eigen c tutorial

C ++ processing matrix operations: Preliminary use of Eigen DatabasePreface: Eigen is a library of linear arithmetic C ++ templates, including vectors, matrices, open source and Related algorithms. Powerful, fast, elegant, and supports multiple platforms. You can use this library to conveniently process matrix operations and achieve the same speed as matlab. It has now evolved to Eigen3, and the latest vers

I. SummaryThese two days to think up to do the work of neural network, requires the completion of C + + neural network algorithm.In front of the first problem is that the neural network algorithm used in a large number of matrix operations. However, C + + does not have a very good support for matrix operations like MATLAB. Originally prepared to write a C + + matrix operation of the code, Google a bit later. Found a few good C + + matrix operations Library, I chose to

*************************************** Reprint Please specify the Source: Http://blog.csdn.net/lttree ********************************************These days, has been busy to help the college a teacher to do a software function module,Module requirements are a series of operations on matrices,Originally was to write their own, later, found that there are ready-made tools, a lot, I finally chose the eigen,Because it is convenient AH ~ just need to put

http://blog.csdn.net/shuzfan/article/details/52367329 Recently has been doing engineering things, more than the use of the Eigen Matrix Computing Library. Briefly describe the characteristics of Eigen: (1) Easy to use, no need for precompilation, small call overhead (2) The function is rich, the style is somewhat approximate matlab, easy to start; (3) The speed is the same, faster than the OPENCV, than the

This week began to implement the grid watermark code, although nothing, but also can only step by step to explore the move forward.The title of my thesis is At first I was going to use eigen to decompose the eigenvalues of the Laplace matrix, so it involved the eigen configuration. Eigen is an open-source matrix operations Library, which encapsulates a large numb

Reference Blog: http://blog.csdn.net/u011092188/article/details/77430988 The representations of the various forms in the Eigen library are as follows:1: Rotation matrix (3x3): eigen::matrix3d--uses a matrix to represent the rotation transformation relationships in space2: Rotation vector (3X1): eigen::angleaxisd--with a rotating axis and a rotation angle to repre

I. OverviewThese two days to think up to do the work of the neural network, the need to complete the neural network algorithm in C + +.In front of the first problem is that the neural network algorithm used in a large number of matrix operations, but C + + is not like MATLAB, the matrix operations have a good support, originally prepared to write a C + + matrix operation of the code, Google a bit, and found a few good C + + matrix operations Library, I chose

Inverse matrix pseudoinverse of matrices with non-matricesPseudo-inverse matrices are generalized forms of inverse matrices, generalized inverse matricesMATLAB is PINV (a)-"inv (a)."#include"stdafx.h"#include#include#includeTemplate_matrix_type_ pseudoinverse (Const_matrix_type_ a,DoubleEpsilon =std::numeric_limitsDouble>:: Epsilon ()) {EIGEN::JACOBISVDEIGEN::COMPUTETHINV); Doubletolerance = Epsilon * Std::max (A.cols (), A.rows ()) *svd.singularvalue

Using Eigen to solve nonlinear least squares; Example: #include "iostream" #include "vector" #include "list" using namespace std; #include "eigen/dense" #include "eigen/core" #include Generic functor template struct my_functor:functor int main (int argc, char *argv[]) { eigen::vectorxd x (2); X (0) =

Using the Eigen library: SVD decomposition, shaped like A = U * S * VT.eigen::jacobisvd//EigenTest.cpp: Defines the entry point of the console application. //#include"stdafx.h"#include#include#include//using EIGEN::MATRIXXF; using namespaceEigen; using namespaceEigen::Internal; using namespaceeigen::architecture; intMain () {matrix3f A; A (0,0)=1A0,1)=0A0,2)=1; A (1,0)=0A1,1)=1A1,2)=1; A (2,0)=0A2,1)=0A2,2)

Eigen is a C + + Template library for linear arithmetic, including: vectors, matrices, and related algorithms. Powerful, fast, elegant, and multi-platform support.The type of matrix in Eigen is generally represented by a similar matrixxxx, which can be used to determine its data type, such as ' d ' for a double not to represent an integer; ' F ' stands for float; ' I ' stands for integers; ' C ' stands for

1. Eigen is a C + + Template library for linear algebra:matrices, vectors, numerical solvers, and related algorithms. http://eigen.tuxfamily.org/supports integers, floating-point numbers, and complex numbers, and can provide matrix operations for special data structures using template programming. For example, when using Ceres-solver to do optimization problems (such as bundle adjustment), sometimes you need to use template programming to write a targ

Compared with other matrix libraries, the Eigen only needs to copy all of the include files to the specified location, without compiling and using the Eigen (Visit), in addition, the use of MATLAB matrix operation is simulated;The above characteristics, so that it has a good practicality.Attach the test code for learning and use.Http://eigen.tuxfamily.org/dox/group__QuickRefPage.html#include Operation Resul

The first thing to say is that the toolkit is very handy and can be extracted. Add the path to this folder in the project.Here are some code exercises:#include The following transpose is used:#include The following example removes a sub-matrix from a matrix (note that the two methods are the same.)The paper that was reproduced is wrong here.。 ）#include Here are some operations of the vector:#include Come down and look at the basic assignment situation:#include Here's how to assign the following

The "The number of rows, columns, and sizes of the current matrix can be obtained by rows (), cols () and size (), and the size of the matrix can be dynamically modified by the resize () function for the dynamic matrix.be aware that:(1) a fixed-size matrix cannot use resize () to modify the size of the matrix; (2) The resize () function will deconstruct the original data, so calling the resize () function does not guarantee that the value of the element will not change. (3) when using the "="

VS2013 PCL1.7.2 uses a eigen library #include Results Sample2: (for reference only) #include

The rotation of the three-dimensional space can be represented by Euler's angle, rotation vector, rotation matrix, and four-dollar number.The first is the Euler angle notation, which we can use to rotate around an axis.A rotational vector is a rotating axis and a rotational angle to represent rotation.The rotation matrix uses a matrix to represent the rotational transformation relationships in the space.The four-dollar number uses 4 variables to denote rotation (adding a latitude) to avoid the p