Location:
Search - .vectors d
Search list
Description: The objective of this projectis to design, model and simulate an autocorrelation
generator circuit using 4-bit LFSR. the register and LFSR will used D flip-flop and some
gates. By the autocorrelation concept, there should be 2 same length vectors, for calculating
the autocorrelation , we have to design the register for storing the original vector and the
shifter for make time delay.
-The objective of this projectis to design, model and simulate an autocorrelation generat or circuit using 4-bit LFSR. the register and LF SR will used D flip-flop and some gates. By the au tocorrelation concept, there should be two same length vectors, for calculating the autocorrelation. we have to design the register or for storing the iginal vector and the shifter for make time Abuelas y.
Platform: |
Size: 13259 |
Author: yangzq |
Hits:
Description: % EM algorithm for k multidimensional Gaussian mixture estimation
%
% Inputs:
% X(n,d) - input data, n=number of observations, d=dimension of variable
% k - maximum number of Gaussian components allowed
% ltol - percentage of the log likelihood difference between 2 iterations ([] for none)
% maxiter - maximum number of iteration allowed ([] for none)
% pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none)
% Init - structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none)
%
% Ouputs:
% W(1,k) - estimated weights of GM
% M(d,k) - estimated mean vectors of GM
% V(d,d,k) - estimated covariance matrices of GM
% L - log likelihood of estimates
%
Platform: |
Size: 3416 |
Author: Shaoqing Yu |
Hits:
Description: The objective of this projectis to design, model and simulate an autocorrelation
generator circuit using 4-bit LFSR. the register and LFSR will used D flip-flop and some
gates. By the autocorrelation concept, there should be 2 same length vectors, for calculating
the autocorrelation , we have to design the register for storing the original vector and the
shifter for make time delay.
-The objective of this projectis to design, model and simulate an autocorrelation generat or circuit using 4-bit LFSR. the register and LF SR will used D flip-flop and some gates. By the au tocorrelation concept, there should be two same length vectors, for calculating the autocorrelation. we have to design the register or for storing the iginal vector and the shifter for make time Abuelas y.
Platform: |
Size: 13312 |
Author: yangzq |
Hits:
Description: % EM algorithm for k multidimensional Gaussian mixture estimation
%
% Inputs:
% X(n,d) - input data, n=number of observations, d=dimension of variable
% k - maximum number of Gaussian components allowed
% ltol - percentage of the log likelihood difference between 2 iterations ([] for none)
% maxiter - maximum number of iteration allowed ([] for none)
% pflag - 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none)
% Init - structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none)
%
% Ouputs:
% W(1,k) - estimated weights of GM
% M(d,k) - estimated mean vectors of GM
% V(d,d,k) - estimated covariance matrices of GM
% L - log likelihood of estimates
%- EM algorithm for k multidimensional Gaussian mixture estimation Inputs: X (n, d)- input data, n = number of observations, d = dimension of variable k- maximum number of Gaussian components allowed ltol- percentage of the log likelihood difference between 2 iterations ([] for none) maxiter- maximum number of iteration allowed ([] for none) pflag- 1 for plotting GM for 1D or 2D cases only, 0 otherwise ([] for none) Init- structure of initial W, M, V: Init.W, Init.M, Init.V ([] for none) Ouputs: W (1, k)- estimated weights of GM M (d, k)- estimated mean vectors of GM V (d, d, k)- estimated covariance matrices of GM L- log likelihood of estimates
Platform: |
Size: 3072 |
Author: Shaoqing Yu |
Hits:
Description: 基于C语言设置TMS320 DSP中断向量表: 随着DSP芯片应用的不断深入,用C语言开发DSP芯片,不仅可以使DSP芯片的开发速度大大提高,也使得程序的修改和移植变得十分方便。C语言设置TMS320系列DSP中断向量表是高级语言开发DSP的一个具体应用。-Based on the C language settings TMS320 DSP Interrupt Vector Table: With the continuous application of DSP chips in depth, using C language to develop DSP chips, not only enable the development of DSP chips significantly enhance the speed, but also makes changes to procedures and transplantation has become very convenient. C language settings TMS320 series DSP interrupt vector table is a high-level language to develop a specific application of DSP.
Platform: |
Size: 4096 |
Author: 小艾 |
Hits:
Description: The inverse of the gradient function. I ve provided versions that work on 1-d vectors, or 2-d or 3-d arrays. In the 1-d case I offer 5 different methods, from cumtrapz, and an integrated cubic spline, plus several finite difference methods.
