Bio-Inspired Electromagnetic Protection Based on Neural Information Processing

doi:10.1016/S1672-6529(14)60030-5

J4 ›› 2014, Vol. 11 ›› Issue (1): 151-157.doi: 10.1016/S1672-6529(14)60030-5

• 论文 • 上一篇

收稿日期:2013-03-16 修回日期:2013-12-16 出版日期:2014-01-10 发布日期:2013-01-10

Bio-Inspired Electromagnetic Protection Based on Neural Information Processing

Xiaolong Chang, Shanghe Liu, Menghua Man, Weihua Han, Jie Chu, Liang Yuan

1. Institute of Electrostatic and Electromagnetic Protection, Mechanical Engineering College, Shijiazhuang 050003, P. R. China
2. Institute of Semiconductors, Chinese Academy of Science, Beijing 100083, P. R. China
3. Department of Information Engineering, Mechanical Engineering College, Shijiazhuang 050003, P. R. China

Received:2013-03-16 Revised:2013-12-16 Online:2014-01-10 Published:2013-01-10
Contact: Xiaolong Chang E-mail:longsmalldragon@163.com
About author:Xiaolong Chang, Shanghe Liu, Menghua Man, Weihua Han, Jie Chu, Liang Yuan

摘要/Abstract

关键词: biological nervous system, robustness, population coding, bio-inspired electromagnetic protection model, neural circuitry

Abstract:

Electronic systems are vulnerable in electromagnetic interference environment. Although many solutions are adopted to solve this problem, for example shielding, filtering and grounding, noise is still introduced into the circuit inevitably. What impresses us is the biological nervous system with a vital property of robustness in noisy environment. Some mechanisms, such as neuron population coding, degeneracy and parallel distributed processing, are believed to partly explain how the nervous system counters the noise and component failure. This paper proposes a novel concept of bio-inspired electromagnetic protec-tion making reference to the characteristic of neural information processing. A bionic model is presented here to mimic neuron populations to transform the input signal into neural pulse signal. In the proposed model, neuron provides a dynamic feedback to the adjacent one according to the concept of synaptic plasticity. A simple neural circuitry is designed to verify the rationality of the bio-inspired model for electromagnetic protection. The experiment results display that bio-inspired electromagnetic pro-tection model has more power to counter the interference and component failure.

Key words: biological nervous system, robustness, population coding, bio-inspired electromagnetic protection model, neural circuitry

Xiaolong Chang, Shanghe Liu, Menghua Man, Weihua Han, Jie Chu, Liang Yuan. [J]. J4, 2014, 11(1): 151-157.

Xiaolong Chang, Shanghe Liu, Menghua Man, Weihua Han, Jie Chu, Liang Yuan. Bio-Inspired Electromagnetic Protection Based on Neural Information Processing[J]. J4, 2014, 11(1): 151-157.

参考文献

[1] Muchaidze G, Koo J, Cai Q, Li T, Han L J, Martwick A, Wang K, Min J, Drewniak J L, Pommerenke D. Suscepti-bility scanning as a failure analysis tool for system-level electrostatic discharge problems. IEEE Transactions on Electromagnetic Compatibility, 2008, 50, 268–276.

[2] Perumalraj R, Dasaradan B S. Electromagnetic shielding effectiveness of copper core yarn knitted fabrics. Indian Journal of Fibre & Textile Research, 2009, 34, 149–154.

[3] Yeh C T, Ker M D. Study of intrinsic characteristics of ESD protection diodes for high-speed I/O applications. Microe-lectronics Reliability, 2012, 52, 1020–1030.

[4] Pommerenke D, Koo J, Muchaidze G. Finding the root cause of an ESD upset event. Proceedings of the 2006 DesignCon, Santa Clara, USA, 2006, 12–36.

[5] Han L J, Koo J. Pommerenke D, Beetner D, Carlton R. Experiment investigation of the ESD sensitivity of an 8-Bit microcontroller. Proceedings of the IEEE International Symposium on Electromagnetic Compatibility, Hawaii, USA, 2007, 1–6.

[6] Faisal A A, Selen L P, Wolpert D M. Noise in the nervous system. Nature Reviews Neuroscience, 2008, 9, 292–303.

