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Signal-to-Noise Ratio: Difference between revisions
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Signal-to-noise ratio (abbreviated SNR) is a measure used in science and engineering that compares the level of a desired signal to the level of background noise. It is defined as the ratio of signal power to the noise power. This is very helpful to apply in the comreprehension of developing our levels of increasing [[Higher Sensory Perception]], [[Remote Viewing]] and [[Expanding Consciousness]]. | Signal-to-noise ratio (abbreviated SNR) is a measure used in science and engineering that compares the level of a desired signal to the level of background noise. It is defined as the ratio of signal power to the noise power. This is very helpful to apply in the comreprehension of developing our levels of increasing [[Higher Sensory Perception]], [[Remote Viewing]] and [[Expanding Consciousness]]. | ||
Signal-to-noise ratio is sometimes used informally to refer to the ratio of useful information to false or irrelevant data in a conversation or exchange. For example, in online discussion forums and other online communities, off-topic posts and spam are regarded as "noise" that interferes with the "signal" of appropriate discussion. | Signal-to-noise ratio is sometimes used informally to refer to the ratio of useful information to false or irrelevant data in a conversation or exchange. For example, in online discussion forums and other online communities, off-topic posts and spam are regarded as "noise" that interferes with the "signal" of appropriate discussion.<ref>[http://en.wikipedia.org/wiki/Signal-to-noise_ratio]</ref> | ||
This is a clear example of why the [[Negative Ego]], [[Ego Defense Mechanism]] and fear must be cleared from the mind or it will impact the "noise" ratio of the clear signal input as well as the translation and deciphering of the signal input. | This is a clear example of why the [[Negative Ego]], [[Ego Defense Mechanism]] and fear must be cleared from the mind or it will impact the "noise" ratio of the clear signal input as well as the translation and deciphering of the signal input. | ||