http://orcid.org/0000-0002-7820-2601
REFERENCES
- M. Hentrich, Methodology and Coronary Artery Disease Cure, Aug. 16 2015.
- J. Zurada, Introduction to Artificial Neural Systems. West Publishing Company, 1992.
- R. Wojtyna and T. Talaska, “Transresistance CMOS neuron for adaptive neural networks implemented in hardware,” Bull. Polish Acad. Sci., Vol. 54, no. 4, pp. 443–8, Dec. 2006.
- A. Hosseinzadeh Namin, K. Leboeuf, R. Muscedere, H. Wu, and M. Ahmadi, “Efficient hardware implementation of the hyperbolic tangent sigmoid function,” IEEE Int. Symp. on Circuits Syst. (ISCAS), pp. 2117–20, May 2009.
- S. Azizian, K. Fathi, B. Mashoufi, and F. Derogarian, “Implementation of a programmable neuron in 0.35 μm CMOS process for multi-layer ANN applications,” in EUROCON-International Conference on Computer as a Tool (EUROCON), Lisbon, Portugal, Apr. 27–29, 2011, pp. 1–4.
- G. Khodabandehloo, M. Mirhassani, and M. Ahmadi, “Analog implementation of a novel resistive-type sigmoidal neuron,” IEEE Trans. Very Large Scale Integr. VLSI Syst., Vol. 20, no. 4, pp. 750–4, Apr. 2012.
- J. Shamsi, A. Amirsoleimani, S. Mirzakuchaki, A. Ahmade, S. Alirezaee, and M. Ahmadi, “Hyperbolic tangent passive resistive-type neuron,” in IEEE International Symposium on Circuits and Systems (ISCAS), Lisbon, Portugal, Jul 30, 2015, pp. 581–4.
- G. Cauwenberghs and M. Bayoumi, Learning on Silicon: Adaptive VLSI Neural Systems. Boston: Kluwer Academic Publishers, 1999.
- I. S. Han, “Membership function circuit for neural-fuzzy hardware of analog-mixed operation based on the programmable conductance,” Int. Fuzzy Syst. Conf., pp. 1–4, Jul. 2007. IEEE.
- S. Azizian, S. Azizian, and F. Sharifian, “CMOS bulk controlled programmable neuron for artificial neural networks,” in 1st International Conference on New Research Achievements in Electrical and Computer Engineering (ICNRAECE), Tehran, Iran, May 2016.
- G. Han and E. S´anchez-Sinencio, “CMOS transconductance multipliers, a tutorial,” IEEE Trans. Circuits Syst. II, Vol. 45, no. 12, pp. 1550–63, Dec. 1998.
- E. Sackinger and W. Guggenbuhl, “A high-swing, high-impedance MOS cascode circuit,” IEEE J. Solid-State Circuits, Vol. SC-25, no. 1, pp. 289–98, Feb. 1990.
- L. J. Reed and J. Berkson, “The application of the logistic function to experimental data,” J. Phys. Chem., Vol. 33, no. 5, pp. 760–79, Jan. 1928.
- V. Pierre-François, “Notice sur la loi que la population poursuit dans son accroissement,” Corresp. Math. Phys., Vol. 10, pp. 113–21, 1838. Retrieved 3 December 2014.
- P. A. Gutierrez, C. Hervas-Martinez, and F. J. Martinez-Estudillo, “Logistic regression by means of evolutionary radial basis function neural networks,” IEEE Trans. Neural Netw., Vol. 22, no. 2, pp. 246–63, Feb. 2011.
- H. Taghavifar and A. Mardani, “Application of artificial neural networks for the prediction of traction performance parameters,” J. Saudi Soc. Agricul. Sci., Vol. 13, no. 1, pp. 35–43, 2014.
- A. Fathi, S. Azizian, and N. Sharifan. “Sensors and amplifiers: Sensor output signal amplification systems,” in Handbook of Research on Nanoelectronic Sensor Modeling and Applications. Pennsylvania: IGI Global Publishing, 2016, pp. 423–504.