[7] Kitano H. Biological robustness. Nature Reviews Genetics, 2004, 5, 826–837.

[8] Ay N, Flack J, Krakauer D C. Robustness and complexity co-constructed in multimodal signaling networks. Philoso-phical Transactions, 2007, 362, 441–447.

[9] Negro F, Holobar A, Farina D. Fluctuations in isometric muscle force can be described by one linear projection of low-frequency components of motor unit discharge rates. The Journal of Physiology, 2009, 587, 5925–5938.

[10] Stokes M. The spatiotemporal structure of population coding in monkey parietal cortex. The Journal of Neuroscience, 2011, 31, 1167–1169.

[11] Noppeney U, Friston K J, Price C J. Degenerate neuronal systems sustaining cognitive functions. Journal of Anatomy, 2004, 205, 433–442.

[12] Edelman G M, Gally J A. Degeneracy and complexity in biological systems. Proceedings of the National Academy of Sciences of the United States of America, USA, 2001, 98, 13763–13768.

[13] Tepper J M, Wilson C J, Koós T. Feedforward and feedback inhibition in neostriatal GABAergic spiny neurons. Brain Research Reviews, 2008, 58, 272–281.

[14] Hebb D O. The Organization of Behavior: A Neuropsy-chological Theory, Psychology Press, New York, USA, 1949.

[15] Maren S. Synaptic mechanisms of associative memory in the amygdale. Neuron, 2005, 47, 783–786.

[16] Weinberger N M. Associative representational plasticity in the auditory cortex: A synthesis of two disciplines. Learning & Memory, 2007, 14, 1–16.

[17] Feldman D E. Synaptic mechanisms for plasticity in neo-cortex. Annual Review of Neuroscience, 2009, 32, 33–35.

[18] Holtmaat A, Svoboda K. Experience-dependant structural synaptic plasticity in the mammalian brain. Nature Reviews Neuroscience, 2009, 10, 647–658.

[19] Liu S H, Yuan L, Chu J. Electromagnetic bionics—a new area of electromagnetic protection. Chinese Journal of Na-ture, 2009, 31, 1–7. (in Chinese)

[20] Liu S H, Chu J, Yuan L. Study and progress of electromag-netic bionics for electronic system. Journal of Academy Armored Force Engineering, 2009, 23, 2–6. (in Chinese)

[21] Liu S H, Man M H, Ju Z Q, Chang X L, Chu J, Yuan L. The immunity of evolvable digital circuits to ESD interference. Journal of Bionic Engineering, 2012, 9, 358–366.

[22] Eckhorn R, Reitboeck H J, Arndt M, Dicke P. Feature link-ing via synchronous among distributed assemblies: Simula-tion results from cat visual cortex. Neural Computation, 1990, 2, 293–307.

[23] Xiong Y, Han W H, Zhang Y B, Yang F H. A design of pulse coded CMOS neuron circuit. Journal of Electron Devices, 2011, 34, 286–291. (in Chinese)

[24] Lapicque L. Recherches quantitatives sur l’excitation élec-trique des nerfs traitée comme une polarization. Journal de Physiologie et de Pathologie Générale, 1907, 9, 620–635. (in French)

[25] Abbott L F. Lapicque’s introduction of the integrate-and-fire model neuron (1907). Brain Research Bulletin, 1999, 50, 303–304.

[26] Matolin D, Schreiter S, Getzlaff S, Schuffny R. An analog VLSI pulsed neural network implementation for image segmentation. Proceedings of the International Conference on Parallel Computing in Electrical Engineering (PARELEC’04), Dresden, Germany, 2004, 51–55.

[27] Xiong Y, Han W H, Zhao K, Zhang Y B, Yang F H. An analog CMOS pulse coupled neural network for image segmentation. Proceedings of 10th IEEE International Conference on Solid-State and Integrated Circuit Technol-ogy (ICSICT), Shanghai, China, 2010, 1883–1885.

Bio-Inspired Electromagnetic Protection Based on Neural Information Processing

PDF (PC)

赞

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 0

Metrics

本文评价

推荐阅读 10