In higher dimensions, only a finite difference/linear algebra solution is provided, but it is fully vectorized and fully sparse in its approach. In 2-d and 3-d, if the gradients are inconsistent, then a least squares solution is generated
Platform: |
Size: 11264 |
Author: 徐亮 |
Hits:
Description: 非常不错的科学类绘图软件,是地质工作者必备的专业成图软件。8.0是目前最新的版本,可以轻松制作基面图、数据点位图、分类数据图、等值线图、线框图、地形地貌图、趋势图、矢量图以及三维表面图等;-Science is very good mapping software is necessary for professional geologists mapping software. 8.0 is the latest version, you can make it easy to create base maps, digital map data points, data map, contour map, wireframe map, topography map, trends, vectors, as well as three-dimensional surface map
Platform: |
Size: 12997632 |
Author: xiaohui |
Hits:
Description: Generic canvas class that can be used to visualize 1-D vectors in Java applications and applets. Allows to be customized in various ways.
Platform: |
Size: 2048 |
Author: xyzyx |
Hits:
Description: OpenGL 程序指导红皮书,Color Plates
Glossary (not included in this version) -OpenGL Programming Guide
or The Red Book
About This Guide
Chapter 1: Introduction to OpenGL
Chapter 2: Drawing Geometric Objects
Chapter 3: Viewing
Chapter 4: Display Lists
Chapter 5: Color
Chapter 6: Lighting
Chapter 7: Blending, Antialiasing, and Fog
Chapter 8: Drawing Pixels, Bitmaps, Fonts, and Images
Chapter 9: Texture Mapping
Chapter 10: The Framebuffer
Chapter 11: Evaluators and NURBS
Chapter 12: Selection and Feedback
Chapter 13: Now That You Know
Appendix A: Order of Operations
Appendix B: OpenGL State Variables
Appendix C: The OpenGL Utility Library
Appendix D: The OpenGL Extension to the X Window System
Appendix E: The OpenGL Programming Guide Auxiliary Library
Appendix F: Calculating Normal Vectors
Appendix G: Homogeneous Coordinates and Transformation Matrices
Appendix H: Programming Tips
Appendix I: OpenGL Invariance
Appendix J: Color Plates
Glossary (not included in this version)
Platform: |
Size: 6776832 |
Author: yangfu |
Hits:
Description: 给出变量的上下边界、初值和代价函数,能够搜索代价函数最小值时的变量取值。属于带约束的优化算法,可以用来求算非线性方程组。-STRSCNE is a Matlab code for constrained nonlinear systems of equations
F(x)=0 l<=x<=u
where F: R^n--> R^n, l and u are vectors of dimension n. Non-existent lower and upper bounds, i.e.
entries of l and u equal to minus o plus infinity, are allowed.
The algorithm is a globally convergent procedure that combines Newton method and an elliptical trust-region approach. The elliptical trust-region is defined employing a scaling diagonal matrix D
and the trust-region subproblem is approximately solved by the dogleg method. Only strictly feasible iterates are generated.
Various input/output options are provided, and we refer to the code itself for further documentation.
Platform: |
Size: 5120 |
Author: muxihan |
Hits:
Description: ITU-T G.722.2
国际电信联盟G.722.2建议书,2003年7月版。该建议书是语音通讯领域的压缩标准,被GSM,WCDMA,3GPP等采用,题目为16kbit下的宽带语音编码,使用自适应多率宽带编码。
内容主要有代数码激励线性预测编码(ACELP),话音活动检测(VAD)等。-This Recommendation describes the high quality Adaptive Multi-Rate Wideband (AMR-WB)
encoder and decoder that is primarily intended for 7 kHz bandwidth speech signals. AMR-WB
operates at a multitude of bit rates ranging from 6.6 kbit/s to 23.85 kbit/s. The bit rate may be
changed at any 20-ms frame boundary.
Annex C includes an integrated C source code software package which contains the implementation
of the G.722.2 encoder and decoder and its Annexes A and B and Appendix I. A set of digital test
vectors for developers is provided in Annex D. These test vectors are a verification tool providing an
indication of success in implementing this codec.
G.722.2 AMR-WB is the same codec as the 3GPP AMR-WB. The corresponding 3GPP
specifications are TS 26.190 for the speech codec and TS 26.194 for the Voice Activity Detector.
Platform: |
Size: 728064 |
Author: 刘涛 |
Hits:
Description: 1.将所要制作成BOOT的程序,在编译之前将其中断向量映射到3F80,
寄存器PMST的值置为3FA0.
2.在CCS中,编译该程序时,加上-v548选项,如下所示:
打开PROJECT->BUILD OPTIONS->COMPILER
-g -as -fr"D:\myprojects\dspii_g\vc5402\lcd" -v548
同时,在PROJECT->BUILD OPTIONS->LINKER中
MAP FILENAME -m
lcd/debug/lcd.map
3.进行编译:
4.编译后在产生了两个文件,一个是.MAP,一个.OUT.
