in internet or maple, is there a neural network package in maple?

i find example link after googled, however, still feeling not easy to apply to data.

is there the most simplest version for two columns of data ?

which algorithm can be used to mining data set in maple after feature extraction

hope systematic and automatic doing this instead of using eyes

i feel derived attributes are unlimited, how to know sufficient?

Hi,

Can Maple solve mathematical models? And can I use it to solve LP and NLPs?

in real practice, 

what is application of the cycles in algcurves[homology] ?

is there any book teaching about the use of this function in maple?

I want to define a function f in Maple such that $f(x[1,2]^{-1/3})=\{1,2\}, f(x[1,2])=\{1,2\}, f(x[1])=\{1\}, f(x[1]^{1/3}) =\{1\}$, f(x)=empty set. How could I do this in Maple? Thank you very much.

Running the code costs a lot of time, I need some suggestions to make faster and more accurate. Thanks!

sonkok.mw

how to convert (a+b)^3 to a list [a+b, a+b, a+b]?

for example

(a+b)^2 to [a+b, a+b]

I would like work in Riemann Normal Coordinates, and derive expansion in number of derivatives of the metric.

For example, starting with the expansion of the metric in Riemann Normal Coordinates (assuming this needs not be derived)

I would like to express the lapliacian, or square-root of the determinant ... etc., in terms of this metric and derive an expansion for them.

However, I cannot even define the metric as such in Maple-Physics, because the coefficients of x^k depend themselfs upon the metric to be defined.

Is there a way to do such calculations in Maple ?

how to count how many terms or items are equal when compare two lists of polynomial terms when length of two list may not be equal

cannot find the error in loop

> restart; u[0] := (4/3)*c^2*cos((1/4)*x)^2; alpha := 2;
 
> iteration := 3;
> for k from 0 while k <= Iteration do u[s] := eval(u[k], t = xi); u[k+1] := simplify(u[k]-(int(diff(u[s], [`$`(xi, alpha)])+diff(u[s]*u[s], x)+diff(u[s]*u[s], x, x, x), xi = 0 .. t))) end do;

Here's a short tensor manipulation which goes totally bananas. Basically I have a metric, and I define a vector k, and right at the end I calcualte the covariant derivative of it. In the metric and elsewhere I have a constant epsilon, a function of time a(t), and 2 functions of all coords, Phi and psi. Then at the end it gives the covariant derivative of k, but now with epsilon and a as functions of all coordinates. 

Any idea what's going on??

code:

restart;
with(Physics);with(PDEtools):
Setup(coordinatesystems=spherical);

ds2:=expand(a(t)^2*(-(1+2*epsilon*Phi(r,theta,phi,t))*dt^2+(1-2*epsilon*psi(r,theta,phi,t))*(dr^2+r^2*dtheta^2+r^2*sin(theta)^2*dphi^2)));
declare(%,(H)(t),(k0,k1,k2,k3)(X));
Setup(metric = ds2);

Define(k[~mu]=[-1/a(t)^2+epsilon*k1(X),epsilon*k2(X),epsilon*k3(X),1/a(t)^2+epsilon*k0(X)]);

Define(NullGDE[nu]=(k[~mu](X)*D_[mu](k[nu](X))),OpticalDeformationMatrix[mu,nu]=(D_[mu](k[nu](X))));

(OpticalDeformationMatrix[1,1,nonzero]);

the final output is Matrix(1, 1, [[(-(2*((diff(epsilon(X), r))*(psi(X))(X))+2*epsilon(X)*(diff((psi(X))(X), r)))*(epsilon(X)*(k1(X))(X)*((a(t))(X)^2)-1)*a(t)-(2*epsilon(X)*(psi(X))(X)-1)*((diff(epsilon(X), r))*(k1(X))(X)*((a(t))(X)^2)+epsilon(X)*((diff((k1(X))(X), r))*((a(t))(X)^2))+2*epsilon(X)*(k1(X))(X)*(a(t))(X)*(diff((a(t))(X), r)))*a(t)+epsilon*psi[r]*(epsilon*k1(X)*(a(t)^2)-1)*a(t)-epsilon^2*psi[theta]*(a(t)^3)*k2(X)-epsilon^2*psi[phi]*(a(t)^3)*k3(X)-(2*(diff(a(t), t))*psi(X)*epsilon+psi[t]*a(t)*epsilon-(diff(a(t), t)))*(epsilon*k0(X)*(a(t)^2)+1))*(1/a(t))]])

where epsilon is now a function!

