Topics Practices: Programming and Numerical Methods Practice 1: Introduction to C Practice 2: Cycles and functions First part cycles Part Two: Roles Practice 3 - Floating point arithmetic Practice 4 - Search for roots of functions Practice 5 - Numerical Integration Practice 6 - Arrangements and matrices Part One: Arrangements Part II: Matrices Practice 7 - Systems of linear equations Practice 8 - INTERPOLATION Practice 9 - Algorithm Design Techniques
標簽： Practice Introduction Programming Practices
上傳時間： 2013-12-16
上傳用戶：R50974
this application was developed in visual c# to draw the sequence of the data given by Lagrange INTERPOLATION algorithm
標簽： application developed the Lagrange
上傳時間： 2013-12-24
上傳用戶：dreamboy36
These codes require an ASCII input file interp.dat of the following form: N: Number of Polynomial INTERPOLATION Points (Small) First Sample (x1,y1) Second Sample (x2,y2) ... Nth Sample (xN,yN) N1: Number of Error Evaluation Points (Large) First Sample (x1,y1) Second Sample (x2,y2) ... N1th Sample (xN1,yN1)
標簽： Polynomia following require Number
上傳時間： 2017-09-21
上傳用戶：許小華
matlab有限元網格劃分程序 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.
標簽： matlab有限元網格劃分程序
上傳時間： 2015-08-12
上傳用戶：凜風拂衣袖
The 4.0 kbit/s speech codec described in this paper is based on a Frequency Domain Interpolative (FDI) coding technique, which belongs to the class of prototype waveform INTERPOLATION (PWI) coding techniques. The codec also has an integrated voice activity detector (VAD) and a noise reduction capability. The input signal is subjected to LPC analysis and the prediction residual is separated into a slowly evolving waveform (SEW) and a rapidly evolving waveform (REW) components. The SEW magnitude component is quantized using a hierarchical predictive vector quantization approach. The REW magnitude is quantized using a gain and a sub-band based shape. SEW and REW phases are derived at the decoder using a phase model, based on a transmitted measure of voice periodicity. The spectral (LSP) parameters are quantized using a combination of scalar and vector quantizers. The 4.0 kbits/s coder has an algorithmic delay of 60 ms and an estimated floating point complexity of 21.5 MIPS. The performance of this coder has been evaluated using in-house MOS tests under various conditions such as background noise. channel errors, self-tandem. and DTX mode of operation, and has been shown to be statistically equivalent to ITU-T (3.729 8 kbps codec across all conditions tested.
標簽： frequency-domain INTERPOLATION performance Design kbit_s speech coder based and of
上傳時間： 2018-04-08
上傳用戶：kilohorse
1A/D轉換器的分類與比較AD轉換器（ADC）是模擬系統與數字系統接口的關鍵部件，長期以米一直被廣泛應用于雷達、通信、電子對抗、聲納、衛星、導彈、測控系統、地震、醫療、儀器儀表、圖像和音頻等領域。隨者計算機和通信產業的迅猛發展，進一步推動了ADC在便攜式設備上的應用并使其有了長足進步，ADC正逐步向高速、高精度和低功耗的方向發展。通常，AD轉換器具有三個基本功能：采樣、量化和編碼。如何實現這三個功能，決定了AD轉換器的電路結構和工作性能。AD轉換器的分類很多，按采樣頻率可劃分為奈奎斯特采樣ADC和過采樣ADC，奈奎斯特采樣ADC又可劃分為高速ADC、中速ADC和低速ADC：按性能劃分為高速ADC和高精度ADC：按結構劃分為串行ADC、并行ADC和串并行ADC.在頻率范圍內還可以按電路結構細分為更多種類。中低速ADC可分為積分型ADC、過采樣Sigma-Delta型 ADC、逐次逼近型ADC，Algonithmic ADC：高速ADC可以分為閃電式ADC、兩步型ADC、流水線ADC、內插性ADC、折疊型ADC和時間交織型ADC，下面主要介紹幾種常用的、應用最廣泛的ADC結構，它們是：逐次比較式（SAR）ADC、快閃式（Flash）ADC、折疊插入式（Fol ding&INTERPOLATION）ADC、流水線式（Pipelined）ADC和-A型A/D轉換器。
標簽： adc
上傳時間： 2022-06-23
上傳用戶：xsr1983
