Speaking from experience after 2 years into PhD program, I can surely say graduate studies may be tiring sometimes. Along the way, there are many moments where you say – “that’s it”. Sticking to what you are doing is most important. Love your work. It does not need for one to be genius to complete graduate studies. Getting focused is the key idea. One should be proactive, keeping in touch with his/her adviser. I did do some blunders during start.
One of the way to keep your spirit high is to read other grad student’s experience. I do that all the time. At least, I know there are other people out there having same situation as mine. Let me share some of the links I feel are good.
I have used Latex from last 1 year. Initially, I used Lyx with MikTex 2.8. Then, I switched to Tex-Maker. For beginner, it is easy to use. Finally I installed Texnic Center, which I did not like much. Now, I am using WinEdt 6.0 and it has been fun.
One more info, this tool to convert pictures to eps looks cool. Try it. I love it!
Unlike feed-forward and feedback network, which does supervised learning, Self organizing maps(SOM) have unsupervised and competitive learning strategy. Supervised learning algorithms such as back propagation algorithm have input vectors and target vectors. We adjust the weights of the neural network till the output vector is same or almost equivalent to the target vector. This means the learning process is supervised from outside. But, on self organizing maps, we employ unsupervised learning strategy. No target vector is required. It employs “winner-take-all” approach. First proposed by Prof. T. Kohonen, it is widely used in wide applications such as image processing, data clustering and visualization, medical image analaysis etc.
I have written a summary report about SOM. Anyone interested can read it from here. I had done coding for clustering of colors. If you need code for illustration of SOM, please let me know.
New blog. I hope I will get time to update it frequently.