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The normalized auto correlation ρxx(l) is defined as:
- a)(rxx (l))/(rxx (0))
- b)-(rxx (l))/(rxx (0))
- c)(rxx (l))/(rxy (0))
- d)None of the mentioned
Correct answer is option 'A'. Can you explain this answer?
Verified Answer
The normalized auto correlation ρxx(l) is defined as:a)(rxx(l))/(r...
Explanation: If the signal involved in auto correlation is scaled, the shape of auto correlation does not change, only the amplitudes of auto correlation sequence are scaled accordingly. Since scaling is unimportant, it is often desirable, in practice, to normalize the auto correlation sequence to the range from -1 to 1. In the case of auto correlation sequence, we can simply divide by rxx (0). Thus the normalized auto correlation sequence is defined as ρxx(l)= (rxx (l))/(rxx (0)).
Most Upvoted Answer
The normalized auto correlation ρxx(l) is defined as:a)(rxx(l))/(r...
The normalized auto-correlation is a statistical measure that describes the degree of similarity between a signal and a delayed version of itself. It is a normalized version of the auto-correlation function, which is a measure of the correlation between two signals as a function of the time lag between them.
The normalized auto-correlation is often used in signal processing and time-series analysis to identify patterns and relationships between data points. It is typically calculated by dividing the auto-correlation function by the product of the standard deviations of the two signals being compared.
The resulting value ranges from -1 to 1, with a value of 1 indicating perfect correlation, 0 indicating no correlation, and -1 indicating perfect anti-correlation. A high value of normalized auto-correlation indicates that there is a strong relationship between the two signals, while a low value suggests the opposite.
The normalized auto-correlation is often used in signal processing and time-series analysis to identify patterns and relationships between data points. It is typically calculated by dividing the auto-correlation function by the product of the standard deviations of the two signals being compared.
The resulting value ranges from -1 to 1, with a value of 1 indicating perfect correlation, 0 indicating no correlation, and -1 indicating perfect anti-correlation. A high value of normalized auto-correlation indicates that there is a strong relationship between the two signals, while a low value suggests the opposite.
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