Concept:
Shannon’s Information Theory deals with quantifying information, limits of communication, and efficient data transmission.
Step 1: Entropy
Entropy measures uncertainty or information content:
\[
H = -\sum p_i \log p_i
\]
It is a fundamental concept introduced by Shannon.
\[
\Rightarrow \text{A is correct}
\]
Step 2: Matched Filter
Matched filter is a receiver design technique, not a fundamental Shannon concept.
\[
\Rightarrow \text{B is incorrect}
\]
Step 3: Auto-correlation
Auto-correlation is a signal processing concept, not directly a Shannon theory concept.
\[
\Rightarrow \text{C is incorrect}
\]
Step 4: Channel Capacity
Channel capacity theorem defines the maximum rate of error-free communication:
\[
C = B \log_2(1 + S/N)
\]
\[
\Rightarrow \text{D is correct}
\]
\[
\therefore \text{Correct answer is (A)}
\]