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Oligonucleotide microarray data distribution and normalization
Information Sciences, 2002Variations in oligonucleotide microarray probe signals that result from various factors, including differences in sample concentrations, can lead to major problems in the interpretation of data obtained from different experiments. Normalization of such signals is typically performed by procedures involving division by a constant approximately ...
Igor A. Sidorov 0001 +6 more
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BRDF Normalization of Hyperspectral Image Data
IEEE International Geoscience and Remote Sensing Symposium, 2002Monitoring vegetative areas with airborne hyperspectral sensors is being more frequently used to relate at-canopy spectral reflectance to canopy condition. Increased application of these techniques is expected with the advent of space borne hyperspectral systems (such as EO-1 Hyperion and CHRIS-PROBA).
H P White +4 more
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Normalization of Microbiome Profiling Data
2018Normalization is a term that is often used but rarely defined and poorly understood. The number of choices of normalization procedure is large-some are inappropriate or inadmissible-and all are narrowly relevant to a specific analysis that depends on both the nature of the data and the question being asked.
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Understanding a Normal Distribution of Data
Journal of Spinal Disorders & Techniques, 2015Assuming data follow a normal distribution is essential for many common statistical tests. However, what are normal data and when can we assume that a data set follows this distribution? What can be done to analyze non-normal data?
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The Value of Normal Clinical Data
Optometry and Vision Science, 2000As optometric practitioners, we all gather and then analyze large quantities of clinical data every day. We understand that some of these data will be normal (or negative), and some will be abnormal (or positive); some will even be questionable (unreliable or suspicious).
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PM&R, 2012
Although some continuous variables follow a normal, or bell-shaped, distribution, many do not. Non-normal distributions may lack symmetry, may have extreme values, or may have a flatter or steeper “dome” than a typical bell. There is nothing inherently wrong with non-normal data; some traits simply do not follow a bell curve.
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Although some continuous variables follow a normal, or bell-shaped, distribution, many do not. Non-normal distributions may lack symmetry, may have extreme values, or may have a flatter or steeper “dome” than a typical bell. There is nothing inherently wrong with non-normal data; some traits simply do not follow a bell curve.
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Normalizing Numeric Values, Min-Max Normalization, Z-Score Standardization, and Decimal ...
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2006
This book describes the principles and clinical application of Tissue Doppler Imaging and Deformation Imaging (Strain and Strain-rate Imaging). Besides practical tips on how to acquire and analyse the data, a lot of pathophysiological principle and basic myocardial physiology, related to cardiac function and deformation, is discussed in depth.
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This book describes the principles and clinical application of Tissue Doppler Imaging and Deformation Imaging (Strain and Strain-rate Imaging). Besides practical tips on how to acquire and analyse the data, a lot of pathophysiological principle and basic myocardial physiology, related to cardiac function and deformation, is discussed in depth.
openaire
Normalization Techniques in Training DNNs: Methodology, Analysis and Application
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023Jie Qin, Ling Shao, Lei Huang
exaly