Low-power high-sensitivity spike detectors for implantable VLSI neural recording microsystems

Li, Yang-Guo; Massoud, Yehia; Haider, Mohammad Rafiqul

doi:10.1007/s10470-014-0311-3

Cited by 12 publications

(3 citation statements)

References 22 publications

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“…Finally, a thick W layer is deposited by electron beam evaporation, and nano-cylindrical-shaped patterns are transferred onto the substrate. [147][148][149][150][151][152][153][154][155].…”

Section: Fabrication Frameworkmentioning

confidence: 99%

Tungsten Supported Plasmonic Nanoscale Absorber for Solar Thermal Photovoltaics Applications

Rana¹,

Khan²,

Batool³

et al. 2022

Preprint

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Current and modern photovoltaics energy systems require miniaturized, ultrathin, compact and high efficiency absorbing and optical devices. So, by keeping these challenges in mind and inspired by the artificially engineered materials, called metamaterials, a high bandwidth optical nanostructured based absorbing device is presented in this report. The design geometry of the proposed nano-absorber comprises an array of nano-circular antennas, etched on a dielectric spacer, aluminium nitride (AlN) which is coated by a thick reflecting layer of silver from the backside. Surprisingly, the design absorber offers high absorption value of above 90% across the large operational wavelengths starting from 400 to 1500 nm. The constituting nano-antennas induces plasmonic resonance features, which enables the localized surface plasmon and results in an enhanced absorption. The nanoscale absorber is also investigated under the excitation of polarization and oblique incident angles of the incoming optical light. Finally, the plasmonic metal, tungsten (W) offers high melting point so that it can sustain under the high-energy photon particles. As compared to previous published work related to plasmonic absorbers, this work provide ultra-compact geometry, easily manufactured design, super bandwidth and polarization insensitivity. So, this can be used for the applications of thermophotovoltaics and energy harvesting etc.

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“…Finally, a thick W layer is deposited by electron beam evaporation, and nano-cylindrical-shaped patterns are transferred onto the substrate. [147][148][149][150][151][152][153][154][155].…”

Section: Fabrication Frameworkmentioning

confidence: 99%

Tungsten Supported Plasmonic Nanoscale Absorber for Solar Thermal Photovoltaics Applications

Rana¹,

Khan²,

Batool³

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…Unfortunately, conversely to the square function, an implementation of the TEO based on its continuous time equation requires derivatives computing in addition to multipliers. For this reason, it is mainly computed in the digital domain with a microprocessor using its discrete time equation [20] [21] [22] even if some analog implementations using the continuous time equation can be founded for spike detection in neural recording systems [18] [19]. However, the TEO discrete time equation requires only one subtractor, two multipliers and three sample & hold circuits which can be implemented easier than derivatives operators in the analog domain.…”

Section: Introductionmentioning

confidence: 99%

Design of analog nonlinear transformations based on a Gilbert multiplier for energy detection

Vauché

Benjelloun

Assila

et al. 2021

Microelectronics Reliability

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“…Technological innovations of sensors and integrated circuit technology have resulted in wireless sensing for various applications [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. The massive scale of sensor data from an infrastructure creates a burden to the property owner to process and extract meaningful information.…”

Section: Introductionmentioning

confidence: 99%

An Oscillatory Neural Network Based Local Processing Unit for Pattern Recognition Applications

et al. 2019

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Prolific growth of sensors and sensor technology has resulted various applications in sensing, monitoring, assessment and control operations. Owing to the large number of sensing units the the aggregate data volume creates a burden to the central data processing unit. This paper demonstrates an analog computational platform using weakly coupled oscillator neural network for pattern recognition applications. The oscillator neural network (ONN) has been studied over the last couple of decades for it’s increasing computational efficiency. The coupled ONN can realize the classification and pattern recognition functionalities based on its synchronization phenomenon. The convergence time and frequency of synchronization are considered as the indicator of recognition. For hierarchical sensing, the synchronization is detected in the first layer, and then the classification is accomplished in the second layer. In this work, a Kuramoto model based frequency synchronization approach is utilized, and simulation results indicate less than 160 ms convergence time and close frequency match for a simplified pattern recognition application. An array of 10 sensors is considered to affect the coupling weights of the oscillating nodes, and demonstrate network level computation. Based on MATLAB simulations, the proposed ONN architecture can successfully detect the close-in-match pattern through synchronization, and differentiate the far-out-match pattern through loss of synchronization in the oscillating nodes.

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Low-power high-sensitivity spike detectors for implantable VLSI neural recording microsystems

Cited by 12 publications

References 22 publications

Tungsten Supported Plasmonic Nanoscale Absorber for Solar Thermal Photovoltaics Applications

Tungsten Supported Plasmonic Nanoscale Absorber for Solar Thermal Photovoltaics Applications

Design of analog nonlinear transformations based on a Gilbert multiplier for energy detection

An Oscillatory Neural Network Based Local Processing Unit for Pattern Recognition Applications

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