21 February 2010
This paper describes a software package for processing biological signals that has been designed to overcome this by assisting and promoting the sharing of laboratory-developed software. The package, called sigTOOL, has two components: [1] a software development environment designed to facilitate further programming by the end-user and [2] an application implemented through that environment to [...]
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AMA citation:
Jiang W. sigTOOL: A MATLAB Toolbox for Biological Signals Analysis. Stone Studio. 2010. Available at: http://wei-jiang.com/programming/matlab/sigtool-a-matlab-toolbox-for-biological-signals-analysis. Accessed July 31, 2010.
APA citation:
Jiang, Wei. (2010). sigTOOL: A MATLAB Toolbox for Biological Signals Analysis. Retrieved July 31, 2010, from Stone Studio Web site, http://wei-jiang.com/programming/matlab/sigtool-a-matlab-toolbox-for-biological-signals-analysis
Chicago citation:
Jiang, Wei, "sigTOOL: A MATLAB Toolbox for Biological Signals Analysis", Stone Studio, posted February 21, 2010, http://wei-jiang.com/programming/matlab/sigtool-a-matlab-toolbox-for-biological-signals-analysis (accessed July 31, 2010).
Harvard citation:
Jiang, W 2010, sigTOOL: A MATLAB Toolbox for Biological Signals Analysis, Stone Studio. Retrieved July 31, 2010, from <http://wei-jiang.com/programming/matlab/sigtool-a-matlab-toolbox-for-biological-signals-analysis>
MLA citation:
Jiang, Wei. "sigTOOL: A MATLAB Toolbox for Biological Signals Analysis." Stone Studio. 21 Feb. 2010. 31 Jul. 2010 <http://wei-jiang.com/programming/matlab/sigtool-a-matlab-toolbox-for-biological-signals-analysis>
Thank you for your interest.
21 February 2010
The integration of spatial and non-spatial analysis software aims at providing a combination of the most efficient and powerful tools available in both environments (Brenning, 2008). There are various examples where this has been accomplished using access links between different software packages. JGrass, for example, provides integration of the statistic R package into the scripting [...]
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AMA citation:
Jiang W. TopoToolbox: a set of Matlab functions for topographic analysis. Stone Studio. 2010. Available at: http://wei-jiang.com/programming/matlab/topotoolbox-a-set-of-matlab-functions-for-topographic-analysis. Accessed July 31, 2010.
APA citation:
Jiang, Wei. (2010). TopoToolbox: a set of Matlab functions for topographic analysis. Retrieved July 31, 2010, from Stone Studio Web site, http://wei-jiang.com/programming/matlab/topotoolbox-a-set-of-matlab-functions-for-topographic-analysis
Chicago citation:
Jiang, Wei, "TopoToolbox: a set of Matlab functions for topographic analysis", Stone Studio, posted February 21, 2010, http://wei-jiang.com/programming/matlab/topotoolbox-a-set-of-matlab-functions-for-topographic-analysis (accessed July 31, 2010).
Harvard citation:
Jiang, W 2010, TopoToolbox: a set of Matlab functions for topographic analysis, Stone Studio. Retrieved July 31, 2010, from <http://wei-jiang.com/programming/matlab/topotoolbox-a-set-of-matlab-functions-for-topographic-analysis>
MLA citation:
Jiang, Wei. "TopoToolbox: a set of Matlab functions for topographic analysis." Stone Studio. 21 Feb. 2010. 31 Jul. 2010 <http://wei-jiang.com/programming/matlab/topotoolbox-a-set-of-matlab-functions-for-topographic-analysis>
Thank you for your interest.
21 February 2010
FieldTrip is a Matlab software toolbox for MEG and EEG analysis that is being developed at the Donders Institute for Brain, Cognition and Behaviour at the Radboud University Nijmegen, the Netherlands.
The FieldTrip toolbox includes algorithms for simple and advanced analysis of MEG and EEG data, such as time-frequency analysis, source reconstruction using dipoles, [...]
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AMA citation:
Jiang W. FieldTrip – the MATLAB toolbox for EEG/MEG analysis. Stone Studio. 2010. Available at: http://wei-jiang.com/programming/matlab/fieldtrip-the-matlab-toolbox-for-eegmeg-analysis. Accessed July 31, 2010.
APA citation:
Jiang, Wei. (2010). FieldTrip – the MATLAB toolbox for EEG/MEG analysis. Retrieved July 31, 2010, from Stone Studio Web site, http://wei-jiang.com/programming/matlab/fieldtrip-the-matlab-toolbox-for-eegmeg-analysis
Chicago citation:
Jiang, Wei, "FieldTrip – the MATLAB toolbox for EEG/MEG analysis", Stone Studio, posted February 21, 2010, http://wei-jiang.com/programming/matlab/fieldtrip-the-matlab-toolbox-for-eegmeg-analysis (accessed July 31, 2010).
