On Noise V

"If the channel is noisy it is not in general possible to reconstruct the original message or the transmitted signal with certainty by any operation on the received signal. There are ways, however, of transmitting the information which are optimal in combating noise." (Claude E. Shannon, "A Mathematical Theory of Communication", Bell System Technical journal, 1948)

"Black-noise phenomena govern natural and unnatural catastrophes like floods, droughts, bear markets, and various outrageous outages, such as those of electrical power. Because of their black spectra, such disasters often come in clusters." (Manfred R Schroeder, "Fractals, Chaos, Power Laws", 1991)

"Engineers have sought to minimize the effects of noise in electronic circuits and communication systems. But recent research has established that noise can play a constructive role in the detection of weak periodic signals." (Kurt Wiesenfeld & Frank Moss, "Stochastic Resonance and the Benefits of Noise: From Ice Ages to Crayfish and SQUIDs", Nature vol. 373, 1995)

"Most engineering systems in communication, control, and signal processing are developed under the often erroneous assumption that the interfering noise is Gaussian. Many physical environments are more accurately modeled as impulsive, characterized by heavy-tailed non-Gaussian distributions. The performances of systems developed under the assumption of Gaussian noise can be severely degraded by the non-Gaussian noise due to potent deviation from normality in the tails." (Seong Rag Kim & Adam Efron, "Adaptive Robust Impulse Noise Filtering", IEEE Transactions on Signal Processing vol. 43 (8), 1995)

"Stochastic resonance simply stands for a new paradigm wherein noise represents a useful tool rather than a nuisance." (Luca Gammaitoni et al, "Stochastic Resonance" Reviews of Modern Physics vol. 70 (l), 1998)

"Uncovering the mysteries of natural phenomena that were formerly someone else's 'noise' is a recurring theme in science." (Alfred Bedard Jr & Thomas Georges, "Atmospheric Infrasound", Physics Today vol. 53 (3), 2000)

"Not all systems crackle. Some respond to external fines with many similar-sized small events (popcorn popping it is heated). Others give way in one single event (chalk snapping as it is stressed). Crackling noise is between these two limits." (James P. Sethna et al, "Crackling Noise", Nature vol. 410, 2001)

"Apart from intrinsic noise sources at the level of an individual neuron there are also sources of noise that are due to signal transmission and network effects. Synaptic transmission failures, for instance, seem to impose a substantial limitation within a neuronal network." (Wulfram Gerstner & Werner Kistler, "Spiking Neuron Models: Single Neurons, Population, Plasticity", 2002)

"Any technical discussion of noise begins with white noise because white noise is pure or ideal noise. White noise serves as the gold standard of noise. Scientists and engineers have explored hundreds of other noise types but most of these deviate from white noise in some specific way. White noise is noisy because it has a wide and flat band of frequencies if one looks at its spectrum. This reflects the common working definition of noise as a so-called wideband signal. Good signals or wanted signals concentrate their energy on a comparatively narrow band of the frequency spectrum. Hence good signals tend to be so-called narrowband signals at least relative to the wide band of white noise. White noise is so noisy because its spectrum is as wide as possible - it runs the whole infinite length of the frequency spectrum itself. So pure or ideal white noise exists only as a mathematical abstraction. It cannot exist physically because it would require infinite energy." (Bart Kosko, "Noise", 2006)

"Noise is a signal we don't like. Noise has two parts. The first has to do with the head and the second with the heart. The first part is the scientific or objective part: Noise is a signal. [...] The second part of noise is the subjective part: It deals with values. It deals with how we draw the fuzzy line between good signals and bad signals. Noise signals are the bad signals. They are the unwanted signals that mask or corrupt our preferred signals. They not only interfere but they tend to interfere at random." (Bart Kosko, "Noise", 2006)