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Relevant bibliographies by topics / Parametric fractal signals

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Academic literature on the topic 'Parametric fractal signals'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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Journal articles on the topic "Parametric fractal signals"

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Korniienko, V., O. Gerasina, D. Tymofieiev, O. Safarov, and Y. Kovalova. "Models of monitoring of self-like traffic of information and communication networks for attack detection systems." System technologies 6, no. 137 (2021): 99–113. http://dx.doi.org/10.34185/1562-9945-6-137-2021-10.

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Autoregressive, fractal and multifractal models of network self-similar traffic are con-sidered, which allow to form an adequate reference model (template) of "normal" traffic and to detect traffic anomalies in attack detection and prevention systems. Models of fractal Brownian motion and fractal Gaussian noise were considered as models of fractal motions, because they have self-similarity and long-term dependence properties that correspond to the properties of experimental data, as well as the possibility of their analytical interpretation. When evaluating and identifying processes for the im

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Cerutti, S., S. Guzzetti, R. Parola, and M. G. Signorini. "Non-Linear Dynamics of Cardiovascular Variability Signals." Methods of Information in Medicine 33, no. 01 (1994): 81–84. http://dx.doi.org/10.1055/s-0038-1634981.

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Abstract:Long-term regulation of beat-to-beat variability involves several different kinds of controls. A linear approach performed by parametric models enhances the short-term regulation of the autonomic nervous system. Some non-linear long-term regulation can be assessed by the chaotic deterministic approach applied to the beat-to-beat variability of the discrete RR-interval series, extracted from the ECG. For chaotic deterministic systems, trajectories of the state vector describe a strange attractor characterized by a fractal of dimension D. Signals are supposed to be generated by a determ

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Saxena, Shikha, and Kamal Kant Gupta. "Artificial Neural Network analysis of EEG waves in complex partial seizure patients." Nepal Journal of Neuroscience 18, no. 1 (2021): 15–21. http://dx.doi.org/10.3126/njn.v18i1.31668.

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Background: Brain dynamics associated with epilepsy remains limited. EEG-based epilepsy diagnosis and seizure detection is still in its infancy. The problem is further amplified for the design and development of automated algorithms, which requires a quantitative parametric representation of the qualitative or visual aspect of the markers. This study proposes an automatic classification system for epilepsy based on neural networks and EEG signals. Material and Method: The present study made use of EEG data from 16 controls and 16 temporal lobe epilepsy (TLE) patients in order to comparat

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Nicola, Claudiu-Ionel, and Marcel Nicola. "Improved Performance for PMSM Sensorless Control Based on the LADRC Controller, ESO-Type Observer, DO-Type Observer, and RL-TD3 Agent." Mathematics 11, no. 15 (2023): 3324. http://dx.doi.org/10.3390/math11153324.

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Starting from the fact that in sensorless control systems of the Permanent Magnet Synchronous Motor (PMSM), the load torque can have short and significant variations, this paper presents the sensorless control of a PMSM based on a Linear Adaptive Disturbance Rejection Controller (LADRC) type controller. Essentially, the successful operation of the LADRC controller to achieve PMSM rotor speed control performance depends on a good estimation of the disturbances acting on the system. Traditionally, an Extended State Observer (ESO) is used to make such an estimate. In this paper, it is proposed to

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Moreno Escobar, Jesús Jaime, Oswaldo Morales Matamoros, Erika Yolanda Aguilar del Villar, et al. "Non-Parametric Evaluation Methods of the Brain Activity of a Bottlenose Dolphin during an Assisted Therapy." Animals 11, no. 2 (2021): 417. http://dx.doi.org/10.3390/ani11020417.

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Dolphin-Assisted Therapies (DAT) are alternative therapies aimed to reduce anxiety levels, stress relief and physical benefits. This paper is focused on measuring and analyzing dolphins brain activity when DAT is taking place in order to identify if there is any differences in female dolphin’s neuronal signal when it is interacting with control or intervention subjects, performing our research in Delfiniti, Ixtapa, Mexico facilities. We designed a wireless and portable electroencephalographic single-channel signal capture sensor to acquire and monitor the brain activity of a female bottle-nose

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Lazović, Luka, Branka Jokanovic, Vesna Rubežić, Milos Radovanovic, and Ana Jovanović. "Fractal Cardioid Slot Antenna for Super Wideband Applications." Electronics 11, no. 7 (2022): 1043. http://dx.doi.org/10.3390/electronics11071043.

