On 01/04/2008, Jaroslav Hajek <[EMAIL PROTECTED]> wrote: > > Although I have come across the concept of kernel-based methods, I still > > do not understand exactly what that means. I am an engineer who dabbles > > in applied mathematics. I do not think the method I have implemented is > > kernel-based. It is sometimes known as "penalized least squares"[1]. > > The idea is to minimize a function that is the sum of a goodness of fit > > term and a data roughness term. I have implemented it for > > one-dimensional data only, and I have not yet seen a multi-dimensional > > implementation in the literature, although it may be possible. > > > > Yes, I know what you mean - Tikhonov regularization (also ridge > regression) sort-of corresponds to using "white noise" term in GPR. I > thought there is something already for ridge regression in > Octave-Forge, but I could not find anything.
There is a very extensive mathematical and engineering literature on this kind ofproblem. Look under "regularization" or "inverse problems" For medical imaging in soft field tomography, I maintain an open source software suite for these kinds of problems. EIDORS - www.eidors.org This may be helpful. -- Andy Adler <[EMAIL PROTECTED]> +1-613-520-2600x8785 ------------------------------------------------------------------------- Check out the new SourceForge.net Marketplace. It's the best place to buy or sell services for just about anything Open Source. http://ad.doubleclick.net/clk;164216239;13503038;w?http://sf.net/marketplace _______________________________________________ Octave-dev mailing list Octave-dev@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/octave-dev
