Useful links for DTI processing
DICOM headers DICOM is usually the data format downloaded form the scanner or the PACS system. (PACS system is an archiving system widely used in hospitals t...
Posts by Category
- Tools 7
- Machine Learning 7
- Coding 6
- Machine learning 5
- Signal processing 5
- Neuroscience 4
- Image processing 1
- Papers 1
Tools
Notes to use TVB software
Install directly from github Update 2019/09/06. Version 2.0 is compatible for python3. But some API is different. If use pip install tvb-library, version 1.5...
Coordinate Transform between Brainstorm, Freesurfer and Curry8
Brainstorm & freesurfer Requirement: The Brainstorm MRI is the T1.mgz generated by the freesurfer OR Export the MRI image from Brainstorm and direct...
Useful sublime text markdown interpretation tool
Use Alt+m to open up the interpreter Install instructions: https://math2001.github.io/MarkdownLivePreview/
Notes on changing the minimal mistakes
I wrote some notes on how to customize your website. Change the sidebar width: If you want to change the image size: goes to _sass and change i...
Notes on changing the academicpages
Other than the notes for changing _config.yml and _pages folder that are already on the academicpages website, here I write down some notes to further custom...
Tricks while Using Matlab
Using Matlab in Jupyter Notebook Jupyter notebook can combine text and code. When you are study new things and take notes, it could be really helpful. The st...
Machine Learning
Theoritical and Empirical studies on generalization in Deep learning
Theory: Bound the generalization error Introduction Probably approximately correct (PAC) learning (Valient, 1984) provided a theoretical framework to provide...
SVD and PCA
The notes from cmu 17spring-18898:
Neural Networks
(Many are copied from Sun, 2019 Optimization paper)
Some basic concepts in CMU 10601
Naive Bayes A linear classifier Generative model: model \(p(X,y)\)
Expectation maximization
We have observed variable \(x\), latent varivable \(z\) and parameters \(\theta\). The complete log likelihood should be \(l(\theta;x,z) = \log p(x,z | \the...
Some less popular concepts in CMU 10601
Semi-supervised learning: mixing labeled and unlabeled data as training data (no query for labels during training); based on the belief that data has the ...
Clustering
Clustering is aimed at grouping set of objects that have similar “properities”. There are many different ways to define the distance for clustering. The famo...
Coding
Pycharm ignore PEP8 errors
Taken from https://gist.github.com/StefanoMagrassi/6c78b6f48599377a5c805fd58a5cd93d
Verify the convoliution theorem using Matlab
When using Matlab to verify “Convolution in time domain is multification in frequency domain”, simply doing fft2 is wrong.
Useful sublime text markdown interpretation tool
Use Alt+m to open up the interpreter Install instructions: https://math2001.github.io/MarkdownLivePreview/
Notes on changing the minimal mistakes
I wrote some notes on how to customize your website. Change the sidebar width: If you want to change the image size: goes to _sass and change i...
Rollback to previous commits
Taken from https://gist.github.com/StefanoMagrassi/6c78b6f48599377a5c805fd58a5cd93d
Notes on changing the academicpages
Other than the notes for changing _config.yml and _pages folder that are already on the academicpages website, here I write down some notes to further custom...
Machine learning
Image data preprocessing for neural networks
We treat each pixel in the image as a variable. We want to make the mean and std of each pixel similar cross all training samples (cross the samples in a ...
Statistical testing concepts
Statistical power From the The_Essential_Guide_to_Effect_Size Defined as the probability that it will reject a false null hypothesis Inversely related...
Approximate Inference
(Summarized from the lecture notes from cmu spring17-10708, Eric Xing)
Compare GPUs
Comparsion of GPU performance online from Timdettmers
Reading summary for The Brain vs Deep Learning – from Tim Dettmer
Original post: http://timdettmers.com/2015/07/27/brain-vs-deep-learning-singularity/
Signal processing
Verify the convoliution theorem using Matlab
When using Matlab to verify “Convolution in time domain is multification in frequency domain”, simply doing fft2 is wrong.
Multitaper
The content below is a translation and summary of the wiki page of Multitaper.
Wavelet Transform
We know that wavelet transform comes from STFT by changing a single windowing function to a set of windowing functions. \(X(t,\omega) = \int_{-\infty}^{\i...
Short Time Fourier Transform
Why use STFT? We wants to know the frequency components at each time point. Solution: we perform FFT on small blocks. \(X(t,\omega) = \int_{-\infty}^{\...
Discrete consine transform(DCT-II)
Why use DCT DTFS/FFT (We will not detail into the difference between these two at this moment.) use $e^{jwt}$ as the base. And if $x(t)$ is real and even,...
Neuroscience
Useful links for DTI processing
DICOM headers DICOM is usually the data format downloaded form the scanner or the PACS system. (PACS system is an archiving system widely used in hospitals t...
EEG source localization
1. Physiology Source of EEG The first a few pages of “François Grimbert, Olivier Faugeras. Analysis of Jansen’s model of a single cortical column. Researc...
Nelder-Mead method/Downhill simplex method
This method is a traditional method for non-linear optimization problem. A simplex is a structure in n-dimensional space formed by n+1 points that are n...
Reading summary for The Brain vs Deep Learning – from Tim Dettmer
Original post: http://timdettmers.com/2015/07/27/brain-vs-deep-learning-singularity/
Image processing
Some concepts in image processing
Ringing artifacts
Papers
Papers I browsed
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