BY
Uday Saikia
>> p=[1 -12.1 40.59 -17.015 -71.95 35.88]
>> r=roots(p)
r=
6.5000
4.0000
2.3000
-1.2000
0.5000
6x-2
p=polyfit(x,y,n)
here p=A vector of the co-efficients of
the polynomial that fits the
data
co-
x=A vector with the horizo...
Here,
‘nearest’ : returns the value of the
data point that is nearest to the
yi = interpl (x, y, xi, ‘method’) interpolat...
x
0
1
2
y
1.0
-0.6242 -1.4707
3
4
5
3.2406
-0.7366 -6.3717
>> x=[0:1.0:5];
y=[1.0 -0.6242 -1.4707 3.2406 -0.7366 -6.3717];
xi=[0:0.1:5];
yilin=interpl(x,y,xi,'linear');
yispl=interp...
Mesh & Surface plots are created in three steps:
*create a grid in the x-y plane
*calculate the value of z at each point o...
>> x=-1:0.1:3;
>> y=1:0.1:4;
>> [X,Y]=meshgrid(x,y);
>> Z=X.*Y.^2./(X.^2+Y.^2);
>> mesh(X,Y,Z)
>> xlabel('x');
>> ylabel('...
POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
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POLYNOMIALS,CURVEFITTING, AND INTERPOLATION

POLYNOMIALS,CURVEFITTING, AND INTERPOLATION
Published on: Mar 4, 2016
Published in: Education      Technology      Art & Photos      
Source: www.slideshare.net


Transcripts - POLYNOMIALS,CURVEFITTING, AND INTERPOLATION

  • 1. BY Uday Saikia
  • 2. >> p=[1 -12.1 40.59 -17.015 -71.95 35.88] >> r=roots(p) r= 6.5000 4.0000 2.3000 -1.2000 0.5000
  • 3. 6x-2
  • 4. p=polyfit(x,y,n) here p=A vector of the co-efficients of the polynomial that fits the data co- x=A vector with the horizontal ordinate of the data points y= A vector with the vertical co-ordinate of the data points n=Degree of polynomial
  • 5. Here, ‘nearest’ : returns the value of the data point that is nearest to the yi = interpl (x, y, xi, ‘method’) interpolated point ‘linear’ : uses linear spline interpolation ‘spline’ : uses cubic spline interpolation yi = It is Interpolated value ‘pchip’ : uses piecewise cubic Hermite interpolation x = It is a vector with horizontal co-ordinate of the input data points y = It is a vector with vertical co-ordinate of the input data points xi = Horizontal co-ordinate of the interpolation point
  • 6. x 0 1 2 y 1.0 -0.6242 -1.4707 3 4 5 3.2406 -0.7366 -6.3717
  • 7. >> x=[0:1.0:5]; y=[1.0 -0.6242 -1.4707 3.2406 -0.7366 -6.3717]; xi=[0:0.1:5]; yilin=interpl(x,y,xi,'linear'); yispl=interpl(x,y,xi,'spline'); yipch=interpl(x,y,xi,'pchip'); yfun=1.5.^xi*cos(2*xi); subplot(1,3,1) plot(x,y,'o'xi,yfun,xi,yilin,'--'); subpolt(1,3,2) plot(x,y,'o',xi,yfun,xi,yispl,'--'); subplot(1,3,3) plot(x,y,'o',xi,yfun,xi,yipch,'--')
  • 8. Mesh & Surface plots are created in three steps: *create a grid in the x-y plane *calculate the value of z at each point of the grid *create the plot
  • 9. >> x=-1:0.1:3; >> y=1:0.1:4; >> [X,Y]=meshgrid(x,y); >> Z=X.*Y.^2./(X.^2+Y.^2); >> mesh(X,Y,Z) >> xlabel('x'); >> ylabel('y'); >> zlabel('z');