Document Type : Review Article

Authors

1 Masters student Dept. of Electrical and Computers Engineering

2 Associate Professor of Electrical Engineering

Abstract

In this paper, a novel circuit for memristor based Infinite Impulse Response Filter (IIR) filter implementation is presented. In this research for increasing the input voltage range in sampling the analog signal, complementary switches were used instead of single-transistor switches. In addition, to increase the filter accuracy, a delayed circuit with the ability to implement high-order filters is presented. In this work, coefficients of the IIR filter were implemented by memristor; using such component could provide in-system reconfigurability. The memristor could decline receiving negative values, where IIR filter coefficients have negative values. In this research a new method for generating negative numbers as filter coefficients is presented. During running an advanced search algorithm, the memristor values ​​were set at six, seven, and eight bits of resolution; these values cause memristors have the lowest error rate in generating coefficients. All circuits were simulated by Cadence tools on TSMC 0.18 micrometer technology platform with 1.8 volt power supply. In simulation results, outputs of low/high-pass filters along with the error rate of coefficients calculated and compared to actual coefficients.

Keywords

[1] M. Rubinoff, "Analogue vs. Digital Computers-A Comparison," Proceedings of the IRE, vol. 41, no. 10, pp. 1254-1262, 1953.
[2] M. D. Hahm, E. G. Friedman, and E. L. Titlebaum, "Analog vs. Digital: A comparison of circuit implementations for low-power matched filters," in Circuits and Systems, 1996. ISCAS'96., Connecting the World., 1996 IEEE International Symposium on, 1996, vol. 4, pp. 280-283.
[3] C. R. Schlottmann and J. Hasler, "High-level modeling of analog computational elements for signal processing applications," IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 22, no. 9, pp. 1945-1953, 2014.
[4] S. W. Smith, "The scientist and engineer's guide to digital signal processing," 1997.
[5] S. M. Kay, "Fundamentals of statistical signal processing," Prentice Hall PTR, 1993.
[6] I. Boucherit and M. Guerti, "Speech analysis in cochlear implant using auditory filter bank model," in Modelling, Identification and Control (ICMIC), 2016 8th International Conference on, 2016, pp. 274-278: IEEE.
[7] T. Qu, Q. Huang, Y. Huang, L. Li, and X. Wu, "An accurate decorrelation method for parametric stereo coding," in Audio, Language and Image Processing (ICALIP), 2016 International Conference on, 2016, pp. 72-76: IEEE.
[8] R. Rehr and T. Gerkmann, "An Analysis of Adaptive Recursive Smoothing with Applications to Noise PSD Estimation," IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 25, no. 2, pp. 397-408, 2017.
[9] F. d. Lacerda, "Conversor DSB-SSB a capacitores chaveados por Transformador de Hilbert em tecnologia CMOS de 180 nm," 2017.
[10] C.-C. Tseng and S.-L. Lee, "Closed-form designs of digital fractional order Butterworth filters using discrete transforms," Signal Processing, vol. 137, pp. 80-97, 2017.
[11] A. J. Lipton, H. Fujiyoshi, and R. S. Patil, "Moving target classification and tracking from real-time video," in Applications of Computer Vision, 1998. WACV'98. Proceedings., Fourth IEEE Workshop on, 1998, pp. 8-14: IEEE.
[12] H.-Y. Wu, M. Rubinstein, E. Shih, J. Guttag, F. Durand, and W. Freeman, "Eulerian video magnification for revealing subtle changes in the world," 2012.
[13] S.-N. Mirebrahimi and F. Merrikh-Bayat, "Programmable discrete-time type I and type II FIR filter design on the memristor crossbar structure," Analog Integrated Circuits and Signal Processing, vol. 79, no. 3, pp. 529-541, 2014.
[14] F. M. Bayat, F. Alibart, L. Gao, and D. B. Strukov, "A reconfigurable FIR filter with memristor-based weights," arXiv preprint arXiv:1608.05445, 2016.
[15] B. Gold, T. G. Stockham, A. V. Oppenheim, and C. M. Rader, "Digital processing of signals," 1969.
[16] B. Widrow, "Adaptive adaline Neuron Using Chemical memistors.". 1960.
[17] H. Kim and S. P. Adhikari, "Memistor is not memristor [express letters]," IEEE Circuits and Systems Magazine, vol. 12, no. 1, pp. 75-78, 2012.
[18] R. M. Fano, L. J. Chu, and R. B. Adler, "Electromagnetic fields, energy, and forces," 1968.
[19] L. Chua, "Memristor-the missing circuit element," IEEE Transactions on circuit theory, vol. 18, no. 5, pp. 507-519, 1971.
[20] 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.
[21] S. Kvatinsky, G. Satat, N. Wald, E. G. Friedman, A. Kolodny, and U. C. Weiser, "Memristor-Based Material Implication (IMPLY) Logic: Design Principles and Methodologies," IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 22, no. 10, pp. 2054-2066, 2014.
