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In another usage in statistics, normalization refers to the creation of shifted and scaled versions of statistics, where the intention is that these normalized values allow the comparison of corresponding normalized values for different datasets in a way that eliminates the effects of certain gross influences, as in an anomaly time series. Some ...
Dialnorm is an integer value with range 1 to 31 corresponding to a playback gain of −30 to 0 dB (unity) respectively. Higher values afford more headroom and are appropriate for dynamic material such as an action film. Dolby recommends that the dialnorm value be determined by measurement of average dialog level in the program.
This is the Vandermonde matrix for the roots of unity, up to the normalization factor. Note that the normalization factor in front of the sum ( /) and the sign of the exponent in ω are merely conventions, and differ in some treatments. All of the following discussion applies regardless of the convention, with at most minor adjustments.
Feature scaling is a method used to normalize the range of independent variables or features of data. In data processing, it is also known as data normalization and is generally performed during the data preprocessing step.
Normalization in quantum mechanics, see Wave function § Normalization condition and normalized solution; Normalization (sociology) or social normalization, the process through which ideas and behaviors that may fall outside of social norms come to be regarded as "normal"
The Legendre polynomials are characterized by orthogonality with respect to the uniform measure on the interval [−1, 1] and the fact that they are normalized so that their value at 1 is 1. The constant by which one multiplies a polynomial so its value at 1 is a normalizing constant.
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The softmax function, also known as softargmax [1]: 184 or normalized exponential function, [2]: 198 converts a vector of K real numbers into a probability distribution of K possible outcomes. It is a generalization of the logistic function to multiple dimensions, and is used in multinomial logistic regression .