This may be a silly question, but does there exist some simple way of (Taylor) expanding an expression of 'small' functions in terms of these functions.

A simple example: Assume that diff(f(x),x) and g(x) are two functions both with range, say, in [-a,+a], where a << 1, and consider the following expression:

sqrt(1 + diff(f(x),x)) * (2 + g(x));

Its expansion to first order in terms of diff(f(x),x) and g(x) should be 2 + diff(f(x),x) + g(x). My problem is that mtaylor does not accept functions as variables to expand on, and I would prefer not to have to substitute back and forth with some 'placeholders'.

The help text for dsolve,numeric,events describes many kinds of triggers and actions and other event specifications, but shows only a very limited selection of examples of these possibilities.

Please tell me of any sources containing extensive examples of the wide variety of available specifications and the problems they are useful in solving.

> restart:with(plots):blt:=7:

> lambda:=2:m:=3:s:=1:

> Eq1:=(diff(f(eta),eta,eta,eta))+(f(eta)*(diff(f(eta),eta,eta)))-((diff(f(eta),eta))^2)+lambda*(((f(eta)*(diff(f(eta),eta,eta,eta))))-2*(diff(f(eta),eta))*(diff(f(eta),eta,eta,eta))^2)-(M/(1+m^2))*((diff(f(eta),eta)+ms))=0;

>

> Eq2:=(diff(h(eta),eta,eta))+(f(eta)*(diff(h(eta),eta)))-((diff(f(eta),eta))*(h(eta)))+lambda*(((f(eta)*(diff(h(eta),eta,eta,eta))))+(h(eta)*(diff(f(eta),eta,eta,eta)))+(diff(f(eta),eta,eta))*(diff(h(eta),eta))-2*(diff(f(eta),eta))*(diff(h(eta),eta,eta))+(M/(1+m^2)))*(m*(diff(f(eta),eta)-h))=0;

>

> Eq3:=((f(eta))*(diff(theta(eta),eta)))+Pr*((diff(theta(eta),eta,eta)))=0;

>

> bcs1 := f(0) = 0, (D(f))(0) = 1, (h)(0) = 0, (theta)(0) = 1, (D(f))(blt) = 0,  h(blt) = 0, theta(blt) = 0, D(D(f))(blt) = 0, (D(h))(blt)=0;

>

> L := [1,2,3];

> for k to 3 do R := dsolve(eval({Eq1, Eq2, Eq3, bcs1}, M = L[k]), [f(eta),h(eta),theta(eta)], numeric, maxmesh=10000, output = listprocedure);;Y || k := rhs(R[3]); YA || k := rhs(R[6]);YB || k := rhs(R[5]);YC || k := rhs(R[4]);YD || k := rhs(R[7]);end do:

>

>

>

Error, (in dsolve/numeric/bvp/convertsys) unable to convert to an explicit first-order system

for example is there an existing package for reducing groups of matrices like the one below to only its unique elements, or do i basically need to use  linear algebra matrix operations ie finding the basis of the set via echeleon reduction blah blah

{Matrix(2, 2, {(1, 1) = 0, (1, 2) = 0, (2, 1) = 0, (2, 2) = -673/2880}), Matrix(2, 2, {(1, 1) = 0, (1, 2) = 0, (2, 1) = 0, (2, 2) = -5/96}), Matrix(2, 2, {(1, 1) = 0, (1, 2) = -(2521/17920)*Zeta(5), (2, 1) = 0, (2, 2) = -(2521/17920)*Zeta(3)-2087/1920}), Matrix(2, 2, {(1, 1) = 0, (1, 2) = 0, (2, 1) = 0, (2, 2) = 0}), Matrix(2, 2, {(1, 1) = 0, (1, 2) = -(7/320)*Zeta(5), (2, 1) = 0, (2, 2) = -(7/320)*Zeta(3)-499/840})}