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ASSUMED

  • function y_cum = cum2x (x,y, maxlag, nsamp, overlap, flag) %CUM2X Cross-covariance % y_cum = cum2x

    function y_cum = cum2x (x,y, maxlag, nsamp, overlap, flag) %CUM2X Cross-covariance % y_cum = cum2x (x,y,maxlag, samp_seg, overlap, flag) % x,y - data vectors/matrices with identical dimensions % if x,y are matrices, rather than vectors, columns are % ASSUMED to correspond to independent realizations, % overlap is set to 0, and samp_seg to the row dimension. % maxlag - maximum lag to be computed [default = 0] % samp_seg - samples per segment [default = data_length] % overlap - percentage overlap of segments [default = 0] % overlap is clipped to the allowed range of [0,99].

    標(biāo)簽: cum2x y_cum Cross-covariance function

    上傳時(shí)間: 2015-09-08

    上傳用戶:xieguodong1234

  • This book contains a detailed analysis of the International Standard for the C language,-3.1 excludi

    This book contains a detailed analysis of the International Standard for the C language,-3.1 excluding the library from a number of perspectives. The organization of the material is unusual in that it is based on the actual text of the published C Standard. The unit of discussion is the individual sentences from the C Standard (2022 of them). Readers are ASSUMED to have more than a passing familiarity with C.

    標(biāo)簽: International the Standard analysis

    上傳時(shí)間: 2015-09-15

    上傳用戶:13188549192

  • The information in this publication is believed to be accurate as of its publication date. Such info

    The information in this publication is believed to be accurate as of its publication date. Such information is subject to change without notice and The ATM Forum is not responsible for any errors. The ATM Forum does not assume any responsibility to update or correct any information in this publication. Notwithstanding anything to the contrary, neither The ATM Forum nor the publisher make any representation or warranty, expressed or implied, concerning the completeness, accuracy, or applicability of any information contained in this publication. No liability of any kind shall be ASSUMED by The ATM Forum or the publisher as a result of reliance upon any information contained in this publication.

    標(biāo)簽: publication information believed accurate

    上傳時(shí)間: 2015-09-16

    上傳用戶:1109003457

  • //Basic packet sending test at the MAC level, used for internal testing only. //This packet test ha

    //Basic packet sending test at the MAC level, used for internal testing only. //This packet test has one node sending out a variety of //differently formatted packets to two ASSUMED destination nodes.

    標(biāo)簽: packet test internal sending

    上傳時(shí)間: 2014-08-21

    上傳用戶:CSUSheep

  • The Joint Video Team (JVT) of ISO/IEC MPEG and ITU-T VCEG are finalising a new standard for the cod

    The Joint Video Team (JVT) of ISO/IEC MPEG and ITU-T VCEG are finalising a new standard for the coding (compression) of natural video images. The new standard [1] will be known as H.264 and also MPEG-4 Part 10, “Advanced Video Coding”. The standard specifies two types of entropy coding: Context-based Adaptive Binary Arithmetic Coding (CABAC) and Variable-Length Coding (VLC). This document provides a short introduction to CABAC. Familiarity with the concept of Arithmetic Coding is ASSUMED.

    標(biāo)簽: finalising standard Joint ITU-T

    上傳時(shí)間: 2015-12-08

    上傳用戶:561596

  • PCA and PLS aims:to get some insight into the bilinear factor models Principal Component Analysis

    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(biāo)簽: Component Principal Analysis bilinear

    上傳時(shí)間: 2016-02-07

    上傳用戶:zuozuo1215

  • Application Note Abstract This Application Note introduces a complete and detailed PSoC® project

    Application Note Abstract This Application Note introduces a complete and detailed PSoC® project. Telephone Call Logger keeps the detailed record of approximately 945 phone calls (7-digit number is ASSUMED to be one phone call) including date, start time and the duration of the phone call in the PSoC device. Users can get this detailed report into the PC environment by using free software, which is included in the project file. When records reach near full capacity of the Flash memory, an LED will turn on to show that it is necessary to backup the data. Software gets the data from PSoC, organizes it and prepares a printable version. Additionally, it sends the date and time information to the PSoC. The external parts in this project can be obtained easily in the market.

    標(biāo)簽: Application Note introduces Abstract

    上傳時(shí)間: 2014-01-01

    上傳用戶:集美慧

  • The BeeStack Application Development Guide describes how to develop an application for BeeStack, in

    The BeeStack Application Development Guide describes how to develop an application for BeeStack, including discussions on major considerations for commercial applications. This document is intended for software developers who write applications for BeeStack-based products using Freescale development tools. It is ASSUMED the reader is a programmer with at least rudimentary skills in the C programming language and that the reader is already familiar with the edit/compile/debug process.

    標(biāo)簽: BeeStack Application Development application

    上傳時(shí)間: 2016-04-17

    上傳用戶:lijianyu172

  • Probabilistic Principal Components Analysis. [VAR, U, LAMBDA] = PPCA(X, PPCA_DIM) computes the princ

    Probabilistic Principal Components Analysis. [VAR, U, LAMBDA] = PPCA(X, PPCA_DIM) computes the principal % component subspace U of dimension PPCA_DIM using a centred covariance matrix X. The variable VAR contains the off-subspace variance (which is ASSUMED to be spherical), while the vector LAMBDA contains the variances of each of the principal components. This is computed using the eigenvalue and eigenvector decomposition of X.

    標(biāo)簽: Probabilistic Components Principal Analysis

    上傳時(shí)間: 2016-04-28

    上傳用戶:qb1993225

  • % DYNMODES calculates ocean dynamic vertical modes % taking a column vector of Brunt-Vaisala values

    % DYNMODES calculates ocean dynamic vertical modes % taking a column vector of Brunt-Vaisala values (Nsq) at % different pressures (p) and calculating some number of % dynamic modes (nmodes). % Note: The input pressures need not be uniformly spaced, % and the deepest pressure is ASSUMED to be the bottom.

    標(biāo)簽: Brunt-Vaisala calculates DYNMODES vertical

    上傳時(shí)間: 2013-12-06

    上傳用戶:busterman

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