scholarly journals On Local Activity and Edge of Chaos in a NaMLab Memristor

2021 ◽  
Vol 15 ◽  
Author(s):  
Alon Ascoli ◽  
Ahmet S. Demirkol ◽  
Ronald Tetzlaff ◽  
Stefan Slesazeck ◽  
Thomas Mikolajick ◽  
...  

Local activity is the capability of a system to amplify infinitesimal fluctuations in energy. Complex phenomena, including the generation of action potentials in neuronal axon membranes, may never emerge in an open system unless some of its constitutive elements operate in a locally active regime. As a result, the recent discovery of solid-state volatile memory devices, which, biased through appropriate DC sources, may enter a local activity domain, and, most importantly, the associated stable yet excitable sub-domain, referred to as edge of chaos, which is where the seed of complexity is actually planted, is of great appeal to the neuromorphic engineering community. This paper applies fundamentals from the theory of local activity to an accurate model of a niobium oxide volatile resistance switching memory to derive the conditions necessary to bias the device in the local activity regime. This allows to partition the entire design parameter space into three domains, where the threshold switch is locally passive (LP), locally active but unstable, and both locally active and stable, respectively. The final part of the article is devoted to point out the extent by which the response of the volatile memristor to quasi-static excitations may differ from its dynamics under DC stress. Reporting experimental measurements, which validate the theoretical predictions, this work clearly demonstrates how invaluable is non-linear system theory for the acquirement of a comprehensive picture of the dynamics of highly non-linear devices, which is an essential prerequisite for a conscious and systematic approach to the design of robust neuromorphic electronics. Given that, as recently proved, the potassium and sodium ion channels in biological axon membranes are locally active memristors, the physical realization of novel artificial neural networks, capable to reproduce the functionalities of the human brain more closely than state-of-the-art purely CMOS hardware architectures, should not leave aside the adoption of resistance switching memories, which, under the appropriate provision of energy, are capable to amplify the small signal, such as the niobium dioxide micro-scale device from NaMLab, chosen as object of theoretical and experimental study in this work.

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Akshaykumar Naregalkar ◽  
Subbulekshmi Durairaj

Abstract A continuous stirred tank reactor (CSTR) servo and the regulatory control problem are challenging because of their highly non-linear nature, frequent changes in operating points, and frequent disturbances. System identification is one of the important steps in the CSTR model-based control design. In earlier work, a non-linear system model comprises a linear subsystem followed by static nonlinearities and represented with Laguerre filters followed by the LSSVM (least squares support vector machines). This model structure solves linear dynamics first and then associated nonlinearities. Unlike earlier works, the proposed LSSVM-L (least squares support vector machines and Laguerre filters) Hammerstein model structure solves the nonlinearities associated with the non-linear system first and then linear dynamics. Thus, the proposed Hammerstein’s model structure deals with the nonlinearities before affecting the entire system, decreasing the model complexity and providing a simple model structure. This new Hammerstein model is stable, precise, and simple to implement and provides the CSTR model with a good model fit%. Simulation studies illustrate the benefit and effectiveness of the proposed LSSVM-L Hammerstein model and its efficacy as a non-linear model predictive controller for the servo and regulatory control problem.


1990 ◽  
Vol 2 (1) ◽  
pp. 65-76 ◽  
Author(s):  
Ph. B�nilan ◽  
D. Blanchard ◽  
H. Ghidouche

2015 ◽  
Vol 735 ◽  
pp. 294-298 ◽  
Author(s):  
Wei Ying Lai ◽  
Nurfarahin Onn ◽  
Collin Howe Hing Tang ◽  
Mohamed Hussein

Hydraulic actuators are widely employed for industrial automation for its high power over weight ratio, functionality in tough operating conditions and low cost. However, the dynamics of hydraulic systems are non-linear and the system subjected to non-smooth and discontinuous non-linearities due to directional change of valve opening, friction, valve overlap and changes of hydraulic pressure acted on valve spool. Taking into account the effect of nonlinear parameter variations such as bulk modulus, compressibility of oil or viscosity of oil, fuzzy logic approach is chosen. Fuzzy control can adapt the inconstant working condition and non-linear system alongside of its robustness. For PWM controlled hydraulic component such as solenoid valve, effective approximation of the flow properties in a solenoid valve is essential. In this paper, the effect of fuzzy logic approach incorporated on pulse width modulation (PWM) controlled hydraulic system is to be investigated and experimentally verified.


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