- Played around with Scilab, used scilab for some simple signal processing work, Amplitude Modulation.
- I've started reading a paper on VM entitled Making LRU friendly to weak locality workloads
- Added Markov chains to my to-learn list
Tuesday, February 27, 2007
Balbir's log - 27 Feb 2007
Saturday, February 24, 2007
Using maxima -- baby steps
The use of symbolic computing makes it easy to visualize and solve problems that were otherwise dry and would put you to sleep. To test the simplicity of a freely available tool called maxima, I tried to solve a common problem with it.
The problem is quite simple, remember high school physics? Well I don't :-). Consider a tuning fork, which oscillates and produces a sound (depending on it's frequency).
We start by entering the mathematical model of the fork
'm*diff(x(t), t, 2)=-k*x(t);
Maxima prints
We now request maxima to solve the equation for us by
desolve([%],[x(t)]);
Maxima asks
Is k * m positive, negative, or zero? We say positive
Maxima prints
We ask maxima to simplify the result for us
radcan(%);
Maxima outputs
That's it, we have our solution.
The problem is quite simple, remember high school physics? Well I don't :-). Consider a tuning fork, which oscillates and produces a sound (depending on it's frequency).
We start by entering the mathematical model of the fork
'm*diff(x(t), t, 2)=-k*x(t);
Maxima prints
We now request maxima to solve the equation for us by
desolve([%],[x(t)]);
Maxima asks
Is k * m positive, negative, or zero? We say positive
Maxima prints
We ask maxima to simplify the result for us
radcan(%);
Maxima outputs
That's it, we have our solution.
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