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Increasing demand for power reduction in computer systems has led to new trends in computations and computer design including reversible computing.
This review introduces the statistical issues relating to multiple comparisons, describes the theoretical basis behind analysis of variance (ANOVA), discusses the essential differences between ANOVA and multiple t-tests, and provides an example of the computations and computer programming used in performing ANOVA.
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However, simulating the quantum computations on a standard classical computer in most cases requires exponential memory and time.
The general method to solve the transformed eigenproblem[formula]is very demanding in computation and computer storage.
The reason for creating this new computer algebra system is to make feasible mixed computation, i.e., programming software that needs both numerical computation and computer algebra.
A survey of the work for bifurcating small-amplitude limit cycles for cubic systems using symbolic computation and computer algebra systems is also elaborated in this chapter.
However, when large numbers of markers (e.g. GWAS data) are involved, the calculation of PCoA by ordinary singular value decomposition (SVD) algorithms can be quite demanding in terms of both computation and computer memory.
Specifically, the biologist of the near future will need to have a broader background in mathematics, computation and computer skills, physics, and chemistry than does the biological researcher today.
It was not until the advent of the computer and computer simulations that computation time was reduced to less than the forecast period itself.
Its proof is based on some heavy computations, and a computer algebra system may be very helpful.
Compared to the method of Zhu et al. [30], this extended method can be applied to large data sets without additional demand for computation costs and computer memory.
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