嫁にTeXでブロック線図を書きたいと言われて、自分がいつもillustratorでブロック線図を描いていたことを思い出した。illustratorで書くので十分なのだが、問題はフォント。illustratorで書くとフォントがTeXのものと違ってしまう。たぶんそれを合わせる方法はあるんだろうが、もっと簡単なものはないかと調べていて発見！
http://www.texample.net/tikz/examples/tag/block-diagrams/
ところで、このサイトはなかなかすごい！これで何でもかけそうだ。
http://www.texample.net/
マニュアル：
http://media.texample.net/pgf/builds/pgfmanualCVS2009-04-24.pdf
問題は、xcolorがpost script specialで、dvioutで表示できないところ。現段階では、日本語環境ではtex→dvi→ps(→pdf)しか方法がなさそうだ。英文の文章を書いている場合には、pdflatexが最も便利そうだ。
よい方法があったら教えてください。
2009年4月29日水曜日
2009年4月4日土曜日
MATLABでImage based Pattern Recognition
SIFTの実装：
http://www.vlfeat.org/~vedaldi/code/sift.html
MSER:
http://www.vlfeat.org/~vedaldi/code/mser.html
Statistical Pattern Recognition Toolbox:
http://cmp.felk.cvut.cz/cmp/software/stprtool/index.html
下記のものが実装されているとのこと(上記HPより抜粋)
Linear discriminant function
* Perceptron and multi-class modification
* Epsilon-optimal separating hyperplane by Kozinec's algorithm
* Fisher Linear Discriminant
* Algorithms to solve the Generalized Anderson's task
Feature extraction
* Principal Component Analysis
* Kernel PCA
* Greedy Kernel PCA
* Linear Discriminant Analysis
* Generalized Discriminant Analysis
Density estimation and clustering
* Gaussian mixture models
* Expectation-Maximization algorithm for Gaussian mixture models
* Minimax estimation for Gaussian distribution
* Reduced Set Density Estimator
* Fitting sigmoid to classifier output
* K-means clustering
Support Vector Machines
* Sequential Minimal Optimizer
* SVM based on Matlab Optimization toolbox
* Matlab interface to SVM^{light}
* Solvers for multi-class BSVM formulation.
* Single-class SVM solvers
* Kernel Fisher Discriminant
* Kernel Perceptron
Others
* Bayes classifier, error estimation
* Cross-validation evaluation
* k-Nearest Neighbor rule
* Quadratic data mapping
Visualization
* Discriminant functions
* Probabilistic models
* SVM classifiers
* Images
Regression
Interface to XTAL regression package which implements:
* Projection pursuit regression (SMART)
* Multilayer perceptron
* Multivariate adaptive regression splines
* k-nearest neighbors and Constrained topological mapping
* Constrained topological mapping
http://www.vlfeat.org/~vedaldi/code/sift.html
MSER:
http://www.vlfeat.org/~vedaldi/code/mser.html
Statistical Pattern Recognition Toolbox:
http://cmp.felk.cvut.cz/cmp/software/stprtool/index.html
下記のものが実装されているとのこと(上記HPより抜粋)
Linear discriminant function
* Perceptron and multi-class modification
* Epsilon-optimal separating hyperplane by Kozinec's algorithm
* Fisher Linear Discriminant
* Algorithms to solve the Generalized Anderson's task
Feature extraction
* Principal Component Analysis
* Kernel PCA
* Greedy Kernel PCA
* Linear Discriminant Analysis
* Generalized Discriminant Analysis
Density estimation and clustering
* Gaussian mixture models
* Expectation-Maximization algorithm for Gaussian mixture models
* Minimax estimation for Gaussian distribution
* Reduced Set Density Estimator
* Fitting sigmoid to classifier output
* K-means clustering
Support Vector Machines
* Sequential Minimal Optimizer
* SVM based on Matlab Optimization toolbox
* Matlab interface to SVM^{light}
* Solvers for multi-class BSVM formulation.
* Single-class SVM solvers
* Kernel Fisher Discriminant
* Kernel Perceptron
Others
* Bayes classifier, error estimation
* Cross-validation evaluation
* k-Nearest Neighbor rule
* Quadratic data mapping
Visualization
* Discriminant functions
* Probabilistic models
* SVM classifiers
* Images
Regression
Interface to XTAL regression package which implements:
* Projection pursuit regression (SMART)
* Multilayer perceptron
* Multivariate adaptive regression splines
* k-nearest neighbors and Constrained topological mapping
* Constrained topological mapping
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