Harvard citation:
Jiang, W 2010, FieldTrip – the MATLAB toolbox for EEG/MEG analysis, Stone Studio. Retrieved July 31, 2010, from <http://wei-jiang.com/programming/matlab/fieldtrip-the-matlab-toolbox-for-eegmeg-analysis>
MLA citation:
Jiang, Wei. "FieldTrip – the MATLAB toolbox for EEG/MEG analysis." Stone Studio. 21 Feb. 2010. 31 Jul. 2010 <http://wei-jiang.com/programming/matlab/fieldtrip-the-matlab-toolbox-for-eegmeg-analysis>
Thank you for your interest.
20 February 2010
EigTool is a free MATLAB package for computing pseudospectra of dense and sparse matrices. It also provides a graphical interface to MATLAB’s built-in eigs routine (ARPACK) for large-scale eigenvalue computations. EigTool was developed from 1999 – 2002 by Thomas G. Wright at the Oxford University Computing Laboratory, under the direction of Nick Trefethen. The software [...]
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AMA citation:
Jiang W. EigTool: Matlab Package for Computing Pseudospectra of Dense and Sparse Matrices. Stone Studio. 2010. Available at: http://wei-jiang.com/programming/matlab/eigtool-matlab-package-for-computing-pseudospectra-of-dense-and-sparse-matrices. Accessed July 31, 2010.
APA citation:
Jiang, Wei. (2010). EigTool: Matlab Package for Computing Pseudospectra of Dense and Sparse Matrices. Retrieved July 31, 2010, from Stone Studio Web site, http://wei-jiang.com/programming/matlab/eigtool-matlab-package-for-computing-pseudospectra-of-dense-and-sparse-matrices
Chicago citation:
Jiang, Wei, "EigTool: Matlab Package for Computing Pseudospectra of Dense and Sparse Matrices", Stone Studio, posted February 20, 2010, http://wei-jiang.com/programming/matlab/eigtool-matlab-package-for-computing-pseudospectra-of-dense-and-sparse-matrices (accessed July 31, 2010).
Harvard citation:
Jiang, W 2010, EigTool: Matlab Package for Computing Pseudospectra of Dense and Sparse Matrices, Stone Studio. Retrieved July 31, 2010, from <http://wei-jiang.com/programming/matlab/eigtool-matlab-package-for-computing-pseudospectra-of-dense-and-sparse-matrices>
MLA citation:
Jiang, Wei. "EigTool: Matlab Package for Computing Pseudospectra of Dense and Sparse Matrices." Stone Studio. 20 Feb. 2010. 31 Jul. 2010 <http://wei-jiang.com/programming/matlab/eigtool-matlab-package-for-computing-pseudospectra-of-dense-and-sparse-matrices>
Thank you for your interest.
20 February 2010
The aim of the chebfun system is to “feel symbolic but run at the speed of numerics”. More precisely our vision is to achieve for functions what floating-point arithmetic achieves for numbers: rapid computation in which each successive operation is carried out exactly apart from a rounding error that is very small in relative terms [...]
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AMA citation:
Jiang W. ChebFun: Matlab Toolbox Numerical computation. Stone Studio. 2010. Available at: http://wei-jiang.com/programming/matlab/chebfun-matlab-toolbox-numerical-computation. Accessed July 31, 2010.
APA citation:
Jiang, Wei. (2010). ChebFun: Matlab Toolbox Numerical computation. Retrieved July 31, 2010, from Stone Studio Web site, http://wei-jiang.com/programming/matlab/chebfun-matlab-toolbox-numerical-computation
Chicago citation:
Jiang, Wei, "ChebFun: Matlab Toolbox Numerical computation", Stone Studio, posted February 20, 2010, http://wei-jiang.com/programming/matlab/chebfun-matlab-toolbox-numerical-computation (accessed July 31, 2010).
Harvard citation:
Jiang, W 2010, ChebFun: Matlab Toolbox Numerical computation, Stone Studio. Retrieved July 31, 2010, from <http://wei-jiang.com/programming/matlab/chebfun-matlab-toolbox-numerical-computation>
MLA citation:
Jiang, Wei. "ChebFun: Matlab Toolbox Numerical computation." Stone Studio. 20 Feb. 2010. 31 Jul. 2010 <http://wei-jiang.com/programming/matlab/chebfun-matlab-toolbox-numerical-computation>
Thank you for your interest.
28 January 2010
cloudPlot will help visualize the distribution of a 2-dimensional dataset. It is especially helpful when looking at extremely large datasets where a redular plot(x,y,’.’) will just fill the plot with a solid color because the measurement points overlap each other. cloudPlot uses the built-in matlab routines to set the axis limits and grid points appropriate [...]
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AMA citation:
Jiang W. cloudPlot – Matlab function to plot the distribution of 2-dimensional data.. Stone Studio. 2010. Available at: http://wei-jiang.com/programming/matlab/cloudplot-matlab-function-to-plot-the-distribution-of-2-dimensional-data. Accessed July 31, 2010.
