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The Weissman score is a performance metric for lossless compression applications. It was developed by Tsachy Weissman, a professor at Stanford University, and Vinith Misra, a graduate student, at the request of producers for HBO's television series Silicon Valley, a television show about a fictional tech start-up working on a data compression algorithm.
This provides great benefit to the overall compression ratio, and psychoacoustic analysis routinely leads to compressed music files that are one-tenth to one-twelfth the size of high-quality masters, but with discernibly less proportional quality loss. Such compression is a feature of nearly all modern lossy audio compression formats.
Where SR = suppression Ratio, D = responding during CS and B = responding before CS. If SR = 0, there were no responses during the CS and conditioning is strong. If SR = 1/2, the response rate did not change when the CS was presented and there is no evidence of conditioning; It would be unusual for SR to be greater than 1/2.
The recording is a series of six to seven vertex positive waves of which I through V are evaluated. These waves, labeled with Roman numerals in Jewett/Williston convention, occur in the first 10 milliseconds after onset of an auditory stimulus. The ABR is termed an exogenous response because it is dependent upon external factors. [3] [4] [5]
After two years of graduate study, he received his Ph.D. in psychology from Harvard University, where he served under Edwin Boring as assistant in psychology, from 1932 to 1934. The following year he spent studying physiology under Hallowell Davis at Harvard Medical School , and in 1935 served as a research fellow in physics at Harvard for a year.
Stevens' power law is an empirical relationship in psychophysics between an increased intensity or strength in a physical stimulus and the perceived magnitude increase in the sensation created by the stimulus.
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Compression artifacts in compressed audio typically show up as ringing, pre-echo, "birdie artifacts", drop-outs, rattling, warbling, metallic ringing, an underwater feeling, hissing, or "graininess". An example of compression artifacts in audio is applause in a relatively highly compressed audio file (e.g. 96 kbit/sec MP3).