Improved setup for studying the low-frequency noise in semiconductor devices and structures

1997 ◽  
Vol 40 (1) ◽  
pp. 85-90 ◽  
Author(s):  
S. A. Sokolik ◽  
A. M. Gulyaev ◽  
I. N. Miroshnikova
Keyword(s):  
Semiconductor Devices ◽  
Low Frequency ◽  
Frequency Noise ◽  
Low Frequency Noise

Low-frequency noise in AlN/AlGaN/GaN metal-insulator-semiconductor devices: A comparison with Schottky devices

2014 ◽  
Vol 116 (5) ◽  
pp. 054510 ◽  
Author(s):  
Son Phuong Le ◽  
Tuan Quy Nguyen ◽  
Hong-An Shih ◽  
Masahiro Kudo ◽  
Toshi-kazu Suzuki
Keyword(s):  
Semiconductor Devices ◽  
Low Frequency ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Metal Insulator ◽  
Metal Insulator Semiconductor ◽  
Schottky Devices

Adaptive algorithms for measuring low-frequency noise parameters of semiconductor devices under mass control

2020 ◽  
pp. 59-64
Author(s):  
V. А. Sergeev ◽  
S. Е. Reschikoff
Keyword(s):  
Spectral Density ◽  
Power Spectral Density ◽  
Semiconductor Devices ◽  
Low Frequency ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Filter Bandwidth ◽  
Spectrum Shape ◽  
Power Spectral ◽  
Shape Indicator

The solution of the problem of increasing the confidence and efficiency of quality control of semiconductor devices is considered. The analysis of conditions for measuring the power spectral density of low – frequency noise of semiconductor devices with a spectrum of the form (γ – the spectrum shape indicator) under mass quality control is presented. The error in measuring the power spectral density under the specified measurement conditions strongly depends on the value of the spectrum shape indicator. Adaptive algorithms for measuring low-frequency noise parameters are proposed for cases of a given limit error in measuring the power spectral density and a given time for a single measurement. The proposed algorithms include a preliminary estimation of the value of the spectrum shape indicator and subsequent measurement of the noise power spectral density at the optimal filter bandwidth. The optimal filter bandwidth is determined based on the results of a preliminary assessment of the spectrum shape indicator. For both cases, we obtained estimates of the gain in the sense of the average for the set (ensemble) of controlled products. The possibility of adaptive or cognitive adjustment of the measurement system parameters in the control process based on the results of evaluating sample averages in the training sample is discussed.

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