Consequently, the required number of frequency samples and computational complexity of decomposition reduce dramatically.
Techniques such as aerosol particle tracer sampling and computational fluid dynamics can be applied to study the performance of negative-pressure rooms and to assess how design variables can affect their performance.
Here we review the current sampling and computational approaches for inferring mutational timing and the evidence from next generation sequencing-informed data on mutational timing across all tumour types.
Examples from different sensory systems show that, in all three directions, substantial progress can be achieved once rapid online data analysis, adaptive sampling, and computational modeling are tightly integrated into experiments.
If the filter computation can be distributed among multiple robots, the number of computations performed by all the robots, i.e., the overall computational efficiency would be greater than the processing carried out by a single-robot having to carry-out both the sampling and computational tasks.
The sample size and computational cost are reduced by employing the present approach compared to direct Monte Carlo simulation (MCS).
Hence, in its simple form, it may not be suitable where there are constraints in the extent of the sample domain and computational resources.
The model was validated by comparing sample paths and computational confidence intervals with three experimental data sets of a tubular milli-reactor for polystyrene production with different configurations.
The chapter develops a comprehensive theory of the complexity of induction, which analyzes the inherent difficulty of various kinds of learning problems in terms of sample complexity and computational complexity.
Here, I describe the development and application of NMR spectroscopic techniques in my laboratory for characterizing the dynamic properties of nucleic acids that tightly integrate a broad set of NMR measurements, including residual dipolar couplings, spin relaxation, and relaxation dispersion with sample engineering and computational approaches.
