Due to the carrier mobility changes with the mechanical loading and its small size, the MOSFET (metal-oxide-semiconductor field-effective-transistor) has the potential to be a suitable chip stress monitoring tool for microelectronic packaging. In this work, a complete and accurate approach to calibrate the coefficients for both types of MOSFET stress sensors under thermal and mechanical loadings was investigated quantitatively. Through data from different measurement modes on different types of MOSFET, the optimal experimental methodology was next proposed for the sensor applications on packaging stress extraction. The thermomechanical coupling coefficients for the selected experimental mode were finally extracted so that packaging stress measurements with MOSFET under elevated temperature can be performed more accurately.

Abstract:The accuracy of noise estimation is important for the performance of a speech denoising system. Most noise estimators suffer from either overestimation or underestimation on the noise level. An overestimate on noise magnitude will cause serious speech distortion for speech denoising. Conversely, a great quantity of residual noise will occur when the noise magnitude is underestimated. Accurately estimating noise magnitude is important for speech denoising. This study proposes employing variable segment length for noise tracking and variable thresholds for the determination of speech presence probability, resulting in the performance improvement for a minima-controlled-recursive-averaging (MCRA) algorithm in noise estimation. Initially, the fundamental frequency was estimated to determine whether a frame is a vowel. In the case of a vowel frame, the increment of segment lengths and the decrement of threshold for speech presence were performed which resulted in underestimating the level of noise magnitude. Accordingly, the speech distortion is reduced in denoised speech. On the contrary, the segment length decreases rapidly in noise-dominant regions. This enables the noise estimate to update quickly and the noise variation to track well, yielding interference noise being removed effectively through the process of speech denoising. Experimental results show that the proposed approach has been effective in improving the performance of the MCRA algorithm by preserving the weak vowels and consonants. The denoising performance is therefore improved.

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The purpose of this paper is to study the MOSFET stress sensor behaviors and to develop the related measurement methodology. With the newly developed technology, the piezoresistance coefficients of the MOSFET were extracted, and the strain and temperature effect induced MOSFET characteristics were obtained. The results of this study can be used to adjust the chip structure in a packaging so that the optimal packaging technology and material can be chosen, and accuracies of the numerical analysis can be verified through experimental data with the new technology studied in this paper.

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