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## Mathematical Modelling and Analysis of Memristors with and without its Temperature Effects

References [1] L. O. Chua, “Memristor-the missing circuit element,” IEEE Trans.Circuit Theory, vol. CT-18, no. 5, pp. 507-519, Sep. 1971. [2] Williams, R. S. “How we found the missing memristor”. IEEE Spectr., vol. 45, pp. 28 - 35, 2008. [3] D. B. Strukov, G. S. Snider, D. R. Stewart, and R. S. Williams, “The Missing memristor found,” Nature, vol. 453, no. 7191, pp. 80-83, 2008. [4] Pazienza, G. E., J. Albo-Canals. “Teaching Memristors to EE Undergraduate Students”. IEEE Circuits and Systems

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## Rectifying memristor bridge circuit realized with human skin

Introduction A memristor ( mem ory r es istor ) is labelled as the fourth passive electrical circuit element [ 1 ] and its resistance may change with an applied electrical voltage or current. It is characterized by its state dependent Ohm’s law and its state equation that describes how the inner state changes with the applied electrical stimulus (1) v = M ( x ) i $$v=M\left( x \right)i$$ (2) d x d t = f ( x , i ) . $$\frac{dx}{dt}=f\left( x,i \right).$$ Equations ( 1 ) and ( 2 ) describe a generic memristor which is the

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## Analysis and Synthesis of Chaotic Circuits using Memristor Properties

References [1] CHUA, L. O. : Memristor - The Missing Circuit Element, IEEE Transaction Circuit Theory 18 No. 5 (1971), 507-519. [2] CHUA, L. O.-KANG, S. M. : Memristive Devices and Systems, Proceedings of the IEEE 64 No. 2 (1976), 209-223. [3] STRUKOV, D. B.-SNIDER, G. S.-STEWART, G. R.-WILLIAMS, R. S. : The Missing Memristor Found, Nature 453 (2008), 80-83. [4] ITOH, M.-CHUA, L. O. : Memristor Oscillators., International Journal of Bifurcation and Chaos 18 No. 11 (2008), 3183

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## Synchronization Analysis of Inertial Memristive Neural Networks with Time-Varying Delays

References [1]L. O. Chua Memristor-the missing circuit element, IEEE Transaction on Circuit Theory, Vol. 18, No 6, pp. 507-519, 1971 [2] D. Strukov, G. Snide and D. Stewart, The missing memristor found, Nature, Vol. 453, No. 6, pp. 80- 83, 2008. [3] R. Rakkiyappan, S. Premalatha, A. Chandrasekar and J. Cao, Stability and synchronization of innertial memristive neural networks with time delays, Cognit. Neurodyn., Vol. 10, No. 5, pp. 437-451, 2016. [4] N. Li and J. Cao, Lag synchronization of

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## Novel Fuzzy-Based Self-Adaptive Single Neuron PID Load Frequency Controller for Power System

Engineering & Computer Sciences, 19(4), pp. 513–530. Shahrokhi, M. and Zomorrodi, A., 2013. Comparison of PID controller tuning methods. Department of Chemical & Petroleum Engineering Sharif University of Technology, pp.1–2. Wang, Q., Shuang, Y. (2015). A single neuron PID control algorithm of memristor-based. Computer Information System, 14, no. 20143104, pp. 5023– 5030. Xiao-dan, et al. (2017). Application of single neuron adaptive PID approach in rolling tension control. In: 2nd International Conference on Materials

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## Fractional derivatives in electrical circuit theory – critical remarks

, no. 2, pp. 108-111 (2011). [12] Gomez-Aguilar J.F., et al., Electrical circuits described by a fractional derivative with regular Kernel , Revista Mexicana de Fisica, vol. 62 (2016). [13] Sikora R., Chady T., Łopato P., Psuj G., Theoretical Electrical Engineering , (in Polish), West Pomeranian University of Technology Publishing, Szczecin (2016). [14] Sikora R., Electromagnetic field theory , (in Polish), WNT Warszawa (1997). [15] Gomez-Aguilar J.F., Behavior characteristics of a cap-resistor, memcapacitor, and a memristor from the

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## On the Topological Properties of the Certain Neural Networks

References [1] J. Cao, R. Li, Fixed-time synchronization of delayed memristor-based recurrent neural networks, Sci. China. Inf. Sci. 60(3) (2017) 032201. [2] Y. Huo, J. B-Liu, J. Cao, Synchronization analysis of coupled calcium oscillators based on two regular coupling schemes, Neurocomputing 165 (2015) 126-132. [3] Z. Guo, J. Wang, Z. Yan, Attractivity analysis of memristor-based cellular neural networks with time-varying delays, IEEE Trans. Neural Netw. Learn. Syst. 25 (2013) 704-717. [4] J

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## Flexible Neural Network Architecture for Handwritten Signatures Recognition

and behaviors from natural language instructions,” in Experimental Robotics . Springer, 2016, pp. 373–388. [6] A. Horzyk, “How does generalization and creativity come into being in neural associative systems and how does it form human-like knowledge?” Neurocomputing , vol. 144, pp. 238–257, 2014. [7] J. A. Starzyk et al. , “Memristor crossbar architecture for synchronous neural networks,” Circuits and Systems I: Regular Papers, IEEE Transactions on , vol. 61, no. 8, pp. 2390–2401, 2014. [8] V. A. Nguyen, J. A. Starzyk, W.-B. Goh, and D. Jachyra

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## A new three-dimensional chaotic system with a hidden attractor, circuit design and application in wireless mobile robot

. VOLOS: Advances in Memristors, Memristive Devices and Systems. Springer, Berlin, Germany, 2017. [6] S. VAIDYANATHAN and C.H. LIEN: Applications of Sliding Mode Control in Science and Engineering. Springer, Berlin, Germany, 2017. [7] S. RASAPPAN and S. VAIDYANATHAN: Global chaos synchronization of WINDMI and Coullet chaotic systems by backstepping control. Far East Journal of Mathematical Sciences, 67 (2), (2012), 265–287. [8] S. VAIDYANATHAN, C.K. VOLOS and V.T. PHAM: Global chaos control of a novel nine-term chaotic system via sliding mode