gstar2002

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Name	gstar2002
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Problem using finite difference to solve a initial value problem

aug 1 at 0:30 David Roberts 11.9k●2●18●56

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Is is preferable to use a difference formula of higher order of accuracy for spatial derivatives to solve this IVP problem ?

finite-differences na.numerical-analysis

oct 10 at 18:17 David Ketcheson 181●4

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206

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what is the relation between vector space and the defination of vector in physics. [closed]

linear-algebra physics

may 23 12 at 15:33 gstar2002 57●5

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198

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Is there a relationship between Entropy of a fininte distrete probability distribution and the squre sum of the values of probability mass function of that distribution?

pr.probability linear-algebra

jan 8 at 16:54 R W 3,496●1●5●13

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What is the distribution of the distance between a specific word in a Text which is generated by a markov process?

stochastic-processes pr.probability

oct 29 at 23:23 Omer 1,058●3●6

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147

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why are two ranomly choosed vectors in high dimension space likely to be perpandicular to each other? [closed]

linear-algebra

nov 15 at 14:19 gstar2002 57●5

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Do the Eigenvectors find by use PCA on a set of data point, a good replacement for Random Projection when I later on use L1Magic to reconstruct the sparse vector?

compressed-sensing linear-algebra pr.probability random-matrices

dec 18 at 15:16 gstar2002 57●5

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Problem using finite difference to solve a initial value problem

Is is preferable to use a difference formula of higher order of accuracy for spatial derivatives to solve this IVP problem ?

what is the relation between vector space and the defination of vector in physics. [closed]

Is there a relationship between Entropy of a fininte distrete probability distribution and the squre sum of the values of probability mass function of that distribution?

What is the distribution of the distance between a specific word in a Text which is generated by a markov process?

why are two ranomly choosed vectors in high dimension space likely to be perpandicular to each other? [closed]

Do the Eigenvectors find by use PCA on a set of data point, a good replacement for Random Projection when I later on use L1Magic to reconstruct the sparse vector?

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