scholarly journals On the Impact of Unknown Signals on Delay, Doppler, Amplitude, and Phase Parameter Estimation

2019 ◽  
Vol 67 (2) ◽  
pp. 431-443 ◽  
Author(s):  
Yicheng Chen ◽  
Rick S. Blum
2006 ◽  
Vol 41 (1) ◽  
pp. 72-83 ◽  
Author(s):  
Zhe Zhang ◽  
Eric R. Hall

Abstract Parameter estimation and wastewater characterization are crucial for modelling of the membrane enhanced biological phosphorus removal (MEBPR) process. Prior to determining the values of a subset of kinetic and stoichiometric parameters used in ASM No. 2 (ASM2), the carbon, nitrogen and phosphorus fractions of influent wastewater at the University of British Columbia (UBC) pilot plant were characterized. It was found that the UBC wastewater contained fractions of volatile acids (SA), readily fermentable biodegradable COD (SF) and slowly biodegradable COD (XS) that fell within the ASM2 default value ranges. The contents of soluble inert COD (SI) and particulate inert COD (XI) were somewhat higher than ASM2 default values. Mixed liquor samples from pilot-scale MEBPR and conventional enhanced biological phosphorus removal (CEBPR) processes operated under parallel conditions, were then analyzed experimentally to assess the impact of operation in a membrane-assisted mode on the growth yield (YH), decay coefficient (bH) and maximum specific growth rate of heterotrophic biomass (µH). The resulting values for YH, bH and µH were slightly lower for the MEBPR train than for the CEBPR train, but the differences were not statistically significant. It is suggested that MEBPR simulation using ASM2 could be accomplished satisfactorily using parameter values determined for a conventional biological phosphorus removal process, if MEBPR parameter values are not available.


Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 387
Author(s):  
Yiting Liang ◽  
Yuanhua Zhang ◽  
Yonggang Li

A mechanistic kinetic model of cobalt–hydrogen electrochemical competition for the cobalt removal process in zinc hydrometallurgical was proposed. In addition, to overcome the parameter estimation difficulties arising from the model nonlinearities and the lack of information on the possible value ranges of parameters to be estimated, a constrained guided parameter estimation scheme was derived based on model equations and experimental data. The proposed model and the parameter estimation scheme have two advantages: (i) The model reflected for the first time the mechanism of the electrochemical competition between cobalt and hydrogen ions in the process of cobalt removal in zinc hydrometallurgy; (ii) The proposed constrained parameter estimation scheme did not depend on the information of the possible value ranges of parameters to be estimated; (iii) the constraint conditions provided in that scheme directly linked the experimental phenomenon metrics to the model parameters thereby providing deeper insights into the model parameters for model users. Numerical experiments showed that the proposed constrained parameter estimation algorithm significantly improved the estimation efficiency. Meanwhile, the proposed cobalt–hydrogen electrochemical competition model allowed for accurate simulation of the impact of hydrogen ions on cobalt removal rate as well as simulation of the trend of hydrogen ion concentration, which would be helpful for the actual cobalt removal process in zinc hydrometallurgy.


2015 ◽  
Vol 13 (01) ◽  
pp. 1450044 ◽  
Author(s):  
Jun Suzuki

We discuss a problem of parameter estimation for quantum two-level system, qubit system, in presence of unknown phase parameter. We analyze trade-off relations for mean square errors (MSEs) when estimating relevant parameters with separable measurements based on known precision bounds; the symmetric logarithmic derivative (SLD) Cramér–Rao (CR) bound and Hayashi–Gill–Massar (HGM) bound. We investigate the optimal measurement which attains the HGM bound and discuss its properties. We show that the HGM bound for relevant parameters can be attained asymptotically by using some fraction of given n quantum states to estimate the phase parameter. We also discuss the Holevo bound which can be attained asymptotically by a collective measurement.


2019 ◽  
Vol 252 ◽  
pp. 128-136 ◽  
Author(s):  
Laura Escuder-Gilabert ◽  
Yolanda Martín-Biosca ◽  
Salvador Sagrado ◽  
María José Medina-Hernández

2014 ◽  
Vol 680 ◽  
pp. 455-458
Author(s):  
Yu Han

The frequency that extreme events appear in the life is low,but once it appears,the impact will be significant; many scholars have conducted in depth research and found that statistical theory of extreme value. The theory of extreme statistics plays a more and more important role in many fields such as automatic control, assembly line etc. This paper,makes an in-depth research towards the characteristics and parameter estimation of the extreme value statistical models,as well as the application,mainly analyzes the Bayes parameter estimation method of extreme value distribution,the extreme value distribution theory and Copula function random vector model.


2011 ◽  
Vol 64 (4) ◽  
pp. 880-886 ◽  
Author(s):  
P. D. Jensen ◽  
H. Ge ◽  
D. J. Batstone

The biodegradability and bioavailability of hydrolysis-limited substrates under anaerobic (and aerobic) conditions can be represented by two key parameters – degradability (fd), or the percentage that can be effectively be destroyed during digestion, and first order hydrolysis coefficient (khyd), or the speed at which material breaks down. Biochemical methane potential (BMP) testing uses a batch test (in triplicate), and by fitting against a first order model, can fit both parameters in the same test. BMP testing is now being widely used for anaerobic process feasibility and design purposes, and standardisation efforts are ongoing. In this paper, we address a number of key issues relating to the test method and its analysis. This includes proposal of a new fitting and parameter estimation method, evaluation of the impact of inoculum to substrate ratio on fitted parameters, and comparison to performance in continuous systems. The new parameter estimation technique provides an estimate of parameter uncertainty and correlation, and is clearly more suitable than model transformation and linear regression. An inoculum volume ratio of at least 50% (2:1 on VS basis) was required on a cellulose substrate to use methane production as primary indicator, as found by comparing methane production and solubilisation of cellulose. Finally, on a typical material, waste activated sludge, the batch test was slightly conservative in terms of degradability and rate, indicating a bias in the BMP test. The test is a cost-effective and capable method to evaluate potential substrates, but it should be noted that it is generally conservative, especially if sub-optimal inoculum is used.


2020 ◽  
Author(s):  
Yvonne Ruckstuhl ◽  
Tijana Janjic

<p>We investigate the feasibility of addressing model error by perturbing and  estimating uncertain static model parameters using the localized ensemble transform Kalman filter. In particular we use the augmented state approach, where parameters are updated by observations via their correlation with observed state variables. This online approach offers a flexible, yet consistent way to better fit model variables affected by the chosen parameters to observations, while ensuring feasible model states. We show in a nearly-operational convection-permitting configuration that the prediction of clouds and precipitation with the COSMO-DE model is improved if the two dimensional roughness length parameter is estimated with the augmented state approach. Here, the targeted model error is the roughness length itself and the surface fluxes, which influence the initiation of convection. At analysis time, Gaussian noise with a specified correlation matrix is added to the roughness length to regulate the parameter spread. In the northern part of the COSMO-DE domain, where the terrain is mostly flat and assimilated surface wind measurements are dense, estimating the roughness length led to improved forecasts of up to six hours of clouds and precipitation. In the southern part of the domain, the parameter estimation was detrimental unless the correlation length scale of the Gaussian noise that is added to the roughness length is increased. The impact of the parameter estimation was found to be larger when synoptic forcing is weak and the model output is more sensitive to the roughness length.</p>


Sign in / Sign up

Export Citation Format

Share Document