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Emotion conversion is a technique for changing emotional information in input speech while maintaining linguistic information and speaker individuality [17, 18].
Emotion conversion is a technique that changes emotional information in input speech while maintaining linguistic information and speaker individuality [12, 13].
Regarding some features of neural networks such as internal dynamic of neural networks in prediction, changing information error, unnecessary information in input data, employing neural networks in the engineering field as a tool to control and observe the process performance has been increased substantially.
Overall, these results expand the repertoire of functions for digital signaling beyond increasing robustness to also facilitate multidimensional phenotype control based on temporal information in input signals.
Selective attention is normally associated with the cognitive ability to internally focus on, or be aware of, only a small sub-set of the sensory information in input, relevant to current thought or behaviour, at the expense of the rest (Duncan, 1995, 2006).
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In this equation, we have inputs, x, with the information in those inputs, dT x), on the measurement scale T, and outputs, G x), with information in those outputs, dT[G x)], on the measurement scale T. We may abbreviate this key equation of measurement and information as dT ∝ dT G which we read as the information in inputs, dT, is proportional to the information in outputs, dT[G].
Schema-level matchers utilize the information available in input schemas to find matches between schema elements.
The application of information states in input design for guaranteed parameter identification is finally considered.
It makes full use of the input image, but the high-frequency information in the input image is limited.
The indirect approach in Lasker et al. (2005, 2007) to solve P is to first convert input maps into collections of helices (which requires manual specification of appropriate map density thresholds (Jiang et al., 2001) that can be found in the input maps, ignoring any other non-helical information in the input maps.
The RANCs perform a type of fuzzy logic that has intuitive and advantageous properties, including preserving all of the information in the input signals and separating the stimulus intensity from more useful information conveyed by the stimulus, such as the identity of an odorant or spectral information about a photostimulus.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com