scholarly journals Device improvement and circuit performance evaluation of complete SiGe double gate tunnel FETs

2012 ◽  
Author(s):  
Bahniman Ghosh ◽  
Rahul Mishra
2018 ◽  
Vol 141 ◽  
pp. 31-39 ◽  
Author(s):  
Michael Graef ◽  
Fabian Hosenfeld ◽  
Fabian Horst ◽  
Atieh Farokhnejad ◽  
Franziska Hain ◽  
...  

2011 ◽  
Author(s):  
Rahul Mishra ◽  
Bahniman Ghosh ◽  
Sanjay K. Banerjee ◽  
Abdul Manaf Hashim ◽  
Vijay K. Arora

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Aihua Zhang ◽  
Yongchao Wang ◽  
Chen Chen ◽  
Hamid Reza Karimi

Focus on this issue of disturbance and fault value is inevitable in data collection about analog circuit. A novel strategy is developed for analog circuit online performance evaluation based on fuzzy learning and double weighted support vector machine (DWMK-FSVM). First, the double weighted support vector regression machine is employed to be the indirect evaluation means, relied on the college analog electronic technology experiment to evaluate analog circuit. Second, the superiority of fuzzy learning also is addressed to realize active suppression to the fault values and disturbance parameters. Moreover, the multikernel RBF is employed by support vector regression machine to realize more flexibility online such as the bandwidths tuning. Numerical results, supported by the college analog circuit experiments, adopted OTL performance eight indexes, which were obtained via precision instrument evaluation in two years to construct training set and are then to be evaluated online based on DWMK-FSVM. Simulation results presented not only highlight precision of the evaluation strategy derived here but also illustrate its great robustness.


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