S
Santo Banerjee
Researcher at Polytechnic University of Turin
Publications - 194
Citations - 3391
Santo Banerjee is an academic researcher from Polytechnic University of Turin. The author has contributed to research in topics: Chaotic & Attractor. The author has an hindex of 27, co-authored 167 publications receiving 2182 citations. Previous affiliations of Santo Banerjee include Universiti Putra Malaysia & Istituto Nazionale di Fisica Nucleare.
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Turing instabilities and spatio-temporal chaos in ratio-dependent Holling-Tanner model.
TL;DR: Numerical simulation shows that either prey or predator population do not converge to any stationary state at any future time when parameter values are taken in the Turing-Hopf domain, and reveals the fact that Hopf-bifurcation is essential for the onset of spatiotemporal chaos.
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A fractional-order chaotic system with hidden attractor and self-excited attractor and its DSP implementation
TL;DR: The definition of fractional calculus is introduced into a 3D multi-attribute chaotic system in this research, and a novel chaotic system without equilibrium points is constructed, in which the nonlinear function term in FMACS is replaced with a rare non linear function e x .
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Discrete tempered fractional calculus for new chaotic systems with short memory and image encryption
TL;DR: This study investigates a discrete analogy of tempered fractional calculus on an isolated time scale and provides a new kind of discrete fractionalculus that has useful properties and discrete Mittag–Leffler functions derived.
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Dynamical analysis of a new chaotic system: asymmetric multistability, offset boosting control and circuit realization
TL;DR: A new four-dimensional dissipative chaotic system which can produce multiple asymmetric attractors is designed and its dynamical behaviors are analyzed and the basin of attraction reveals the asymmetric multistability of the system.
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Short memory fractional differential equations for new memristor and neural network design
TL;DR: The new features of short memory fractional differential equations are used to improve the performance of networks and discussions are made about potential applications.