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Auswahl der wissenschaftlichen Literatur zum Thema „Non ideal devices“

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Zeitschriftenartikel zum Thema "Non ideal devices"

1

West, Brian R., and David V. Plant. "Optimization of non-ideal multimode interference devices." Optics Communications 279, no. 1 (2007): 72–78. http://dx.doi.org/10.1016/j.optcom.2007.06.056.

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2

Schroeder, D., and U. Witkowski. "Simulation of semiconductor devices with non-ideal metallic contacts." IEEE Transactions on Electron Devices 44, no. 4 (1997): 679–81. http://dx.doi.org/10.1109/16.563375.

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Natan, A., L. Kronik, H. Haick, and R. T. Tung. "Electrostatic Properties of Ideal and Non-ideal Polar Organic Monolayers: Implications for Electronic Devices." Advanced Materials 19, no. 23 (2007): 4103–17. http://dx.doi.org/10.1002/adma.200701681.

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4

Davey, K. "Optimization shows Halbach arrays to be non-ideal for induction devices." IEEE Transactions on Magnetics 36, no. 4 (2000): 1035–38. http://dx.doi.org/10.1109/20.877618.

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5

Lee, Jae-Eun, Chuljun Lee, Dong-Wook Kim, Daeseok Lee, and Young-Ho Seo. "An On-Chip Learning Method for Neuromorphic Systems Based on Non-Ideal Synapse Devices." Electronics 9, no. 11 (2020): 1946. http://dx.doi.org/10.3390/electronics9111946.

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In this paper, we propose an on-chip learning method that can overcome the poor characteristics of pre-developed practical synaptic devices, thereby increasing the accuracy of the neural network based on the neuromorphic system. The fabricated synaptic devices, based on Pr1−xCaxMnO3, LiCoO2, and TiOx, inherently suffer from undesirable characteristics, such as nonlinearity, discontinuities, and asymmetric conductance responses, which degrade the neuromorphic system performance. To address these limitations, we have proposed a conductance-based linear weighted quantization method, which controls conductance changes, and trained a neural network to predict the handwritten digits from the standard database MNIST. Furthermore, we quantitatively considered the non-ideal case, to ensure reliability by limiting the conductance level to that which synaptic devices can practically accept. Based on this proposed learning method, we significantly improved the neuromorphic system, without any hardware modifications to the synaptic devices or neuromorphic systems. Thus, the results emphatically show that, even for devices with poor synaptic characteristics, the neuromorphic system performance can be improved.
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6

Nguyen, Quoc-Minh, Nan-Hui Chiang, Huu-Duy Tran, Hung-Yu Wang, and Li-Te Yin. "Symbolic nodal analysis of conveyor-based circuits considering non-ideal active devices." AEU - International Journal of Electronics and Communications 69, no. 11 (2015): 1635–40. http://dx.doi.org/10.1016/j.aeue.2015.07.014.

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Gubicza, Agnes, Miklós Csontos, András Halbritter, and György Mihály. "Non-exponential resistive switching in Ag2S memristors: a key to nanometer-scale non-volatile memory devices." Nanoscale 7, no. 10 (2015): 4394–99. http://dx.doi.org/10.1039/c5nr00399g.

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English, Lisa B. "In Pursuit of an Ideal – A Perspective on Non-Invasive Continuous Glucose Monitoring." European Endocrinology 8, no. 1 (2010): 18. http://dx.doi.org/10.17925/ee.2012.08.01.18.

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Diabetes is one of the most common non-communicable diseases globally, and is the fourth or fifth leading cause of death in many countries. Medical technology for the management of diabetes has advanced steadily since the discovery of insulin in the early 20th century. Today, individuals with diabetes benefit from home-use blood glucose meters, continuous insulin pumps and, most recently, continuous glucose monitoring (CGM). Numerous studies have shown that frequent use of real-time CGM can improve glycaemic control with reduced risk of hypoglycaemia. However, current CGM devices have not been wholeheartedly embraced, limiting their potential. A CGM device that is accurate, non-invasive, pain-free and non-intrusive to daily activities could drive increased adoption and use of CGM, potentially improving health and quality of life for many individuals living with diabetes.
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9

Alim, Mohammad A., Sanjida Khanam, and Martin A. Seitz. "Immittance Spectroscopy of Smart Components and Novel Devices." Active and Passive Electronic Components 16, no. 3-4 (1994): 153–70. http://dx.doi.org/10.1155/1994/25820.

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AC small-signal immittance spectroscopy is employed as a viable tool to demonstrate electrical characterization, performance improvement, and quality assurance issues of smart materials-based components and novel devices. The variation in the ac response, complemented via dc measurements within a range of tolerating temperature, delineates competing phenomena occurring in the microstructures of these engineering material systems. The results are presented in a generic manner with possible explanations on the mechanisms for two selected Debye-like (nearly ideal) and non-Debye (non-ideal) low-capacitance resistors. This spectroscopic approach allows systematic development of a representative equivalent circuit, considered to be the characteristic of the devices and components, for specific applications.
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10

Halverson, Adam F., and Loucas Tsakalakos. "Junction Operation of GaAs Wire Array Solar Cells." MRS Proceedings 1493 (2013): 253–59. http://dx.doi.org/10.1557/opl.2013.403.

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ABSTRACTWire array solar cells benefit from enhanced coupling of light into the active area of the device, significantly decreased collection lengths due to radial charge separation and collection, and easier access to grain boundaries for passivation which may enable future deposition on non-wafer substrates. We report on an analysis of the junction operation of wire array based GaAs solar cells through temperature and light intensity dependent current-voltage analysis and compare these data to matched planar devices. We see evidence of non-ideal recombination pathways indicated by activation energies for generation-recombination that are significantly less than the band gap of GaAs. We observe voltage shifts in the wire array devices at low temperature and high light intensity that we posit can be explained by electron accumulation in the window layers of the devices.
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