Answer: None; all will be recoverable
Explanation:
If a signal (band-limited) is sampled at regular intervals, it could be recoverable or not, based on the number of samples taken.
Let's assume that we want to take samples of a simple sinusoid; If we take more than two samples during a signal cycle, the original waveform will be able to be reconstructed, just passing the sampled waveform through a low-pass filter.
In the more general case in which the signal occupies a frequency spectrum, if the sample frequency is greater than the double of the highest frequency in the spectrum, the signal can be retrieved completely, according to the Nyquist Theorem.
In this case , as the highest frequency is 145 Hz, it would be enough to take samples at a rate greater than 290 Hz; As the sample rate is 295 Hz, all the signal can be recovered, at least, using an ideal "brickwall" low-pass filter.
Answer:
I'm doing a digital media test right now
Answer:
here
Explanation:
Python is an interpreted high-level general-purpose programming language. Its design philosophy emphasizes code readability with its use of significant indentation.
Answer:
random_number_file = open("1000 Random Number from 0 to 100.txt", 'r')
random_number_list = random_number_file.readlines()
print('random_number_list)
Explanation:
The name of the file containing the random integer text is ; "1000 Random Number from 0 to 100.txt"
The random_number_file variable stores the opened file ("1000 Random Number from 0 to 100.txt") using the open keyword and reads it ('r')
This file stored in the random_number_file variable is the read into a list by using the readlines() method on the random_number_file
