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Jacob Cohen (April 20, 1923 – January 20, 1998) was an American psychologist and statistician best known for his work on statistical power and effect size, which helped to lay foundations for current statistical meta-analysis [1] [2] and the methods of estimation statistics. He gave his name to such measures as Cohen's kappa, Cohen's d, and ...
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.
For another, both Shannon’s and Fano’s coding schemes are similar in the sense that they both are efficient, but suboptimal prefix-free coding schemes with a similar performance. Shannon's (1948) method, using predefined word lengths, is called Shannon–Fano coding by Cover and Thomas, [ 4 ] Goldie and Pinch, [ 5 ] Jones and Jones, [ 6 ...
Parallel compression, also known as New York compression, is a dynamic range compression technique used in sound recording and mixing. Parallel compression, a form of upward compression , is achieved by mixing an unprocessed 'dry', or lightly compressed signal with a heavily compressed version of the same signal.
Psychological statistics is application of formulas, theorems, numbers and laws to psychology. Statistical methods for psychology include development and application statistical theory and methods for modeling psychological data. These methods include psychometrics, factor analysis, experimental designs, and Bayesian statistics. The article ...
There are two types of compression: downward and upward. Both types of compression reduce the dynamic range of an audio signal. [2] Downward compression reduces the volume of loud sounds above a certain threshold. The quiet sounds below the threshold remain unaffected. This is the most common type of compressor.
Rate–distortion theory is a major branch of information theory which provides the theoretical foundations for lossy data compression; it addresses the problem of determining the minimal number of bits per symbol, as measured by the rate R, that should be communicated over a channel, so that the source (input signal) can be approximately reconstructed at the receiver (output signal) without ...
The curve is much shallower in the high frequencies than in the low frequencies. This flattening is called upward spread of masking and is why an interfering sound masks high frequency signals much better than low frequency signals. [1] Figure B also shows that as the masker frequency increases, the masking patterns become increasingly compressed.