我是 季育澤 (Yu-Tseh Jason Chi)!! 我把這個部落格當成我自己的小小記事本. 如果有老朋友孤狗到這的話, 請來信告知我一下. 我的email是 firstname.lastname@example.org
你的blog很熱耶. see the map!
剛剛看了一下blog的stat, 系統已經自動擋掉幾百個spam comments了.
Pls sir i want to know about the som matlab code for my reasearh work.
I am the maintainer of the SmallBASIC project (http://smallbasic.sf.net). We currently have a bug with our matrix inversion function which I have so far been unable to solve.
Would it be okay to incorporate your C code for matrix inversion calculations into SmallBASIC? I currently have it integrated in my local dev environment and it seems to work perfectly.
If this is OK I will ensure you are given due credit.
Sure! Feel free to use my code. I want to remind you that this algorithm is very slow when the size of the matrix is large.
I am a PhD student at Monash University, Melbourne, Australia. I would like permission to use your matrix inversion code in C++ for my own diesel engine simulation programme.
If that is alright with you, how would you like it to be referenced?
Yes, you can use it. But keep in mind that the code is very slow for large matrix. There are other much faster algo to calculate matrix inversion. Google it. Good luck!
It is only a 4×4 matrix so speed isn’t very important.
Please let me know how you would like it referenced.
I would like to know is there any way to convert the matlab code to c code so that i can run the program in dsp processor?
sir i am Me student will you please give me matlab code for segmenting compressed video using markov model and global motion estimation.
hello sir i am studying SOM from past 2 months i read your SOM matlab code facinating but can you help me out with data selection for training which you have used 900 dimensional ?
I want to ask you a question….is there any way to simulate neural network with the weights provided by Supervised learning method like MLP and RBF…need your help in this regard, I am working on real time voice filteration..it is very easy with the supervised learning method and how can we achieve it with unsupervised learning
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