31 December, 2005

受傷的心

受傷的心 - 作詞:吳宗憲, 作曲:吳宗憲

受傷的心已經無閒 無閒聽你擱講分明
就欲離開的行李內 找無你我的將來
男人的心嘛真堅定 擱再講感覺無著你的愛情
這張無留住址的批 代表阮永遠無後悔

啊... 傷心傷心的話 請你放置你的心肝底
無論天涯 亦是海角 阮永遠欲走乎你找
啊... 愛情愛情是假 何必聲聲句句欲挽回
若是日頭從西邊出來 阮還是決定欲走乎你找

12 December, 2005

Toward Freedom

Some days ago, I decided to get rid of Matlab because

  1. It is heavy. It takes at least 3 seconds to start itself and usually the programs are running slowly compared to the programs written in Python.
  2. It is propritary. Although many people in the control field use Matlab to do simulations, I don't agree with that. Why not use open source software instead? For operations with matrices and transfer functions, I highly recommand Scilab. As for numerical calucations, I think any programming language will perform better than the Mablab programming language.

02 December, 2005

Convexity

Recently I enjoyed surfing homepages of famous people in the control field. At first, I don't even know those people have a homepage. I came across their homepages because I wanted to find an old paper whose electronical version was not available through school's library. So I used google to search the paper's information. And found some authors place pdf files of the papers in their homepage, which is a nice idea from my point of view. I also found there are many interesting things in their homepages, e.g. their lecture notes, old papers, books, biography... I especially like to see their lecture notes, because they are usually written in a compact way, only the main and important concepts are listed in the notes and tedious calculation are omitted. This helps me to quickly catch the most important idea that the authors want to convey. Today I read three different people's lecture notes:

  1. Stephen P. Boyd: Convex Optimization in Electrical Engineering.
  2. Carsten W. Scherer: LMI Relaxations in Robust Control.
  3. M. C. de Oliveira: Background material on convexity.

I found one thing in common: they all have the following quote

The greatest watershed in optimiztion is not between linearity and nonlinearity, but between convexity and nonconvexity - Rockafellar