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Numerical Computing with MATLAB （by Cleve Moler) is a textbook for an introductory course
in numerical methods, Matlab, and technical computing. The emphasis is on in-
formed use of mathematical software. We want you learn enough about the mathe-
matical functions in Matlab that you will be able to use them correctly, appreciate
their limitations, and modify them when necessary to suit your own needs. The
topics include
* introduction to Matlab,
* linear equations,
* interpolation,
* zero and roots,
* least squares,
* quadrature,
* ordinary di?erential equations,
* random numbers,
* Fourier analysis,
* eigenvalues and singular values,
* partial di?erential equations.
標(biāo)簽：
introductory
Numerical
Computing
textbook
上傳時(shí)間：
2016-07-04
上傳用戶(hù)：思琦琦
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Toolbox for Numerical Computing with MATLAB （by Cleve Moler).
Numerical Computing with MATLAB （by Cleve Moler) is a textbook for an introductory course
in numerical methods, Matlab, and technical computing. The emphasis is on in-
formed use of mathematical software. We want you learn enough about the mathe-
matical functions in Matlab that you will be able to use them correctly, appreciate
their limitations, and modify them when necessary to suit your own needs. The
topics include
* introduction to Matlab,
* linear equations,
* interpolation,
* zero and roots,
* least squares,
* quadrature,
* ordinary di?erential equations,
* random numbers,
* Fourier analysis,
* eigenvalues and singular values,
* partial differential equations.
標(biāo)簽：
Numerical
Computing
MATLAB
with
上傳時(shí)間：
2014-01-01
上傳用戶(hù)：guanliya
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measure through
the cross-entropy of test data. In addition,
we introduce two novel smoothing techniques,
one a variation of Jelinek-Mercer
smoothing and one a very simple linear interpolation
technique, both of which outperform
existing methods.
標(biāo)簽：
cross-entropy
introduce
smoothing
addition
上傳時(shí)間：
2014-01-06
上傳用戶(hù)：qilin
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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
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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(biāo)簽：
Practice
Introduction
Programming
Practices
上傳時(shí)間：
2013-12-16
上傳用戶(hù)：R50974
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this application was developed in visual c# to draw the sequence of the data given by Lagrange Interpolation algorithm
標(biāo)簽：
application
developed
the
Lagrange
上傳時(shí)間：
2013-12-24
上傳用戶(hù)：dreamboy36
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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(biāo)簽：
Polynomia
following
require
Number
上傳時(shí)間：
2017-09-21
上傳用戶(hù)：許小華
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matlab有限元網(wǎng)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(biāo)簽：
matlab有限元網(wǎng)格劃分程序
上傳時(shí)間：
2015-08-12
上傳用戶(hù)：凜風(fēng)拂衣袖
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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(biāo)簽：
frequency-domain
interpolation
performance
Design
kbit_s
speech
coder
based
and
of
上傳時(shí)間：
2018-04-08
上傳用戶(hù)：kilohorse
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1A/D轉(zhuǎn)換器的分類(lèi)與比較AD轉(zhuǎn)換器（ADC）是模擬系統(tǒng)與數(shù)字系統(tǒng)接口的關(guān)鍵部件，長(zhǎng)期以米一直被廣泛應(yīng)用于雷達(dá)、通信、電子對(duì)抗、聲納、衛(wèi)星、導(dǎo)彈、測(cè)控系統(tǒng)、地震、醫(yī)療、儀器儀表、圖像和音頻等領(lǐng)域。隨者計(jì)算機(jī)和通信產(chǎn)業(yè)的迅猛發(fā)展，進(jìn)一步推動(dòng)了ADC在便攜式設(shè)備上的應(yīng)用并使其有了長(zhǎng)足進(jìn)步，ADC正逐步向高速、高精度和低功耗的方向發(fā)展。通常，AD轉(zhuǎn)換器具有三個(gè)基本功能：采樣、量化和編碼。如何實(shí)現(xiàn)這三個(gè)功能，決定了AD轉(zhuǎn)換器的電路結(jié)構(gòu)和工作性能。AD轉(zhuǎn)換器的分類(lèi)很多，按采樣頻率可劃分為奈奎斯特采樣ADC和過(guò)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(jié)構(gòu)劃分為串行ADC、并行ADC和串并行ADC.在頻率范圍內(nèi)還可以按電路結(jié)構(gòu)細(xì)分為更多種類(lèi)。中低速ADC可分為積分型ADC、過(guò)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(xiàn)ADC、內(nèi)插性ADC、折疊型ADC和時(shí)間交織型ADC，下面主要介紹幾種常用的、應(yīng)用最廣泛的ADC結(jié)構(gòu)，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(xiàn)式（Pipelined）ADC和-A型A/D轉(zhuǎn)換器。
標(biāo)簽：
adc
上傳時(shí)間：
2022-06-23
上傳用戶(hù)：xsr1983
