canonic.m The procedure determines the distribution for a simple random variable in
affine form, when the minterm probabilities are available. Input data are a row vector of coefficientsfor the indicator functions in the affine form (with the constant value last) and a row vector of the
probabilities of the minterm generated by the events. Results consist of a row vector of values and arow vector of the corresponding probabilities.
% CANONIC file canonic.m Distribution for simple rv in affine form
% Version of 6/12/95% Determines the distribution for a simple random variable
% in affine form, when the minterm probabilities are available.% Uses the m-functions mintable and csort.
% The coefficient vector must contain the constant term.
% If the constant term is zero, enter 0 in the last place.c = input(' Enter row vector of coefficients ');
pm = input(' Enter row vector of minterm probabilities ');n = length(c) - 1;
if 2^n ~= length(pm)error('Incorrect minterm probability vector length');
endM = mintable(n); % Provides a table of minterm patterns
s = c(1:n)*M + c(n+1); % Evaluates X on each minterm[X,PX] = csort(s,pm); % s = values; pm = minterm probabilitiesXDBN = [X;PX]';disp('Use row matrices X and PX for calculations')
disp('Call for XDBN to view the distribution')
canonicf.mfunction [x,px] = canonicf(c,pm) is a function version of canonic,
which allows arbitrary naming of variables.
function [x,px] = canonicf(c,pm)% CANONICF [x,px] = canonicf(c,pm) Function version of canonic% Version of 6/12/95
% Allows arbitrary naming of variablesn = length(c) - 1;
if 2^n ~= length(pm)error('Incorrect minterm probability vector length');
endM = mintable(n); % Provides a table of minterm patterns
s = c(1:n)*M + c(n+1); % Evaluates X on each minterm[x,px] = csort(s,pm); % s = values; pm = minterm probabilities
jcalc.m Sets up for calculations for joint simple random variables. The matrix
P of
$P(X={t}_{i},Y={u}_{j})$ is arranged as on the plane (i.e., values of
Y increase upward).
The MATLAB function meshgrid is applied to the row matrix
X and the reversed row matrix
for
Y to put an appropriate
X -value and
Y -value at each position. These are in the
“calculating matrices”
t and
u , respectively, which are used in determining probabilities and
expectations of various functions of
$t,u$ .
% JCALC file jcalc.m Calculation setup for joint simple rv
% Version of 4/7/95 (Update of prompt and display 5/1/95)% Setup for calculations for joint simple random variables
% The joint probabilities arranged as on the plane% (top row corresponds to largest value of Y)
P = input('Enter JOINT PROBABILITIES (as on the plane) ');X = input('Enter row matrix of VALUES of X ');
Y = input('Enter row matrix of VALUES of Y ');PX = sum(P); % probabilities for X
PY = fliplr(sum(P')); % probabilities for Y[t,u] = meshgrid(X,fliplr(Y));disp(' Use array operations on matrices X, Y, PX, PY, t, u, and P')
fullerene is a bucky ball aka Carbon 60 molecule. It was name by the architect Fuller. He design the geodesic dome. it resembles a soccer ball.
Tarell
what is the actual application of fullerenes nowadays?
Damian
That is a great question Damian. best way to answer that question is to Google it. there are hundreds of applications for buck minister fullerenes, from medical to aerospace. you can also find plenty of research papers that will give you great detail on the potential applications of fullerenes.
Tarell
what is the Synthesis, properties,and applications of carbon nano chemistry
Yeah, it is a pain to say the least. You basically have to heat the substarte up to around 1000 degrees celcius then pass phosphene gas over top of it, which is explosive and toxic by the way, under very low pressure.
Harper
Do you know which machine is used to that process?