Yi Cao

Aeimit

Yes, it is possible. For example, see

http://www.mathworks.com/matlabcentral/fileexchange/18286

Yi

Hi Anoop Balan,

Thanks for commenting on the code. The algorithm is polynomial. This means the computation time will growth about n^p with n the size of the problem and p some constant depending on CPU speed, memory and software implementation. On my PC, Intel Core2 Quad CPU (Q9300) 2.5 GHz with 4 GB RAM, with XP and Matlab 2009b, I got the following results:

n = 1000, cpu time = 18 sec
n = 2000, cpu time = 150 sec
n = 4000, cpu time = 1216 sec

Another machin

n = 1000, cpu time = 128 sec
n = 2000, cpu time = 1024 sec

So roughly, p = 3 (2^3 = 8). I do not know why your machin has so large p (>5). When you solve a large size problem, make sure you start with a clean workspace to avoid any unnecessary overhead for swaping memory with hard disk.

Yi

Hi,
Is it possible to use the UFK when the non-linear function 'f' is unknown. But instead there is a 'map' (non deterministic) which is known. I want to filter the measurement signal using this non-deterministic 'map' which is only a set of samples and is seen periodically in the measurement signal.

Thanks.

Truly excellent. It has everything you could ask of a Matlab program: good structure, excellent comments, simplicity, flow and efficiency. Thank you for sharing.

Thanks... You might be right about the memory part. Although I was cleaning the workspace, I was using a MEX code which might have a memory leak (dont know if this is possible).

I ended up using the Jonker-Volgenant shortest augmenting path algorithm from 'http://boguslawobara.net/index.php?page=software.php'. This solves the same problem and appeared way faster.