[22] Z. Biolek, D. Biolek, and V. Biolkova, "SPICE Model of Memristor with Nonlinear Dopant Drift," Radioengineering, vol. 18, no. 2, 2009.
[23] T. Prodromakis, B. P. Peh, C. Papavassiliou, and C. Toumazou, "A versatile memristor model with nonlinear dopant kinetics," IEEE transactions on electron devices, vol. 58, no. 9, pp. 3099-3105, 2011.
[24] J. J. Yang, M. D. Pickett, X. Li, D. A. Ohlberg, D. R. Stewart, and R. S. Williams, "Memristive switching mechanism for metal/oxide/metal nanodevices," Nature nanotechnology, vol. 3, no. 7, pp. 429-433, 2008.
[25] E. Lehtonen and M. Laiho, "CNN using memristors for neighborhood connections," in Cellular Nanoscale Networks and Their Applications (CNNA), 2010 12th International Workshop on, 2010, pp. 1-4: IEEE.
[26] M. D. Pickett et al., "Switching dynamics in titanium dioxide memristive devices," Journal of Applied Physics, vol. 106, no. 7, p. 074508, 2009.
[27] H. Abdalla and M. D. Pickett, "SPICE modeling of memristors," in Circuits and Systems (ISCAS), 2011 IEEE International Symposium on, 2011, pp. 1832-1835: IEEE.
[28] C. Yakopcic, T. M. Taha, G. Subramanyam, R. E. Pino, and S. Rogers, "A memristor device model," IEEE electron device letters, vol. 32, no. 10, pp. 1436-1438, 2011.
[29] S. Kvatinsky, E. G. Friedman, A. Kolodny, and U. C. Weiser, "TEAM: Threshold adaptive memristor model," IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 60, no. 1, pp. 211-221, 2013.
[30] S. Shin, K. Kim, and S. M. Kang, "Memristor Applications for Programmable Analog ICs," IEEE Transactions on Nanotechnology, vol. 10, no. 2, pp. 266-274, 2011.
[31] Y. V. Pershin and M. D. Ventra, "Practical Approach to Programmable Analog Circuits With Memristors," IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 57, no. 8, pp. 1857-1864, 2010.
[32] T. Raja and S. Mourad, "Digital logic implementation in memristor-based crossbars," in 2009 International Conference on Communications, Circuits and Systems, 2009, pp. 939-943.
[33] J. Cong and X. Bingjun, "mrFPGA: A novel FPGA architecture with memristor-based reconfiguration," in 2011 IEEE/ACM International Symposium on Nanoscale Architectures, 2011, pp. 1-8.
[34] D. Biolek, V. Biolkova, and Z. Kolka, "Memristive systems for analog signal processing," in 2014 IEEE International Symposium on Circuits and Systems (ISCAS), 2014, pp. 2588-2591.
[35] B. Mouttet, "Proposal for Memristors in Signal Processing," in Nano-Net: Third International ICST Conference, NanoNet 2008, Boston, MA, USA, September 14-16, 2008, Revised Selected Papers, M. Cheng, Ed. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009, pp. 11-13.
[36] X. Hu, S. Duan, L. Wang, and X. Liao, "Memristive crossbar array with applications in image processing," Science China Information Sciences, journal article vol. 55, no. 2, pp. 461-472, February 01 2012.
[37] D. Soudry, D. D. Castro, A. Gal, A. Kolodny, and S. Kvatinsky, "Memristor-Based Multilayer Neural Networks With Online Gradient Descent Training," IEEE Transactions on Neural Networks and Learning Systems, vol. 26, no. 10, pp. 2408-2421, 2015.
[38] Y. V. Pershin and M. Di Ventra, "Experimental demonstration of associative memory with memristive neural networks," Neural Networks, vol. 23, no. 7, pp. 881-886, 2010/09/01/ 2010.
[39] X. Liu, Z. Zeng, and S. Wen, "Implementation of Memristive Neural Network With Full-Function Pavlov Associative Memory," IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 63, no. 9, pp. 1454-1463, 2016.
[40] A. A. Emara, M. M. Aboudina, and H. A. Fahmy, "Corrected and accurate Verilog-A for linear dopant drift model of memristors," in Circuits and Systems (MWSCAS), 2014 IEEE 57th International Midwest Symposium on, 2014, pp. 499-502: IEEE.
[41] C. E. Merkel, N. Nagpal, S. Mandalapu, and D. Kudithipudi, "Reconfigurable N-level memristor memory design," in Neural Networks (IJCNN), The 2011 International Joint Conference on, 2011, pp. 3042-3048: IEEE.
[42] F. Alibart, E. Zamanidoost, and D. B. Strukov, "Pattern classification by memristive crossbar circuits using ex situ and in situ training," Nature communications, vol. 4, p. 2 , 072, 2013.
[43] M. Prezioso, F. Merrikh-Bayat, B. Hoskins, G. Adam, K. K. Likharev, and D. B. Strukov, "Training and operation of an integrated neuromorphic network based on metal-oxide memristors," Nature, vol. 521, no. 7550, pp. 61-64, 2015.
[44] B. Razavi, Design of analog CMOS integrated circuits, Second Edition ed. MA, Boston:McGraw-Hill, 2017.
[45] A. V. Oppenheim, R. W. Schafer, and J. R. Buck, Discrete-time signal processing (2nd ed.). Prentice-Hall, Inc., 1999, p. 870.