5用记事本编写一个.cmd文件.-1. Will be produced by the BOOT program, prior to the compilation of its interrupt vectors mapped to the 3F80, register PMST the value of the home as 3FA0. 2. In CCS, compile the program, plus-v548 option, as shown below : Open the PROJECT-> BUILD OPTIONS-> COMPILER-g-as-fr " D: \ myprojects \ dspii_g \ vc5402 \ lcd" -v548 Meanwhile, in PROJECT-> BUILD OPTIONS-> LINKER in MAP FILENAME-m lcd/debug/lcd.map 3. compile: 4. compiled in the production of two documents, one is. MAP, 1. OUT. 5 using Notepad to write a. cmd file.
Platform: |
Size: 60416 |
Author: 朱坤 |
Hits:
Description: 分别采用维纳滤波和l-d算法设计一个6阶前向线性预测器,给出设计过程,matlab程序。
要求:1、得到预测器的权向量和预测误差功率
2、画出预测阶数和预测误差功率的曲线
3、在使用l-d算法时,假设 , ,…… 未知
-Wiener filter and were used to design a 6-ld algorithm prior to the linear predictor order, given the design process, matlab program. Requirements: 1, are predictors of weight vectors and the prediction error power of 2, draw the prediction order and the prediction error power, Curve 3, in the use ld algorithms, assumptions, ... ... unknown
Platform: |
Size: 1024 |
Author: xiaosa |
Hits:
Description: Clustering is the unsupervised classification of patterns (observations, data items,
or feature vectors) into groups (clusters). The clustering problem has been
addressed in many contexts and by researchers in many disciplines this reflects its
broad appeal and usefulness as one of the steps in exploratory data analysis.
However, clustering is a difficult problem combinatorially, and differences in
assumptions and contexts in different communities has made the transfer of useful
generic concepts and methodologies slow to occur. This paper presents an overview
of pattern clustering methods from a statistical pattern recognition perspective,
with a goal of providing useful advice and references to fundamental concepts
accessible to the broad community of clustering practitioners.-Clustering is the unsupervised classification of patterns (observations, data items,
or feature vectors) into groups (clusters). The clustering problem has been
addressed in many contexts and by researchers in many disciplines this reflects its
broad appeal and usefulness as one of the steps in exploratory data analysis.
However, clustering is a difficult problem combinatorially, and differences in
assumptions and contexts in different communities has made the transfer of useful
generic concepts and methodologies slow to occur. This paper presents an overview
of pattern clustering methods from a statistical pattern recognition perspective,
with a goal of providing useful advice and references to fundamental concepts
accessible to the broad community of clustering practitioners.
Platform: |
Size: 1154048 |
Author: nadjia |
Hits:
Description: 1.解压缩之后,在vs2008下可直接运行,不过需要安装opencv
2.提供人脸检测与识别功能
3.人脸识别,需要预先选定文件夹提取特征向量,然后才可以选取比较,这个需要改源程序-1. Unzipped, run directly under the vs2008, but need to install opencv 2. Provides face detection and recognition 3. Recognition, pre-selected folder need to extract the feature vectors before they can select a comparison, this need change the source code
Platform: |
Size: 13505536 |
Author: 文石磊 |
Hits:
Description: 1 SIFT 发展历程
SIFT算法由D.G.Lowe 1999年提出,2004年完善总结。后来Y.Ke将其描述子部分用PCA代替直方图的方式,对其进行改进。
2 SIFT 主要思想
SIFT算法是一种提取局部特征的算法,在尺度空间寻找极值点,提取位置,尺度,旋转不变量。
3 SIFT算法的主要特点:
a) SIFT特征是图像的局部特征,其对旋转、尺度缩放、亮度变化保持不变性,对视角变化、仿射变换、噪声也保持一定程度的稳定性。
b) 独特性(Distinctiveness)好,信息量丰富,适用于在海量特征数据库中进行快速、准确的匹配[23]。
c) 多量性,即使少数的几个物体也可以产生大量SIFT特征向量。
d) 高速性,经优化的SIFT匹配算法甚至可以达到实时的要求。
e) 可扩展性,可以很方便的与其他形式的特征向量进行联合。
4 SIFT算法步骤:
1) 检测尺度空间极值点
2) 精确定位极值点
3) 为每个关键点指定方向参数
4) 关键点描述子的生成
本包内容为sift算法matlab源码-1 SIFT course of development
SIFT algorithm by DGLowe in 1999, the perfect summary of 2004. Later Y.Ke its description of the sub-part of the histogram with PCA instead of its improvement.
2 the SIFT main idea
The SIFT algorithm is an algorithm to extract local features in scale space to find the extreme point of the extraction location, scale, rotation invariant.
