Synthetic seismograms using the state‐space approach

Geophysics ◽  
1979 ◽  
Vol 44 (5) ◽  
pp. 880-895 ◽  
Author(s):  
J. M. Mendel ◽  
N. E. Nahi ◽  
M. Chan

We develop time‐domain state‐space models for lossless layered media which are described by the wave equation and boundary conditions. We develop state‐space models for two cases: (1) source and sensor at the surface, and (2) source and sensor in the first layer. Our models are for nonequal one‐way traveltimes; hence, they are more general than most existing models of layered media which are usually for layers of equal one‐way traveltimes. A notable exception to this is the work of Wuenschel (1960); however, most of the useful results even in his paper are developed only for the uniform traveltime case. Our state‐space model treat all of the equations that describe a layered‐media system together in the time domain. Earlier approaches (e.g., Wuenschel, 1960; Robinson, 1968) recursively connect adjacent layers by means of frequency‐domain relationships. We refer to our state equations as “causal functional equations.” They actually represent a new class of equations. Why are we interested in a different class of models for what appears to be a well‐studied system? As is well known, there is a vast literature associated with systems which are described by time‐domain state‐space models. Most recent results in estimation and identification theories, for example, require a state‐space model. These time‐domain techniques have proven very beneficial outside of the geophysics field and we feel should also be beneficial in the geophysics field. In fact, our ultimate objective is to apply those theories to the layered‐media problem; but, to do so, of course, requires state‐space models—hence, this paper.

Author(s):  
J-C Lee

A hydraulic attenuator has been used in hydraulic active suspension systems of automotive vehicles to reduce high amplitude ripple pressure of a pump. The hydraulic attenuator considered in this study is so highly non-linear and of high order that the analysis in the time domain has been performed infrequently, although the frequency response analysis with the transfer matrix method was applicable. In this paper, a state space representation of the dynamics for a hydraulic attenuator is presented, utilizing the electrical analogy. The results of the experiment are compared with those of the simulation to validate the state space model proposed. The comparison reveals that the state space model proposed is practically applicable for estimating the dynamic responses of the hydraulic attenuator in the time domain.


2020 ◽  
Vol 77 (7) ◽  
pp. 1149-1162 ◽  
Author(s):  
Benjamin A. Staton ◽  
Matthew J. Catalano ◽  
Brendan M. Connors ◽  
Lewis G. Coggins ◽  
Michael L. Jones ◽  
...  

Salmon populations harvested in mixed-stock fisheries can exhibit genotypic, behavioral, and life history diversity that can lead to heterogeneity in population productivity and size. Methods to quantify this heterogeneity among populations in mixed-stock fisheries are not well-established but are critical to assessing harvest–biodiversity trade-offs when setting harvest policies. We developed an integrated, age-structured, state-space model that allows for more complete use of available data and sharing of information than simpler methods. We compared a suite of state-space models of varying structural complexity to simpler regression-based approaches and, as an example case, fitted them to data from 13 Chinook salmon (Oncorhynchus tshawytscha) populations in the Kuskokwim drainage in western Alaska. We found biological and policy conclusions were largely consistent among state-space models but differed strongly from regression-based approaches. Simulation trials illustrated our state-space models were largely unbiased with respect to spawner–recruit parameters, abundance states, and derived biological reference points, whereas the regression-based approaches showed substantial bias. These findings suggest our state-space model shows promise for informing harvest policy evaluations of harvest–biodiversity trade-offs in mixed-stock salmon fisheries.


2012 ◽  
Vol 2 (2) ◽  
pp. 190-204 ◽  
Author(s):  
Ruth King

Traditionally, state-space models are fitted to data where there is uncertainty in the observation or measurement of the system. State-space models are partitioned into an underlying system process describing the transitions of the true states of the system over time and the observation process linking the observations of the system to the true states. Open population capture–recapture–recovery data can be modelled in this framework by regarding the system process as the state of each individual observed within the study in terms of being alive or dead, and the observation process the recapture and/or recovery process. The traditional observation error of a state-space model is incorporated via the recapture/recovery probabilities being less than unity. The models can be fitted using a Bayesian data augmentation approach and in standard BUGS packages. Applying this state-space framework to such data permits additional complexities including individual heterogeneity to be fitted to the data at very little additional programming effort. We consider the efficiency of the state-space model fitting approach by considering a random effects model for capture–recapture data relating to dippers and compare different Bayesian model-fitting algorithms within WinBUGS.


Author(s):  
Tadeusz Kaczorek ◽  
Piotr Ostalczyk

AbstractIn this survey we consider two fractional-order discrete state-space models of linear systems. In both cases the crucial elements are the fundamental matrices. The difference between them is analyzed. A fundamental condition for the first state-space model is given. The investigations are illustrated by the numerical examples.


2017 ◽  
Vol 69 ◽  
pp. 428-440 ◽  
Author(s):  
Clayton R. Marqui ◽  
Douglas D. Bueno ◽  
Luiz C.S. Goes ◽  
Paulo J.P. Gonçalves

Author(s):  
Shintaroh Murakami ◽  
Hidekazu Nishimura

In this paper, modal motion of a motorcycle during braking is analyzed to clarify influence of a stabilization control system designed to the modes. A thirteen degree-of-freedom nonlinear state-space model including rider’s motion is linearized around an equilibrium point of quasi-steady state straight running with constant deceleration, and the modal analysis is carried out using the linearized state-space models. Conducting mode separation and performing simulations utilizing the linearized state-space models, the behavior of the modes including capsize, weave, and wobble modes are analyzed. The characteristic of each mode is clarified from relationships among the impulsive responses of simulations and the eigenvectors obtained from eigenanalysis. Furthermore, the influence of a motorcycle stabilization control system to each mode is analyzed from simulation results.


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