Basic Solutions and Linear Combinations

In summary, the conversation discusses a homogeneous system of linear equations with four variables and its reduced row echelon form. It clarifies the concept of basic solutions and provides a subroutine in Fortran 77 for reading and correcting data. The subroutine includes input prompts for the user and outputs the system size, coefficient matrix, and constant vector.
  • #1
lapo3399
55
0
Just to clarify these concepts: if a homogeneous system of linear equations with four variables z1, z2, z3, and z4 yields a matrix in reduced row echelon form that defines (as an arbitrary example) the linear equations

z1 = z3 + 0.5z4 = t + 0.5s
z2 = 2z3 - z4 = 2t - s
z3 = t
z4 = s

then the linear combination should be:

[tex]
\left[ \begin{array}{ c } z1 & z2 & z3 & z4 \end{array} \right] = t \left[ \begin{array}{ c } 1 & 2 & 1 & 0 \end{array} \right] + s \left[ \begin{array}{ c } 0.5 & -1 & 0 & 1 \end{array} \right]
[/tex]

and the basic solutions are:

[tex]
\left[ \begin{array}{ c } 1 & 2 & 1 & 0 \end{array} \right] , \left[ \begin{array}{ c } 0.5 & -1 & 0 & 1 \end{array} \right]
[/tex]

My main problem is understanding exactly what the basic solutions are. I'm not sure whether they're just the direction vectors multiplied by each of the parameters or whether they include the parameters as well. Please clarify this for me.

Thanks.
 
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  • #2
pls i need some one to help me correct my read subroutine in fortran 77.i must have made some errors and i need to be corrected.Thanks
walterman

c**********************************************************
subroutine read_data(a,b,n,nsys)
c**********************************************************
implicit double precision (a-h,o-z)
dimension a(n,n),b(n)
charactername*20, form*50
c
write(*,*)
write(*,*) 'Enter configuration file name: '
read (*,'(a)')
open(unit=10,file='fname',status='New',iostat=non)
100 continue
read(unit=*,fmt=*) nsys
if(nsys.eq.5) then
form='(5f10.5)'
else
form='(6f10.5)'
end if
read(unit=*,fmt=*,err=999) ((a(i,j), j=1,nsys), i=1,nsys)
read(unit=*,fmt=*,err=999) (b(i), i=1,nsys)
999 write(*,*)
write(*,'(a,i3,a,f16.8)') ' System size : ',nsys,' x',nsys
write(*,*)
write(*,*) 'xmulticient matrix : '
write(20,fmt=form) ((a(i,j), j=1,nsys), i=1,nsys)
write(*,fmt=form) ((a(i,j), j=1,nsys), i=1,nsys)
write(*,*)
write(*,*) 'constant vector: '
write(21,fmt=form) (b(i), i=1,nsys)
write(*,fmt=form) (b(i), i=1,nsys)
write(*,*)

return
end
 
  • #3


The basic solutions are the specific values for the parameters (t and s) that satisfy the system of equations. In this case, the basic solutions are the vectors [1, 2, 1, 0] and [0.5, -1, 0, 1] when t and s are set to any real number. These solutions form the basis for all other solutions to the system of equations.

To further clarify, the basic solutions represent the direction vectors (or the coefficients of the variables) that, when multiplied by the parameters, give the specific solutions to the system of equations. So in this case, [1, 2, 1, 0] represents the direction vector for t and [0.5, -1, 0, 1] represents the direction vector for s.

In summary, the basic solutions are the specific values for the parameters that make up the linear combination of the direction vectors, which in turn give the solutions to the system of equations.
 

1. What is a basic solution in linear algebra?

A basic solution in linear algebra is a particular solution to a system of linear equations that contains no free variables. In other words, it is a solution that satisfies all of the equations in the system.

2. How do you find basic solutions in linear algebra?

To find basic solutions in linear algebra, you can use the Gaussian elimination method to reduce the system of equations to echelon form. The basic solutions will then be the solutions to the system with all free variables set to 0.

3. What is a linear combination?

A linear combination is a mathematical operation where two or more vectors are multiplied by a scalar and then added together. This can also be thought of as scaling and combining vectors to create a new vector.

4. How do you determine if a vector is a linear combination of other vectors?

To determine if a vector is a linear combination of other vectors, you can set up a system of equations where the coefficients of the vectors are the variables. If there exists a solution to the system of equations, then the vector is a linear combination of the other vectors.

5. Why are basic solutions and linear combinations important in linear algebra?

Basic solutions and linear combinations are important in linear algebra because they allow us to solve systems of equations and express vectors in terms of other vectors. They also form the basis for many other concepts in linear algebra, such as vector spaces and matrix operations.

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