## 1 Introduction
However, as buildings increase in size and become more complicated, the deployment of a slew of accelerometers becomes prohibitively expensive, especially about the number of sensors, the correct sensor placement, and the amount of gathered data (in terms of processing vast volumes of dynamic data), and the analytic technique [14; 15]. [PERSON] et al. [16] developed a method to extract the modal parameters of structures based on distributed measurements of dynamic strains using optical fiber sensors in a laboratory beam. The laboratory results indicated that the distributed vibration strain collected was sufficient for convergence. Hence, the first two mode shapes were accurately determined. The dynamic response characteristics of a 51-story building in downtown Los Angeles during the 2019 Mw 7.1 Ridgecrest, California, earthquake were identified from recorded response data, which was possible due to the consideration of other natural hazards, the use of system identification methods, the application of spectral analysis, and computing the coherence-phase angle spectrum [17]. The reinforced concrete (RC) building comprises a dual-core shear wall, perimeter columns, and post-tensioned flat slabs for approximately 80% of the floors. The recorded acceleration levels were trim (0.014 g at the foundation level and 0.069 g at the roof), and the maximum drift ratio computed from the recorded data was \(\sim\)0.15%, so there were no reports of observed damage. [PERSON] et al. [18] compared and analyzed several models to study the effects of different underground story modeling methodologies using 11 aftershocks with different hypocenters and magnitudes recorded for a 16-story building office located in the city of Vina del Mar, Chile. The results revealed strong agreement between the model and the actual vibration data for the models considering horizontal springs attached to the retaining walls of the subterranean stories to account for the soil-structure interaction. [PERSON] et al. [19] used a modified discrete-time Fourier transform combined with moving window technology in the time domain to examine the time-varying dynamic features of Shanghai Tower under the stimulation of normal wind and two subsequent typhoons. According to the authors, the findings can help with the wind-resistant design of significantly high-rise structures. Currently, state-of-the-art modal analyses of already built structures indicate that there is more than one method with which the dynamic properties of buildings can be identified. These methods can be grouped into two main categories: parametric identification, which establishes a simplified mathematical model with which the measured and calculated responses can be compared, and nonparametric identification, which identifies the system by means of transformations, functions, and mathematical processes [20; 21]. Some interesting works determining the dynamic response of heritage and modern structures with irregularities using system identification techniques can be consulted in the references [22; 23; 24; 25]. In these works, different approaches are used to identify the main dynamic characteristics using accelerometers installed in the studied buildings. The general objective of this research is to compare both system identification philosophies, ascertain how compatible they are, and generate MATLAB code for both approaches that automate the analysis.