VHDL-AMS model of MEMS capacitive accelerometer with delta-sigma A/D converter for behavioral level design

Holovatyy, Andriy; Teslyuk, Vasyl

doi:10.1109/cadsm.2015.7230865

Cited by 5 publications

(7 citation statements)

References 4 publications

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“…From Figure 5, it is detected that percentage of interpretability for proposed method is raised to 68% whereas the existing method 7,13,14 is at risk at initial phase of implementation whereas after certain data movements it is maximized to 51%. Even though low interpretability is achieved in existing method the difference in percentage as compared with proposed method is much higher and for large data set the intended distance will again enlarge.…”

Section: Scenariomentioning

confidence: 99%

“…In both case studies, 11,12 it is perceived that sensitivity of MEMS will increase due to dynamic characteristics in the construction phase. To reduce the sensitivity constraint geometrical parameters are designed inside the sensing elements 13 thus giving raise to input parameters to resolve in outdoor environments. All the above mentioned method has separate drawbacks and XAI provides several ways for solving all the problems.…”

Section: Conventional Models On Xai and Memsmentioning

confidence: 99%

“…From Figure 2 and Table 2, it can be observed that the respite time is varied from 10 to 200 and corresponding critical points are measured and compared with existing methods. 7,13,14 The major objective in this scenario is to reduce the number of critical points but MEMS is conniving all measured values from several directions. Thus the average value from three axes is considered as measurement point to have at least constant critical nodes.…”

Section: Scenariomentioning

confidence: 99%

“…From Figure 4, it is evident that the projected design on XAI provides low impairment percentage of 6 whereas the existing method has lost many data within a small information gain platform on an average of 44%. The most important reason for failure cases in existing method 7,13,14 is that XAI is not integrated with MEMS as only standard sensors which perceives information and passes it to the receiver is utilized. This type of process can provide quick results on evaluated parametric values but again the process will fail at insignificant gain regions.…”

Section: Scenariomentioning

confidence: 99%

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Implementation of explainable artificial intelligence in commercial communication systems using micro systems

Manoharan

Yuvaraja²,

Kuppusamy³

et al. 2023

Science Progress

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The developments in the field of artificial intelligence (AI) and decision making systems are identified as virtuous models for banking and finance sector (BFS) applications. Even though AI provides great advantage in application changes it is essential to remodel the system using explainable artificial intelligence (XAI) design system. Also the standard sensing models provides appropriate monitoring values but huge size of sensors is considered as a major drawback. Thus two diverse problems are addressed in this research work where XAI has been integrated with micro electro-mechanical systems (MEMS) for solving the problems related to BFS applications. Further the data security has been enhanced as XAI is implemented with conviction managements and real time experiments are carried out by developing a unique application by integrating new mathematical designs. To validate the effectiveness of BFS application the developed model is tested with five scenarios which includes multiple parametric arrangements with interpretability process. The tested and compared outcomes with existing models indicates that XAI and MEMS provides inordinate improvements in terms of data impairments thus increasing the transparency of the projected system to an average 96%.

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Section: Scenariomentioning

confidence: 99%

Section: Conventional Models On Xai and Memsmentioning

confidence: 99%

Section: Scenariomentioning

confidence: 99%

Section: Scenariomentioning

confidence: 99%

See 2 more Smart Citations

Implementation of explainable artificial intelligence in commercial communication systems using micro systems

Manoharan

Yuvaraja²,

Kuppusamy³

et al. 2023

Science Progress

View full text Add to dashboard Cite

show abstract

“…13.1 development environment using its libraries. Nowadays, the hardware description langauges such as VHDL, VHDL-AMS, Verilog, Verilog-AMS are widely used for creating behavioral descriptions and models of digital, analog and mixed-signal devices and systems [44,45]. The Quartus II development environment supports the entire process of designing specialized hardware from user input to FPGA programming, debugging of both the chip itself and the tools as a whole.…”

Section: Implementation Of the Specialized Hardware Components Of Neu...mentioning

confidence: 99%

Neural Network Technology for Cryptographic Protection of Data Transmission at UAV

Tsmots¹,

Teslyuk²,

Łukaszewicz³

et al. 2023

Preprint

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The neural network technology for real-time cryptographic data protection with symmetric keys (masking codes, neural network architecture and weights matrix) for unmanned aerial vehicles (UAV) onboard communication systems has been developed. It provides hardware and software implementation with high technical and operational characteristics. The development of neural network technology for real-time cryptographic data protection was performed using an integrated approach based on theoretical foundations of neural network cryptographic data protection, new algorithms and structures of neural network data encryption and decryption, modern element base with the possibility of programming for the structure, and computer-aided design of hardware and software tools. The development and implementation of the on-board system of neural network cryptographic data protection in real-time are based on the following principles: variable composition of equipment; modularity; conveyorization and spatial parallelism; specialization and adaptation of hardware and software to data encryption and decryption. The tabular-algorithmic method of calculating the scalar product has been improved, it provides fast calculation of the scalar product of input data for both fixed and floating-point by bringing to the largest common order of weights and forming tables of macro-partial products for them. Components of neural network cryptographic data encryption and decryption have been developed on the processor core supplemented by specialized scalar product calculation modules. The specialized hardware for neural network cryptographic data encryption was developed using VHDL for equipment programming in the Quartus II development environment ver. 13.1 and the appropriate libraries, and implemented on the basis of the FPGA EP3C16F484C6 Cyclone III family.

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ASIC and MEMS co-design methodology

Andryakov

Anikina

Belyaev

et al. 2016

2016 IEEE NW Russia Young Researchers in Electrical and Electronic Engineering Conference (EIConRusNW)

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VHDL-AMS model of MEMS capacitive accelerometer with delta-sigma A/D converter for behavioral level design

Cited by 5 publications

References 4 publications

Implementation of explainable artificial intelligence in commercial communication systems using micro systems

Implementation of explainable artificial intelligence in commercial communication systems using micro systems

Neural Network Technology for Cryptographic Protection of Data Transmission at UAV

ASIC and MEMS co-design methodology

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