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Books on the topic 'Signal-noise-ratio'

Author: Grafiati
Published: 4 June 2021
Last updated: 18 February 2022

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1

Sivathevan, T. Signal to quantization noise ratio. London: University of East London, 1994.

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2

J, Curran Paul. Estimating the signal-to-noise ratio of AVIRIS data. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1989.

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3

J, Curran Paul. Estimating the signal-to-noise ratio of AVIRIS data. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1989.

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4

Curran, Paul J. Estimating the signal-to-noise ratio of AVIRIS data. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1989.

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5

Robinson, A. P. The relationship between vision carrier-to-noise ratio and picture signal-to-noise ratio ina system 1 television receiver. London: BBC, 1987.

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6

Walsh, Norman J. Bandwidth and signal-to-noise ratio enhancement of the NPS Transient Electromagnetic Scattering Laboratory. Monterey, Calif: Naval Postgraduate School, 1989.

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7

Manning, Robert Michael. Real-time in situ signal-to-noise ratio estimation for the assessment of operational communications links. [Cleveland, Ohio]: National Aeronautics and Space Administration, Glenn Research Center, 2002.

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8

Manning, Robert Michael. Real-time in situ signal-to-noise ratio estimation for the assessment of operational communications links. [Cleveland, Ohio]: National Aeronautics and Space Administration, Glenn Research Center, 2002.

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9

Manning, Robert Michael. Real-time in situ signal-to-noise ratio estimation for the assessment of operational communications links. [Cleveland, Ohio]: National Aeronautics and Space Administration, Glenn Research Center, 2002.

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10

Manning, Robert Michael. Real-time in situ signal-to-noise ratio estimation for the assessment of operational communications links. [Cleveland, Ohio]: National Aeronautics and Space Administration, Glenn Research Center, 2002.

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11

Meadows, Michael E. An evaluation of using the noise-to-signal ratio to determine the smoothing constant in exponential smoothing for inventory control. Monterey, Calif: Naval Postgraduate School, 1996.

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12

Taguchi, Genichi. Taguchi Methods: Signal-To-Noise Ratio for Quality Evaluation (Taguchi Methods Series). Irwin Professional Publishing, 1993.

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13

Matthew, Sneddon, and Langley Research Center, eds. Laboratory study of the noticeability and annoyance of sounds of low signal-to-noise ratio. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1996.

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14

Amin, Nabil Ahmed Fouad. Adaptive antenna algorithms for maximizing the signal to jamming-plus-noise ratio as solving the generalized Eigenvalue problem. 1988.

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15

S, Daugherty Elaine, Kramarchuk Ihor, and United States. National Aeronautics and Space Administration., eds. Automated measurement of the bit-error rate as a function of signal-to-noise ratio for microwave communications systems. [Washington, D.C.]: National Aeronautics and Space Administration, 1987.

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16

United States. National Aeronautics and Space Administration., ed. REAL-TIME IN SITU SIGNAL-TO-NOISE RATIO ESTIMATION FOR THE ASSESSMENT OF OPERATIONAL..., NASA/TM--2002-211703... NATIONAL AERONAUTICS AND SP. [S.l: s.n., 2003.

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17

Luxon, Linda. Disorders of hearing. Oxford University Press, 2011. http://dx.doi.org/10.1093/med/9780198569381.003.0301.

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Hearing loss is the commonest sensory disability worldwide, and the World Health Organisation has estimated that 278 million people suffer a moderate to profound hearing loss in both ears, with 80 per cent of deaf and hearing-impaired people living in low- and middle-income countries (WHO 2006). Tinnitus affects approximately 10 per cent of developed populations (Coles 1984) and of these, 5 per cent find the symptom troublesome and seek help (Davis 1995). Tinnitus and hearing loss are primary symptoms of disordered cochlear function, but may also present as a result of central auditory pathology with normal cochlear function. Pathology affecting the central auditory pathways characteristically presents as difficulty hearing in conditions of poor signal-to-noise ratio, for example, in a classroom in the presence of background noise, listening to transmitted sound, for example on the telephone or on a television, and sound localization. As a consequence of multiple relays and bilateral representation above the level of the cochlear nuclei, central auditory dysfunction does not present with hearing loss. Hearing loss and/or tinnitus, with or without associated vestibular abnormalities, will most commonly be the result of otological pathology. However, importantly for the neurologist cochlear, VIII nerve, or central auditory dysfunction may be part of the clinical presentation of a neurological disorder.
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18

Ruxton, Graeme D., William L. Allen, Thomas N. Sherratt, and Michael P. Speed. Disruptive camouflage. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199688678.003.0003.

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Disruptive camouflage involves using coloration to hinder detection or recognition of an object’s outline, or other conspicuous features of its body. This involves using coloration to create ‘false’ edges that make the ‘true’ interior and exterior edges used by visual predators to find and recognize prey less apparent. Disruptive camouflage can therefore be thought of as a manipulation of the signal-to-noise ratio that depends on features of the perceptual processing of receivers. This chapter discusses the multiple mechanisms via which disruptive camouflage is thought to influence visual processing, from edge detection, through perceptual grouping, and then on to object recognition processing. This receiver-centred approach—rather than a prey-phenotype-centred approach—aims to integrate disruption within the sensory ecology of predator–prey interactions. We then discuss the taxonomic, ecological, and behavioural correlates of disruptive camouflage strategies, work on the relationship between disruption and other forms of protective coloration, and review the development of approaches to quantifying disruption in animals.
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19

United States. National Telecommunications and Information Administration., ed. Estimation of system gain and bias using noisy observations with known noise power ratio. [Boulder, Colo.]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 2002.

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20

Estimation of system gain and bias using noisy observations with known noise power ratio. [Boulder, Colo.]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 2002.

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21

Estimation of system gain and bias using noisy observations with known noise power ratio. [Boulder, Colo.]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 2002.

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