3 the main features of the SIFT algorithm:
a) SIFT feature is the local characteristics of the image, zoom, rotate, scale, brightness change to maintain invariance, the perspective changes, affine transformation, the noise also maintain a certain degree of stability.
b) unique (Distinctiveness), informative, and mass characteristics database for fast, accurate matching [23].
c) large amounts, even if a handful of objects can also produce a large number of SIFT feature vectors.
d) high-speed and optimized SIFT matching algorithm can even achieve real-time requirements.
e) The scalability can be very convenient fe
Platform: |
Size: 2831360 |
Author: 李青彦 |
Hits:
Description: 为提高基于内容的图像检索系统中纹理特征提取的有效性,提出了又一种纹理图像检索方法。该方法
利用非下采样 Contourlet变换对图像进行分解, 提取不同子带和不同方向变换系数矩阵的均值和方差为特征向量, 作
为数据库中纹理图像的索引,并利用两种不同的相似度函数计算图像之间的相似度,建立了一套基于示例查询图像
的纹理图像检索系统。实验结果表明,与小波包等特征提取方法相比, 该方法不仅能降低特征向量维数,而且能取得
更高的检索准确率和检索速度。-To i ncrease t he vali d ity o f tex t ure feature ex tracti on in conten t-based i mage retrieva l syste m, a nove l approach
for tex ture i m age retr ieva lw as proposed . Th i s approach w as based on theNonSubsamp l ed Con t our l et T ransform ( NSCT). The
m eans and variab l es of NSCT co efficien tsm a trix i n d ifferen t s ubbands and var i ous directi ons were ex tracted to for m the feature
vectors wh ich we re reg arded as i ndexes of tex t ure i mages i n i m age da tabase . Two s i m il ar ity functi ons were used to compute the
si m ilar i ty bet w een i m ages . A tex ture re trieval sy stem based on query i m age w as deve l oped . Co m pared to the w ave let packag e
transform, th i s approach can no t on l y reduce the di m ension o f feature vectors , but a l so get higher accu racy and speed of
retr i eva. l
Platform: |
Size: 346112 |
Author: jjdjjf |
Hits:
Description: 滤波程序,从同事那里要的,大家一起交流学习-BADNELL & BURGESS D.A.M.T.P. CAMBRIDGE
C
C DIAGONALIZATION OF REAL SYMMETRIC N-BY-N MATRIX Z.
C
C METHOD: HOUSEHOLDER REDUCTION TO TRI-DIAGONAL FORM AND SHIFTED
C QL ALGORITHM TO DETERMINE THE E-VALUES AND E-VECTORS.
C
C BASED ON MARTIN, REINSCH & WILKINSON: NUM. MATH. 11, 181-95 (1968).
C
C INPUT REQUIRED. N, IUP AND Z. ONLY LOWER TRIANGLE OF Z NEED BE SUPPLIED.
C MATRIX Z OVERWRITTEN BY EIGENVECTORS OF Z.
C IUP=1/-1 ASC/DESCENDING SORT, 0 NO SORT.
C MXMAT, IS THE ROW DIMENSION OF Z IN THE CALLING ROUTINE.
C
C OUTPUT. Z AND D, WHERE Z CONSISTS OF COLUMN EIGENVECTORS
C AND D CONSISTS OF CORRESPONDING EIGENVALUES.
C
C NOTE: E IS A WORKING ARRAY.
C
Platform: |
Size: 2048 |
Author: 李鹏飞 |
Hits:
Description: lusolvec.f Numerical solution of a set of linear
C *** Equations / a matrix equation A * x = b
C *** using LU decomposition, matrix A and
C *** vectors b and x being double complex,
C *** and inversion of A.-3-D FDTD code with PEC bounlusolvec.f Numerical solution of a set of linear
C*** Equations/a matrix equation A* x = b
C*** using LU decomposition, matrix A and
C*** vectors b and x being double complex,
C*** and inversion of A.daries
Platform: |
Size: 2048 |
Author: 林夕言 |
Hits:
Description: Function to perform Principle Component Analysis over a set of training
vectors passed as a concatenated matrix.
Usage:- [V,D,M] = pca(X,n)
[V,D] = pca(X,aM,n)
where:-
<input>
X = concatenated set of column vectors
aM = assume that the mean is aM
n = number of principal components to extract (optional)
<output>
V = ensemble of column eigen-vectors
D = vector of eigen-values
M = mean of X (optional)
- Function to perform Principle Component Analysis over a set of training
vectors passed as a concatenated matrix.
Usage:- [V,D,M] = pca(X,n)
[V,D] = pca(X,aM,n)
where:-
<input>
X = concatenated set of column vectors
aM = assume that the mean is aM
n = number of principal components to extract (optional)
<output>
V = ensemble of column eigen-vectors
D = vector of eigen-values
M = mean of X (optional)
Platform: |
Size: 1024 |
Author: Praveen |
Hits: