• ETRI Journal
• /
• v.22 no.1
• /
• pp.38-46
• /
• 2000

The extraction of model parameters for embedded passive components is crucial for designing and characterizing the performance of multichip module (MCM) substrates. In this paper, a method for optimizing the extraction of these parameters using genetic algorithms is presented. The results of this method are compared with optimization using the Levenberg-Marquardt (LM) algorithm used in the HSPICE circuit modeling tool. A set of integrated resistor structures are fabricated, and their scattering parameters are measured for a range of frequencies from 45 MHz to 5 GHz. Optimal equivalent circuit models for these structures are derived from the s-parameter measurements using each algorithm. Predicted s-parameters for the optimized equivalent circuit are then obtained from HSPICE. The difference between the measured and predicted s-parameters in the frequency range of interest is used as a measure of the accuracy of the two optimization algorithms. It is determined that the LM method is extremely dependent upon the initial starting point of the parameter search and is thus prone to become trapped in local minima. This drawback is alleviated and the accuracy of the parameter values obtained is improved using genetic algorithms.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2000.07a
• /
• pp.585-591
• /
• 2000

The wavelet transform is the most recent technique for processing signals with time-varying spectra. In this paper, the wavelet transform is utilized to improved the assessment and multi-resolution analysis of acoustic emission signals generating in partial discharge. This paper especially deals with the assessment of process statistical parameter using the features extracted from the wavelet coefficients of measured acoustic emission signals in case of applied voltage 20[kv]. Since the parameter assessment using all wavelet coefficients will often turn out leads to inefficient or inaccurate results, we selected that level-3 stage of multi decomposition in discrete wavelet transform. We applied FIR(Finite Impulse Response)digital filter algorithm in discrete to suppression for random noise. The white noise be included high frequency component denoised as decomposition of discrete wavelet transform level-3. We make use of the feature extraction parameter namely, maximum value of acoustic emission signal, average value, dispersion, skewness, kurtosis, etc. The effectiveness of this new method has been verified on ability a diagnosis transformer go through feature extraction in stage of acting(the early period, the last period) .

• 한국정보디스플레이학회:학술대회논문집
• /
• 2008.10a
• /
• pp.201-204
• /
• 2008

Based on the device physics, a new I-V equation for TFTs is derived and a simple parameter extraction method is suggested. The new method gives more physically meaningful threshold voltage and mobility, and the obtained values can be directly used for the TFT device modeling.

• Journal of Korea Society of Industrial Information Systems
• /
• v.7 no.5
• /
• pp.147-153
• /
• 2002

In this paper, a substrate network model to be used with BSIM3 MOSFET model for submicron MOSFETs in giga hertz frequencies and its direct parameter extraction with physically meaningful values are proposed. The proposed substrate network model includes a conventional resistance and single inductance originated from ring-type substrate contacts around active devices. Model parameters are extracted from S-parameter data measured from common-bulk configured MOS transistors with floating gate and use where needed without any optimization process. The proposed modeling technique has been applied to various-sized MOS transistors. The substrate model has been validated for frequency up to 300Hz.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.16 no.11
• /
• pp.1132-1142
• /
• 1991

This paper proposed a method of feature parameter extraction for shape information analysis of moving object. In the 2-D plane, moving object are extracted by the difference method. Feature parameters of moving object are chosen area, perimeter, a/p ratio, vertex, x/y ratio. We changed brightness variation from the range of 600Lux to the 1400Lux and then determined Permissible Error range of feature parameter due to the brightness variation. So as to verify the validity of proposed method, experiment are performed with a toy car and it's results showed that decision error was less than 6%.

• Proceedings of the IEEK Conference
• /
• 2003.11a
• /
• pp.49-52
• /
• 2003

In this paper, we propose new speech feature parameter using NMf(Non-Negative Matrix Factorization). NMF can represent multi-dimensional data based on effective dimensional reduction through matrix factorization under the non-negativity constraint, and reduced data present parts-based features of input data. In this paper, we verify about usefulness of NMF algorithm for speech feature extraction applying feature parameter that is got using NMF in Mel-scaled filter bank output. According to recognition experiment result, we could confirm that proposal feature parameter is superior in recognition performance than MFCC(mel frequency cepstral coefficient) that is used generally.

• Proceedings of the Korea Society of Information Technology Applications Conference
• /
• 2002.11a
• /
• pp.363-370
• /
• 2002

A substrate network model characterizing substrate effect of submicron MOS transistors for RF operation and its parameter extraction with physically meaningful values are presented. The proposed substrate network model includes a single resistance and inductance originated from ring-type substrate contacts around active devices. Model parameters are extracted from S-parameter data measured from common-bulk configured MOS transistors with floating gate and use where needed with out any optimization. The proposed modeling technique has been applied to various-sized MOS transistors. Excellent agreement the measurement data and the simulation results using extracted substrate network model up to 30GHz.

• Journal of the Korean Institute of Telematics and Electronics D
• /
• v.34D no.12
• /
• pp.54-61
• /
• 1997

An accurate extraction technique is developed to determine full euqivalent circuit parameters of Si MOSFETs using 1 set of measured S-parametes without complicated optimization process. This technique is based on the use of anlytic Z-parameters experessions for resistances and inductances and the Y-parameter ones for ntrinsic parameters. This accuracy is proved over the wide range of gate voltage by observing good agreement between measured and fitted Z-parameter equations and frequency-independent response of the extracted intrinsic parameters. Using this technique, gate voltage-dependencies of model parameters are obained in the saturation region and these results show the similar behavior to the short-channel effects expected from the device theory.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2002.11a
• /
• pp.363-370
• /
• 2002

A substrate network model characterizing substrate effect of submicron MOS transistors for RF operation and its parameter extraction with physically meaningful values are presented. The proposed substrate network model includes a single resistance and inductance originated from ring-type substrate contacts around active devices. Model parameters are extracted from S-parameter data measured from common-bulk configured MOS transistors with floating gate and use where needed with out any optimization. The proposed modeling technique has been applied to various-sized MOS transistors. Excellent agreement the measurement data and the simulation results using extracted substrate network model up to 30㎓

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.9
• /
• pp.1769-1774
• /
• 2009

An algorithm for extracting the BJT DC model parameter values for SPICE model is proposed. The nonlinear optimization method for analyzing the device I-V data using the Levenberg-Marquardt algorithm is proposed and the method for calculating initial conditions of model parameters to improve the convergence characteristics is proposed. The base current and collector current obtained from the proposed method shows the root mean square error of 6.04% compared with the measured data of the PNP BJT named 2SA1980.