We are given two discrete-time signals $x(n)$ and $h(n)$: $x(n) = \{0, 1, 1, 2\}$ $h(n) = \{a, b, c\}$
The signal $y(n)$ is the convolution of $x(n)$ and $h(n)$: $y(n) = x(n) \otimes h(n)$
We are also given that $Y(e^{j\omega})$ is the Discrete Fourier Transform (DFT) of $y(n)$, and $Y(e^{j0}) = 36$.
A key property of the DFT (or DTFT) is that its value at $\omega = 0$ corresponds to the sum of the samples of the time-domain signal. So, $Y(e^{j0}) = \sum_{n} y(n)$.
Another important property is the convolution property of DFT: If $y(n) = x(n) \otimes h(n)$, then in the frequency domain, their DFTs multiply: $Y(e^{j\omega}) = X(e^{j\omega}) H(e^{j\omega})$
Now, let's evaluate this at $\omega = 0$: $Y(e^{j0}) = X(e^{j0}) H(e^{j0})$
We know that $X(e^{j0}) = \sum_{n} x(n)$ and $H(e^{j0}) = \sum_{n} h(n)$.
Let's calculate the sum of samples for $x(n)$: $\sum_{n} x(n) = 0 + 1 + 1 + 2 = 4$.
So, $X(e^{j0}) = 4$. Let's calculate the sum of samples for $h(n)$: $\sum_{n} h(n) = a + b + c$. So, $H(e^{j0}) = a + b + c$.
Now, substitute these into the convolution property at $\omega = 0$: $Y(e^{j0}) = X(e^{j0}) H(e^{j0})$ $36 = 4 \times (a + b + c)$
Now, solve for $(a + b + c)$: $a + b + c = \frac{36}{4}$ $a + b + c = 9$
Therefore, the correct relation is $a + b + c = 9$.
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