To solve this problem, we need to calculate the compression ratio for the given AZTEC coded data.
- Compression Ratio: The compression ratio is defined as the ratio of the original size of the data to the size of the compressed data. It is calculated using the formula:
\[ \text{Compression Ratio} = \frac{\text{Original Size}}{\text{Compressed Size}} \]
The original size refers to the number of elements in the uncompressed data, while the compressed size refers to the number of elements in the compressed data.
The given AZTEC coded data is:
\[ [5, 10, -5, 100, 2, 5, -4, 100] \]
The original size of the data is the number of elements in the array, which is 8 (since there are 8 numbers). Assuming that the compressed data uses 1 bit for each value (which is a common case for compression algorithms like AZTEC), the size of the compressed data would be proportional to the number of distinct values or symbols.
For simplicity, we assume that the compressed data contains fewer bits or elements than the original data, typically achieving a significant reduction in size. The exact size of the compressed data can be calculated based on the algorithm used, but the options suggest a common compression ratio.
The most likely compression ratio for the given data is \( \text{1:8} \), which means that the data was compressed to 1/8th of its original size.
What is the voltage across the inductor at $t=0$? (Circuit diagram provided: A 60V voltage source in series with a switch that closes at $t=0$, a 30 ohm resistor, and a 15H inductor.) 
The overall impulse response of the system shown in figure is given by (Block diagram provided: Input $X(n)$ splits. One path goes to $h_1[n]$, another to $h_2[n]$. The outputs of $h_1[n]$ and $h_2[n]$ are subtracted. This result is convolved with $h_3[n]$. Separately, $X(n)$ also goes to $h_5[n]$. The output of $h_3[n]$ and $h_5[n]$ are subtracted. This result is convolved with $h_4[n]$ to produce $y(n)$.) 