APA citation:
Jiang, Wei. (2010). cloudPlot – Matlab function to plot the distribution of 2-dimensional data.. Retrieved July 31, 2010, from Stone Studio Web site, http://wei-jiang.com/programming/matlab/cloudplot-matlab-function-to-plot-the-distribution-of-2-dimensional-data
Chicago citation:
Jiang, Wei, "cloudPlot – Matlab function to plot the distribution of 2-dimensional data.", Stone Studio, posted January 28, 2010, http://wei-jiang.com/programming/matlab/cloudplot-matlab-function-to-plot-the-distribution-of-2-dimensional-data (accessed July 31, 2010).
Harvard citation:
Jiang, W 2010, cloudPlot – Matlab function to plot the distribution of 2-dimensional data., Stone Studio. Retrieved July 31, 2010, from <http://wei-jiang.com/programming/matlab/cloudplot-matlab-function-to-plot-the-distribution-of-2-dimensional-data>
MLA citation:
Jiang, Wei. "cloudPlot – Matlab function to plot the distribution of 2-dimensional data.." Stone Studio. 28 Jan. 2010. 31 Jul. 2010 <http://wei-jiang.com/programming/matlab/cloudplot-matlab-function-to-plot-the-distribution-of-2-dimensional-data>
Thank you for your interest.
27 January 2010
RANSAC is an abbreviation for "RANdom SAmple Consensus". It is an iterative method to estimate parameters of a mathematical model from a set of observed data which contains outliers. It is a non-deterministic algorithm in the sense that it produces a reasonable result only with a certain probability, with this probability increasing as more iterations [...]
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AMA citation:
Jiang W. Matlab RANdom SAmple Consensus (RANSAC) Toolbox. Stone Studio. 2010. Available at: http://wei-jiang.com/programming/matlab/matlab-random-sample-consensus-ransac-toolbox. Accessed July 31, 2010.
APA citation:
Jiang, Wei. (2010). Matlab RANdom SAmple Consensus (RANSAC) Toolbox. Retrieved July 31, 2010, from Stone Studio Web site, http://wei-jiang.com/programming/matlab/matlab-random-sample-consensus-ransac-toolbox
Chicago citation:
Jiang, Wei, "Matlab RANdom SAmple Consensus (RANSAC) Toolbox", Stone Studio, posted January 27, 2010, http://wei-jiang.com/programming/matlab/matlab-random-sample-consensus-ransac-toolbox (accessed July 31, 2010).
Harvard citation:
Jiang, W 2010, Matlab RANdom SAmple Consensus (RANSAC) Toolbox, Stone Studio. Retrieved July 31, 2010, from <http://wei-jiang.com/programming/matlab/matlab-random-sample-consensus-ransac-toolbox>
MLA citation:
Jiang, Wei. "Matlab RANdom SAmple Consensus (RANSAC) Toolbox." Stone Studio. 27 Jan. 2010. 31 Jul. 2010 <http://wei-jiang.com/programming/matlab/matlab-random-sample-consensus-ransac-toolbox>
Thank you for your interest.
27 January 2010
Microarray technology allows gene expression profiling at a global level by measuring mRNA abundance. ARMADA (Automated Robust MicroArray Data Analysis) is a MATLAB implemented program with a graphical user interface (GUI) which performs all steps of typical microarray data analysis; starting from importing raw data from several image analysis software outputs as well as text [...]
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AMA citation:
Jiang W. Automated Robust MicroArray Data Analysis in MATLAB (Toolbox). Stone Studio. 2010. Available at: http://wei-jiang.com/programming/matlab/automated-robust-microarray-data-analysis-in-matlab-toolbox. Accessed July 31, 2010.
APA citation:
Jiang, Wei. (2010). Automated Robust MicroArray Data Analysis in MATLAB (Toolbox). Retrieved July 31, 2010, from Stone Studio Web site, http://wei-jiang.com/programming/matlab/automated-robust-microarray-data-analysis-in-matlab-toolbox
Chicago citation:
Jiang, Wei, "Automated Robust MicroArray Data Analysis in MATLAB (Toolbox)", Stone Studio, posted January 27, 2010, http://wei-jiang.com/programming/matlab/automated-robust-microarray-data-analysis-in-matlab-toolbox (accessed July 31, 2010).
Harvard citation:
Jiang, W 2010, Automated Robust MicroArray Data Analysis in MATLAB (Toolbox), Stone Studio. Retrieved July 31, 2010, from <http://wei-jiang.com/programming/matlab/automated-robust-microarray-data-analysis-in-matlab-toolbox>
MLA citation:
Jiang, Wei. "Automated Robust MicroArray Data Analysis in MATLAB (Toolbox)." Stone Studio. 27 Jan. 2010. 31 Jul. 2010 <http://wei-jiang.com/programming/matlab/automated-robust-microarray-data-analysis-in-matlab-toolbox>
Thank you for your interest.