This paper examines the asymptotic (large sample) performance of a family of non-data aided feedforward (NDA FF) nonlinear least-squares (NLS) type carrier frequency estimators for burst-mode phase shift keying (PSK) modulations transmitted through AWGN and flat Ricean-fading channels. The asymptotic performance of these estimators is established in closed-form expression and compared with the modified Cram`er-Rao bound (MCRB). A best linear unbiased estimator (BLUE), which exhibits the lowest asymptotic variance within the family of NDA FF NLS-type estimators, is also proposed.
標簽： performance asymptotic examines non-data
上傳時間： 2015-12-30
上傳用戶：225588
PCA and PLS aims:to get some insight into the bilinear factor models Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression, focusing on the mathematics and numerical aspects rather than how s and why s of data analysis practice. For the latter part it is assumed (but not absolutely necessary) that the reader is already familiar with these methods. It also assumes you have had some preliminary experience with linear/matrix algebra.
標簽： Component Principal Analysis bilinear
上傳時間： 2016-02-07
上傳用戶：zuozuo1215
用游標的方法實現對稱差的計算，即 （A-B）+（B-A）
上傳時間： 2016-05-23
上傳用戶：遠遠ssad
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.
標簽： introductory Numerical Computing textbook
上傳時間： 2016-07-04
上傳用戶：思琦琦
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.
標簽： Numerical Computing MATLAB with
上傳時間： 2014-01-01
上傳用戶：guanliya
詞法分析器 對輸入一個函數，并對其分析main() { int a,b a = 10 b = a + 20 }
上傳時間： 2013-12-20
上傳用戶：hfmm633
基因算法，用VC++或MATLAB，java等工具設計一程序計算任一個隨機產生的DNA基因表達式的有效長度和值 設隨機產生的基因表達式為： + Q - / b * b a Q b a a b a a b b a a a b
上傳時間： 2014-01-09
上傳用戶：aa54
函數再現機構設計 試設計一曲柄搖桿機構，再現函數 要求： 輸入構件的轉角范圍180°，輸出構件擺角范圍30°，即： 當輸入構件從a轉至a+90時，輸出構件從b轉至b+30 當輸入構件從a+90轉至a+180時，輸出構件從b+30轉至b
上傳時間： 2013-12-17
上傳用戶：英雄
this directory contains the following: * The acdc algorithm for finding the approximate general (non-orthogonal) joint diagonalizer (in the direct Least Squares sense) of a set of Hermitian matrices. [acdc.m] * The acdc algorithm for finding the same for a set of Symmetric matrices. [acdc_sym.m](note that for real-valued matrices the Hermitian and Symmetric cases are similar however, in such cases the Hermitian version [acdc.m], rather than the Symmetric version[acdc_sym] is preferable. * A function that finds an initial guess for acdc by applying hard-whitening followed by Cardoso s orthogonal joint diagonalizer. Note that acdc may also be called without an initial guess, in which case the initial guess is set by default to the identity matrix. The m-file includes the joint_diag function (by Cardoso) for performing the orthogonal part. [init4acdc.m]
標簽： approximate directory algorithm the
上傳時間： 2014-01-17
上傳用戶：hanli8870
The toolbox solves a variety of approximate modeling problems for linear static models. The model can be parameterized in kernel, image, or input/output form and the approximation criterion, called misfit, is a weighted norm between the given data and data that is consistent with the model. There are three main classes of functions in the toolbox: transformation functions, misfit computation functions, and approximation functions. The approximation functions derive an approximate model from data, the misfit computation functions are used for validation and comparison of models, and the transformation functions are used for deriving one model representation from another. KEYWORDS: Total least squares, generalized total least squares, software implementation.
標簽： approximate The modeling problems
上傳時間： 2013-12-20
上傳用戶：15071087253
