"Noise signals are unwanted signals that are always present in a transmission system." (John R Pierce, "Signals: The Telephone and Beyond", 1981)
"Neither noise nor information is predictable." (Ray Kurzweil, "The Age of Spiritual Machines: When Computers Exceed Human Intelligence", 1999)
"No matter what the data, and no matter how the values are arranged and presented, you must always use some method of analysis to come up with an interpretation of the data. While every data set contains noise, some data sets may contain signals. Therefore, before you can detect a signal within any given data set, you must first filter out the noise." (Donald J Wheeler," Understanding Variation: The Key to Managing Chaos" 2nd Ed., 2000)
"We analyze numbers in order to know when a change has
occurred in our processes or systems. We want to know about such changes in a
timely manner so that we can respond appropriately. While this sounds rather
straightforward, there is a complication - the numbers can change even when our
process does not. So, in our analysis of numbers, we need to have a way to
distinguish those changes in the numbers that represent changes in our process
from those that are essentially noise." (Donald J Wheeler, "Understanding
Variation: The Key to Managing Chaos" 2nd Ed., 2000)
"While all data contain noise, some data contain signals. Before you can detect a signal, you must filter out the noise." (Donald J Wheeler, "Understanding Variation: The Key to Managing Chaos" 2nd Ed., 2000)
"The acquisition of information is a flow from noise to
order - a process converting entropy to redundancy. During this process, the
amount of information decreases but is compensated by constant re- coding. In
the recoding the amount of information per unit increases by means of a new
symbol which represents the total amount of the old. The maturing thus implies
information condensation. Simultaneously, the redundance decreases, which
render the information more difficult to interpret." (Lars Skyttner,
"General Systems Theory: Ideas and Applications", 2001)
"In fact, an information theory that leaves out the
issue of noise turns out to have no content." (Hans Christian von Baeyer,
"Information, The New Language of Science", 2003)
"This phenomenon, common to chaos theory, is also known
as sensitive dependence on initial conditions. Just a small change in the
initial conditions can drastically change the long-term behavior of a system.
Such a small amount of difference in a measurement might be considered
experimental noise, background noise, or an inaccuracy of the equipment."
(Greg Rae, Chaos Theory: A Brief Introduction, 2006)
"Data analysis is not generally thought of as being
simple or easy, but it can be. The first step is to understand that the purpose
of data analysis is to separate any signals that may be contained within the
data from the noise in the data. Once you have filtered out the noise, anything
left over will be your potential signals. The rest is just details."
(Donald J Wheeler," Myths About Data Analysis", International Lean
& Six Sigma Conference, 2012)
"Distinguishing the signal from the noise requires both
scientific knowledge and self-knowledge." (Nate Silver, "The Signal and the
Noise: Why So Many Predictions Fail-but Some Don't", 2012)
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