantization of a number of steps.quantization -the digital form of an analog input signal is represented by a finite number of steps.adaptive quantization -the step size of a quantizer is dramatically changed with time in order to adapt to a changing input signal.inverse quantizer -a finite number of steps is converted into a digital REPRESENTATION of an analog signal.
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