The organic devices suffer from mismatch and variations that are due to systematic and random fluctuations in the process and material characteristics.
Syngas is mainly a mixture of H2, CO and CH4; its composition can vary due to fluctuations in the process's conditions but can also dramatically change if the feedstock is modified like coal or biomass grades in gasification.
Clearly, this leads to fluctuations in the process of convergence to the steady-state level of congestion as well as around it, until ultimately the steady-state level is reached.
ξ ki (t) represent intracellular noises due to stochastic fluctuations in the process of degradation inside cells, and are assumed as independently and identically distributed Gaussian white noises with < ξ ki (t)> = 0 and < ξ ki (t) ξ ki (t')> = Dδ i, j (t- t'), k = 1,2.
Because of factors like insufficient detector areas, ambiguous interaction models and intrinsic fluctuations in the processes, the progress in this field has been very slow.
The winding of GaN strip is found, which can be attributed the local fluctuation in the growth process.
Emonet and Cluzel have discussed theoretically the effect of stochastic fluctuation in the chemoreceptor process on the motile behavior of bacteria [19].
Even under a flawless environment in a semiconductor manufacturing process, random variation in the process parameters can cause fluctuation in the device performance.
An integral equation, which is based on the free space Green function approach, is presented for the analysis of sound radiation from a vibrating surface into a viscous fluid by taking into account the small entropy fluctuations inherent in the process.
A large portion of the transitional states can be observed, which is due to the non-uniformity of the QDs, as well as the statistical fluctuation in the atomic processes.
But fluctuations in the manufacturing process make the required consistency hard to achieve.
