dy/dx - = 1 - y,y(0) = 0 is an example of

[zaasmi]

In interpolation is used to represent the δ
Forward difference Δ
Central difference
Backward difference

[zaasmi]

@zaasmi said in MTH603 Mid Term Past and Current Solved Paper Discussion:

In interpolation is used to represent the δ
Forward difference Δ
Central difference
Backward difference

In interpolation, the notation (\delta) typically represents the forward difference operator.

Explanation:

• Forward Difference (\delta): Used to denote the difference between successive values in a sequence. If ( f(x) ) is a function and ( \delta f(x) ) represents the forward difference, then:
  [ \delta f(x) = f(x + h) - f(x) ]

• Backward Difference (\nabla): Represents the difference between preceding values in a sequence. If ( \nabla f(x) ) represents the backward difference, then:
  [ \nabla f(x) = f(x) - f(x - h) ]

• Central Difference: Represents the average of the forward and backward differences:
  [ \Delta f(x) = \frac{f(x + h) - f(x - h)}{2} ]

• Difference Operator (\Delta): This operator generally represents the forward difference when used in the context of interpolation.

Thus, in interpolation, the symbol (\delta) is used to represent the forward difference.

So the correct option is:

Forward difference (\delta)

[zaasmi]

The base of the decimal system is _______
10
0
2
8
None of the above.

[zaasmi]

@zaasmi said in MTH603 Mid Term Past and Current Solved Paper Discussion:

The base of the decimal system is _______
10
0
2
8
None of the above.

The base of the decimal system is:

10

Explanation:

• Decimal System: The decimal system, also known as the base-10 system, uses ten digits (0 through 9) to represent numbers.

• Other Bases:

  • Binary System: Base-2 (digits 0 and 1).
  • Octal System: Base-8 (digits 0 through 7).
  • Hexadecimal System: Base-16 (digits 0 through 9 and letters A through F).

So the correct option is:

10

[zaasmi]

Bisection method is … method
► Open Method
► Bracketing Method

[zaasmi]

@zaasmi said in MTH603 Mid Term Past and Current Solved Paper Discussion:

Bisection method is … method
► Open Method
► Bracketing Method

The Bisection method is a:

Bracketing Method

Explanation:

• Bracketing Method: This method involves finding an interval [a, b] where the function changes sign (i.e., (f(a) \cdot f(b) < 0)). The bisection method iteratively reduces this interval to home in on the root.

• Open Method: This method does not require bracketing of the root. Examples include Newton-Raphson and Secant methods.

The Bisection method is specifically a bracketing method because it starts with an interval that contains the root and continuously reduces the size of this interval to locate the root more accurately.

So the correct option is:

Bracketing Method

[zaasmi]

A 3 x 3 identity matrix have three and __________eigen values.

same
different

[zaasmi]

@zaasmi said in MTH603 Mid Term Past and Current Solved Paper Discussion:

A 3 x 3 identity matrix have three and __________eigen values.

same
different

A (3 \times 3) identity matrix has three eigenvalues, and they are all the same.

Explanation:

• An identity matrix (I) of size (n \times n) has all its diagonal elements equal to 1 and all off-diagonal elements equal to 0.

• The eigenvalues of an (n \times n) identity matrix are all equal to 1.

For a (3 \times 3) identity matrix, the eigenvalues are (1, 1, 1), meaning they are all the same.

So the correct answer is:

same

[zaasmi]

Eigenvalues of a symmetric matrix are all _______ .
Real
complex
zero
positive

[zaasmi]

@zaasmi said in MTH603 Mid Term Past and Current Solved Paper Discussion:

Eigenvalues of a symmetric matrix are all _______ .
Real
complex
zero
positive

The eigenvalues of a symmetric matrix are all:

Real

Explanation:

• Symmetric Matrix: A matrix (A) is symmetric if (A = A^T) (i.e., (A) is equal to its transpose).

• The eigenvalues of a symmetric matrix are always real numbers, regardless of whether the matrix is positive definite or not.

• Symmetric matrices may also have complex eigenvalues, but only in the case of non-real matrices. For symmetric matrices, the eigenvalues are guaranteed to be real.

So the correct option is:

Real

[zaasmi]

The Jacobi iteration converges, if A is strictly diagonally dominant.
TRUE (Page 69)
FALSE

[zaasmi]

@zaasmi said in MTH603 Mid Term Past and Current Solved Paper Discussion:

The Jacobi iteration converges, if A is strictly diagonally dominant.
TRUE (Page 69)
FALSE

TRUE

Explanation:

• Jacobi Iteration: This is an iterative method used to solve a system of linear equations. It involves iterating on the solution vector using the diagonal elements of the coefficient matrix.

• Strict Diagonal Dominance: A matrix is strictly diagonally dominant if, for each row of the matrix, the magnitude of the diagonal element is greater than the sum of the magnitudes of all other (non-diagonal) elements in that row.

• Convergence: The Jacobi iteration method converges if the coefficient matrix ( A ) is strictly diagonally dominant. This means that the method will approach the correct solution if this condition is met.

So the correct statement is:

TRUE

[zaasmi]

Below are all the finite difference methods EXCEPT _________.
jacobi’s method
newton’s backward difference method
Stirlling formula
Forward difference method

[zaasmi]

@zaasmi said in MTH603 Mid Term Past and Current Solved Paper Discussion:

Below are all the finite difference methods EXCEPT _________.
jacobi’s method
newton’s backward difference method
Stirlling formula
Forward difference method

The correct answer is:

Jacobi’s method

Explanation:

• Jacobi’s Method: This is an iterative method for solving a system of linear equations, not a finite difference method.

• Newton’s Backward Difference Method: This is a finite difference method used for interpolation and numerical differentiation.

• Stirling Formula: This is used for interpolation in finite difference methods and approximates the values of the function using finite differences.

• Forward Difference Method: This is used in finite difference methods to approximate derivatives and solve differential equations.

Thus, Jacobi’s method is not a finite difference method, so it is the correct choice for the given question.

[zaasmi]

Two matrices with the same characteristic polynomial need not be similar.
TRUE
FALSE

[zaasmi]

@zaasmi said in MTH603 Mid Term Past and Current Solved Paper Discussion:

Two matrices with the same characteristic polynomial need not be similar.
TRUE
FALSE

TRUE

Explanation:

• Similar Matrices: Two matrices (A) and (B) are similar if there exists an invertible matrix (P) such that (B = P^{-1}AP). Similar matrices share the same eigenvalues and their Jordan forms are the same, which means they have the same characteristic polynomial.

• Characteristic Polynomial: Matrices that have the same characteristic polynomial are guaranteed to have the same eigenvalues, but this alone does not guarantee similarity. Similar matrices must also have the same Jordan canonical form or must be related by a similarity transformation.

Therefore, having the same characteristic polynomial is a necessary but not sufficient condition for similarity.

So, the correct statement is:

TRUE