To solve this problem, we need to calculate the Discrete Fourier Transform (DFT) of the convolution of the signals \( x(n) \) and \( h(n) \). This will help us relate the given information about \( Y(e^{j0}) = 36 \) to the correct expression involving \( a \), \( b \), and \( c \).
- Discrete Fourier Transform (DFT): The DFT of a sequence \( y(n) \) is given by:
\[ Y(e^{j\omega}) = \sum_{n=0}^{N-1} y(n) e^{-j\omega n} \]
- Convolution: The convolution of \( x(n) \) and \( h(n) \) is defined as:
\[ y(n) = (x(n) \otimes h(n)) = \sum_{k=0}^{M-1} x(k) h(n-k) \]
For this case, \( x(n) = \{0, 1, 1, 2\} \) and \( h(n) = \{a, b, c\} \). The DFT of the convolution can be computed using the DFTs of \( x(n) \) and \( h(n) \), leveraging the fact that the DFT of a convolution is the product of the DFTs of the individual sequences.
The DFT at \( \omega = 0 \) (DC component) is:
\[ Y(e^{j0}) = \sum_{n=0}^{N-1} y(n) = 36 \]
Thus, the sum of the sequence \( y(n) \) equals 36. Since \( y(n) = x(n) \otimes h(n) \), we need to compute this sum explicitly. The sequence \( y(n) \) can be found by performing the convolution operation:
\[ y(n) = \{ x(0)h(0) + x(1)h(0) + x(2)h(0) + x(3)h(0), x(0)h(1) + x(1)h(1) + x(2)h(1) + x(3)h(1), x(0)h(2) + x(1)h(2) + x(2)h(2) + x(3)h(2) \} \]
Let’s compute the sum of \( y(n) \). We know that:
\[ Y(e^{j0}) = x(0)a + x(1)a + x(2)a + x(3)a + x(0)b + x(1)b + x(2)b + x(3)b + x(0)c + x(1)c + x(2)c + x(3)c \] \[ Y(e^{j0}) = a(0 + 1 + 1 + 2) + b(0 + 1 + 1 + 2) + c(0 + 1 + 1 + 2) \] \[ Y(e^{j0}) = a \times 4 + b \times 4 + c \times 4 = 4(a + b + c) \] Since \( Y(e^{j0}) = 36 \), we have: \[ 4(a + b + c) = 36 \] \[ a + b + c = 9 \]The correct relation is \( a + b + c = 9 \).