Cool examples given in Gilbert Strang's Introduction to Linear Algebra are

>From Section 6.2 -- The solution to u(k+1) = A uk starting from u0 is

uk = A^k  u0 = S Lambda^k  S^-1 u0 , so that

uk = c1 lambda1^k x1 + ... + cn lambdan^k xn  provided

u0 = c1 x1 + ... + cn xn   (xk is eigenvector corrresponding to eigenvalue 
lamdak)

Lambda is a diagonal matrix with the eigenvalues of A on the diagonal, and S is 
a
square matrix whose columns are the eigenvectors.  Strang illustrates with the
Fibonnaci sequence F0 F1 F2 ... , setting  uk = ( F(k+1) , Fk )  and u0 = (1 , 
0) .


>From Section 6.3 -- The solution to u' = A u starting from u(0) is

u(t) = c1 e^(lambda1 t) x1 + ... + cn e^(lambdan t) xn  provided

u(0) = c1 x1 + ... + cn xn .  The solution can be expressed as

u(t) = e^(A t) u(0)  with the matrix exponential e^(A t) .

Equations involving y'' reduce to u' = A u by combining y' and y into

u = (y' , y)


--Kip Murray

Sent from my iPad

> On Oct 3, 2013, at 6:10 AM, Raul Miller <[email protected]> wrote:
> 
> I was looking at those the other day and ran into a variety of difficulties.
> 
> I'll not bore you with the details, but I'll admit that I would love
> to see some pages devoted to example usages.
> 
> I'm not really looking for comprehensive, in-depth documentation -
> that's already available through web searching ... if I can understand
> what terms I need to use to search on. What I'm looking for are cool
> examples - things that probe the possibilities, bits of prose perhaps
> which hint at relevant search terms. Failed attempts might also be
> useful, as stepping stones for finding or writing more better or
> slightly beautiful expositions.
> 
> Thanks,
> 
> -- 
> Raul
> 
>> On Wed, Oct 2, 2013 at 12:27 PM, km <[email protected]> wrote:
>> Here is a resource that should be better known.  To use it you load
>> ~addons/math/mt/mt.ijs    --Kip Murray
>> 
>> 
>>>>> On Mon, Apr 8, 2013 at 3:17 AM, Kip Murray <[email protected]> wrote:
>>>> 
>>>> Igor Zhuravlof provides j routines that model LAPACK routines for
>>>> eigenvalues and eigenvectors.  See "matrix toolbox"
>>>> 
>>>> ~addons/math/mt
>>>> 
>>>> with contents summarized in
>>>> 
>>>> ~addons/math/mt/mt.ijs
>>>> 
>>>> I have not tried them but would expect them to run in j701JHS.
>> 
>> Sent from my iPad
>> 
>>> On Oct 2, 2013, at 9:21 AM, Raul Miller <[email protected]> wrote:
>>> 
>>> J's support for mechanisms to compute eigenvalues has been rather
>>> messy. And, by messy I mean that it looks like we rarely exercise
>>> these mechanisms - we don't have unit tests on the entry points to be
>>> run before uploading library updates, we don't have particularly good
>>> documentation on the code we have and there are other problems.
>>> 
>>> Here's an example I stumbled over today:
>>> 
>>>  docs_jlapack_''
>>> |value error: dirs
>>> |       dirs jpathsep path,'doc/*.lap'
>>>  require'dirs'
>>> not found: /Users/rdmiller/Applications/j64-801/bin/dirs
>>> |file name error: script
>>> |       0!:0 y[4!:55<'y'
>>>  require 'dir'
>>>  docs_jlapack_''
>>> |value error: dirs
>>> |       dirs jpathsep path,'doc/*.lap'
>>>  getscripts_j_ 'dir'
>>> 
>>> 
>>> So here's a question: does anyone have the time and energy to put into
>>> this mess?
>>> 
>>> Thanks,
>>> 
>>> --
>>> Raul
>>> ----------------------------------------------------------------------
>>> For information about J forums see http://www.jsoftware.com/forums.htm
>> ----------------------------------------------------------------------
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