Air quality modeling: From deterministic to stochastic approaches

Network Modeling Stochastic and Deterministic Approaches

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High Quality Down-Sampling for Deterministic Approaches to Stochastic Computing

Deterministic approaches to stochastic computing (SC) have been recently proposed to remove the random fluctuation and correlation problems of SC and so produce completely accurate results with stochastic logic. For many applications of SC, such as image processing and neural networks, completely accurate computation is not required for all input data. Decision-making on some input data can be ...

Stochastic versus Deterministic Approaches

Deterministic in contrast to stochastic modeling.

The first attempt to model a process is often a deterministic setup with differential equations. The existing stochastic influence is suppressed and hopefully negligible. However, sometimes the stochastic component is important. We demonstrate and clarify this for a growth process. The deterministic approach is given by Yn + 1 = Yn + g(Yn) or dYt = g(Yt)dt, Y0 = 1, g a positive function. The co...

Stochastic and Deterministic Approaches to Estimation in H1

This paper examines system identiication methods from frequency response data that have recently emerged under the title of`Estimation in H 1 '. We brieey review this work and examine in detail the eeects of model order on linear algorithms. This leads to a model order selection criterion which has not been previously discussed in the literature. All the existing literature in this area examine...