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A new geometry for uniplanar, ultra-wideband monopole antenna has been proposed for operations in the 1.8–30 GHz band, thanks to its fractal structure in the form of a cardioid. The antenna has extremely small dimensions at 0.21λ × 0.285λ at the lowest frequency of 1.8 GHz. A parametric analysis of the influence of certain antenna dimensions on its characteristics was performed in order to achieve the widest possible impedance bandwidth. This antenna is designed for low-cost FR-4 substrate because it is primarily intended for use in broadband energy harvesting and IoT systems, but it is also s

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Rahman, Tuan A. Z., A. As’arry, N. A. Abdul Jalil, and R. Kamil. "Dynamic Modelling of a Flexible Beam Structure Using Feedforward Neural Networks for Active Vibration Control." International Journal of Automotive and Mechanical Engineering 16, no. 1 (2019): 6263–80. http://dx.doi.org/10.15282/ijame.16.1.2019.13.0475.

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Active vibration control (AVC) techniques show promising results to reduce unwanted vibration level of flexible structures at any desired location. In this paper, the application of non-parametric identification method using feedforward neural networks (FNNs) to model a flexible beam structure for AVC system is presented. An experimental study was carried out to collect input-output dataset of a flexible beam system. The flexible beam was excited using a pseudo-random binary sequence (PRBS) force signal before acquiring the dynamic response of the system. A non-parametric modelling approach of

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Kolokolov, Yury, and Anna Monovskaya. "A Practice-Oriented Bifurcation Analysis for Pulse Energy Converters. Part 5: A View Towards the Future." International Journal of Bifurcation and Chaos 31, no. 07 (2021): 2150106. http://dx.doi.org/10.1142/s0218127421501066.

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The paper concludes the series of the research works on the interdisciplinary analytical approach (the so-called bifurcation-fractal analytics) to forecast the dynamics of pulse systems on the basis of modified bifurcation diagrams. These diagrams are intended to integrate incompatible-in-traditional-spaces images (mainly transients from the phase space and evolution pictures from the parametric space) in order to analyze whether the running transient converges towards the domain of a desirable behavior taking into account its qualitative and quantitative characteristics. The interdisciplinary

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Nicola, Marcel, Claudiu-Ionel Nicola, Dan Selișteanu, Cosmin Ionete, and Dorin Șendrescu. "Improved Performance of the Permanent Magnet Synchronous Motor Sensorless Control System Based on Direct Torque Control Strategy and Sliding Mode Control Using Fractional Order and Fractal Dimension Calculus." Applied Sciences 14, no. 19 (2024): 8816. http://dx.doi.org/10.3390/app14198816.

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This article starts from the premise that one of the global control strategies of the Permanent Magnet Synchronous Motor (PMSM), namely the Direct Torque Control (DTC) control strategy, is characterized by the fact that the internal flux and torque control loop usually uses ON–OFF controllers with hysteresis, which offer easy implementation and very short response times, but the oscillations introduced by them must be cancelled by the external speed loop controller. Typically, this is a PI speed controller, whose performance is good around global operating points and for relatively small varia

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B., S. Raghavendra, and Narayana Dutt D. "Computing Fractal Dimension of Signals using Multiresolution Box-counting Method." January 21, 2010. https://doi.org/10.5281/zenodo.1057349.

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In this paper, we have developed a method to compute fractal dimension (FD) of discrete time signals, in the time domain, by modifying the box-counting method. The size of the box is dependent on the sampling frequency of the signal. The number of boxes required to completely cover the signal are obtained at multiple time resolutions. The time resolutions are made coarse by decimating the signal. The loglog plot of total number of boxes required to cover the curve versus size of the box used appears to be a straight line, whose slope is taken as an estimate of FD of the signal. The results are

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Conference papers on the topic "Parametric fractal signals"

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Chakraborty, Monisha, and Debanjan Parbat. "Fractals, chaos and entropy analysis to obtain parametric features of surface electromyography signals during dynamic contraction of biceps muscles under varying load." In 2017 2nd International Conference for Convergence in Technology (I2CT). IEEE, 2017. http://dx.doi.org/10.1109/i2ct.2017.8226125.

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