16eeb1d7-1bd7-432c-998e-4520a224e9da20211118072259741naun:naunmdt@crossref.orgMDT DepositInternational Journal of Circuits, Systems and Signal Processing1998-446410.46300/9106http://www.naun.org/cms.action?id=3029118202111820211510.46300/9106.2021.15https://naun.org/cms.action?id=23283An Application of the Z-Transform in Extracting the Density Regulation from the Periodic Output of an Age-Structured Population ModelMichelle EllisErasmusDepartment of Mathematical and Physical Sciences Central University of Technology Bloemfontein 9300, South AfricaThe application of the Z-transform, a manipulation tool from the discrete signal processing (DSP) toolbox, on an ecological model was motivated by the mathematical similarities between an age-structured fish population model with a non linear density regulation and a linear time invariant (LTI) control system. Both models include a switching mechanism in regulating stock/signal throughput in accordance with a given density limitation/set value and both models can be expressed in terms of a negative feedback loop difference equations (Getz & Haight,1989; °Astr¨om & Murray, 2008). In the fish model, the switching mechanism is a density regulated stock-recruitment (SR) function which models the strategies implemented by the population in keeping the vulnerable egg-larvaejuvenile densities within an environmental limitation thereof (Subbey et al, 2014). A switching mechanism is also present in control engineering, for example, in the mechanism associated with cruise control in cars which keeps traveling speed close to a chosen set value midst varying weather and road conditions (Antsaklis and Gao, 2005). In both cases, the choosing of the control action and the tuning of its parameters requires careful consideration to avoid failures such as incorrectly timed switching actions in a control plant (see Kuphaldt (2019)) and errors in estimating total allowable catch (TAC) in the fishing industry (see Borlestean et al (2015), Skagen et al (2013) and Taboadai and R. Anadn (2016)). The Z-transform has proven itself useful in tuning LTI controlmodels for a desired control action (see Orfanidis, (2010) and Smith, (1999)) and it is on this account that its application was extended to the ecological model in pursuit of a more efficient way of estimating SR parameters to simulate an already existing output. It was however found that it could not be used for parameter tuning but rather for the extraction of the SR component hidden in the output together with components resulting from the age structure itself. Such an extraction can greatly assist in the mathematical identification of the SR, reducing the complexity of its choosing as there are many different types used in the fishing industry such as the classic Beverton-Holt model, the Ricker model and Shepherd model (Myers, 2001; Iles, 1994; Shepherd, 1982). It can also be used to monitor changes in the SR over time which can indicate the presence of strategy evolution (Apaloo et al, 2009; Br¨annstr¨om et al, 2013). In 1998 Schoombie and Getz investigated the latter by subjecting the Shepherd SR to strategy optimization with regards to a parameter associated with population interventions in regulating recruitment throughput and it is because of this versatility that the Shepherd SR is chosen for the intended extraction. In true control style, Simulink, a graphic environment for designing control simulations, is used to visualize the production of the output as well as the extraction of the SR from it. This paper showcases the versatility of the Z transform and the possibilities and unexpected finds when applied to similar systems designed to regulate signals or, in this case, recruitment densities.111820211118202116761686181https://www.naun.org/main/NAUN/circuitssystemssignal/2021/d682005-181(2021).pdf10.46300/9106.2021.15.181https://www.naun.org/main/NAUN/circuitssystemssignal/2021/d682005-181(2021).pdfK. J. ˚Astr¨om and R. M. Murray, Feedback systems: an introduction for scientists and engineers.Princeton University Press, ISBN-13: 978-0- 691-13576-2, Chapter 1, 2008. P. Antsaklis and Z. Gao, The electronics engineer’s handbook. McGraw-Hill, Fifth edition, Section 19, 19.1-19.30, 2005. J. Apaloo and J. S. Brown and T. L Vincent, Evolutionary game theory: ESS, convergence stability, and NIS. Evolutionary Ecology Research, 11, 489- 515, 2009. R. J. H. Beverton, and S. J. Holt, On the dynamics of exploited fish populations. 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