In order to ease the pass-band response distortion of the matrix pre-filter,a simple approach for designing matrix spatial filter is proposed,which minimizes the sum of the k maximal distortion norm(k is the number o...In order to ease the pass-band response distortion of the matrix pre-filter,a simple approach for designing matrix spatial filter is proposed,which minimizes the sum of the k maximal distortion norm(k is the number of the constraint points)within the pass-band,while constraining the filter response within the stop-band.Considering the costly amount of calculation of the high-resolution methods,an algorithm with small amount of calculation based on matrix pre-filtering and subspace fitting using acoustic vector array(MF-VSSF)is proposed.Through joint processing of signal subspace of both pressure and particle velocity,the pre-filtering matrix and the signal subspace is decreased to M-dimensional(M is the number of array-element),hence reduces the time-consumption of the matrix pre-filter design and DOA searching.Simulation results show that,the method offers the same performance as MUSIC with pre-filtering,but has much lesser amount of calculation.Moreover,the designed prefilter can efficiently suppress the interference in the stop-band and improve the estimation and resolution performance of successive DOA estimators.展开更多
An improved single-π equivalent circuit model for on-chip inductors in the GaAs process is presented in this paper. Considering high order parasites, the model is established by comprising an improved skin effect bra...An improved single-π equivalent circuit model for on-chip inductors in the GaAs process is presented in this paper. Considering high order parasites, the model is established by comprising an improved skin effect branch and a substrate lateral coupling branch. The parameter extraction is based on an improved characteristic function approach and vector fitting method. The model has better simulation than the previous work over the measured data of 2.5r and 4.5r on-chip inductors in the GaAs process.展开更多
Physics equation-based semiconductor device modeling is accurate but time and money consuming.The need for studying new material and devices is increasing so that there has to be an efficient and accurate device model...Physics equation-based semiconductor device modeling is accurate but time and money consuming.The need for studying new material and devices is increasing so that there has to be an efficient and accurate device modeling method. In this paper, two methods based on multivariate rational regression(MRR) for device modeling are proposed. They are single-pole MRR and double-pole MRR. The two MRR methods are proved to be powerful in nonlinear curve fitting and have good numerical stability. Two methods are compared with OLS and LASSO by fitting the SMIC 40 nm MOS-FET I–V characteristic curve and the normalized mean square error of Single-pole MRR is 3.02 × 10^-8 which is 4 magnitudes less than an ordinary least square. The I–V characteristics of CNT-FET and performance indicators(noise factor, gain, power) of a low noise amplifier are also modeled by using MRR methods. The results show MRR methods are very powerful methods for semiconductor device modeling and have a strong nonlinear curve fitting ability.展开更多
基金supported by the National Natural Science Foundation of China(61201411)
文摘In order to ease the pass-band response distortion of the matrix pre-filter,a simple approach for designing matrix spatial filter is proposed,which minimizes the sum of the k maximal distortion norm(k is the number of the constraint points)within the pass-band,while constraining the filter response within the stop-band.Considering the costly amount of calculation of the high-resolution methods,an algorithm with small amount of calculation based on matrix pre-filtering and subspace fitting using acoustic vector array(MF-VSSF)is proposed.Through joint processing of signal subspace of both pressure and particle velocity,the pre-filtering matrix and the signal subspace is decreased to M-dimensional(M is the number of array-element),hence reduces the time-consumption of the matrix pre-filter design and DOA searching.Simulation results show that,the method offers the same performance as MUSIC with pre-filtering,but has much lesser amount of calculation.Moreover,the designed prefilter can efficiently suppress the interference in the stop-band and improve the estimation and resolution performance of successive DOA estimators.
基金Project supported by the National Natural Science Foundation of China(No.61674036)
文摘An improved single-π equivalent circuit model for on-chip inductors in the GaAs process is presented in this paper. Considering high order parasites, the model is established by comprising an improved skin effect branch and a substrate lateral coupling branch. The parameter extraction is based on an improved characteristic function approach and vector fitting method. The model has better simulation than the previous work over the measured data of 2.5r and 4.5r on-chip inductors in the GaAs process.
文摘Physics equation-based semiconductor device modeling is accurate but time and money consuming.The need for studying new material and devices is increasing so that there has to be an efficient and accurate device modeling method. In this paper, two methods based on multivariate rational regression(MRR) for device modeling are proposed. They are single-pole MRR and double-pole MRR. The two MRR methods are proved to be powerful in nonlinear curve fitting and have good numerical stability. Two methods are compared with OLS and LASSO by fitting the SMIC 40 nm MOS-FET I–V characteristic curve and the normalized mean square error of Single-pole MRR is 3.02 × 10^-8 which is 4 magnitudes less than an ordinary least square. The I–V characteristics of CNT-FET and performance indicators(noise factor, gain, power) of a low noise amplifier are also modeled by using MRR methods. The results show MRR methods are very powerful methods for semiconductor device modeling and have a strong nonlinear curve fitting ability.