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In this paper, we discuss the maximum entropy properties of this kernel.
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The uniform distribution is selected because of its maximum entropy property, i.e. there is nothing assumed to be known about the origin of the impulses.
Among the various distribution described in section 2.2 above, discrete normal in section 2.2.3, discrete half normal in section 2.2.7 and discrete Laplace distribution in section 2.2.8 can also be classified as generated to preserve the maximum entropy property of their continuous counterpart.
This distribution inherits many properties of its continuous counterpart namely unimodality, infinite divisibility, maximum entropy distrbution for given absolute moment.
Local maximum entropy shape functions are used which possess a weak Kronecker-δ property.
The use of the maximum entropy method for FCS (MEMFCS) minimizes this problem by determining the number of components required based on the statistical properties of the dataset.
Similarly, the one-way street to maximum entropy is just that, it has a beginning and an end.
For the ultimate laptop, the maximum entropy corresponds to an information capacity of about 2.13 x 1031 bits -- a billion trillion times more than today's laptops.
Maximum Entropy.
bias-corrected maximum entropy.
MaxEnt ∙ (maximum entropy) [27].
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