Fixed-point error analysis of stochastic gradient adaptive lattice filters

Journal ArticleAbstract-This paper presents a theoretical analysis of the stochastic gradient adaptive lattice filter used as a linear, one-step predictor, when the effects of finite precision arithmetic are taken into account. Only the fixed-point implementation is considered here. Both the unnormalized and normalized adaptation algorithms are analyzed. Expressions for the steady-state mean-squared values of the accumulated numerical errors in the computation of the reflection coefficients and the prediction errors of different orders have been developed. The results show that the dominant term in the expressions for the mean-squared values of the numerical errors is inversely proportional to the convergence parameter. Furthermore, they indicate that the quantization errors associated with the reflection coefficients are more critical than those associated with representing the prediction error sequences. Another interesting result is that signals with high correlation among samples produce larger numerical errors in the adaptive lattice filter than signals with low correlation among samples. We present several simulation examples that show close agreement with the theoretical results. We also present some comparisons between the numerical behavior of the lattice and transversal stochastic gradient adaptive filters. The numerical results support the general belief that the gradient adaptive lattice filters have better numerical properties than their transversal counterparts, even though it is conceivable that the lattice filters can produce larger numerical errors than the transversal filters under some circumstances

Stochastic gradient adaptive filters with gradient adaptive step sizes

Journal ArticleThis paper presents two adaptive step-size gradient adaptive filters. The step sizes are changed using a gradient descent algorithm designed to minimize the squared estimation error. The first algorithm uses the same step-size sequence for all the filter coefficients whereas the second algorithm uses different step-size sequences for different adaptive filter coefficients. An analytical performance analysis of the first algorithm is also presented in the paper. Analyses and experiments indicate that (1) the algorithms have fast convergence rates and small misadjustment errors; and (2) in nonstationary environments, the algorithms tend to adjust the step sizes so as to give close to the best possible performance. Several simulation examples demonstrating the good properties of the adaptive filters are also presented in the paper

A stochastic gradient adaptive filter with gradient adaptive step size

Journal ArticleAbstract-This paper presents an adaptive step-size gradient adaptive filter. The step size of the adaptive filter is changed according to a gradient descent algorithm designed to reduce the squared estimation error during each iteration. An approximate analysis of the performance of the adaptive filter when its inputs are zero mean, white, and Gaussian and the set of optimal coefficients are time varying according to a random walk model is presented in the paper. The algorithm has very good convergence speed and low steady-state misadjustment. Furthermore, the tracking performance of these algorithms in nonstationary environments is relatively insensitive to the choice of the parameters of the adaptive filter and is very close to the best possible performance of the least mean square (LMS) algorithm for a large range of values of the step size of the step size adaptation algorithm. Several simulation examples demonstrating the good properties of the adaptive filter as well as verifying the analytical results are also presented in the paper

Information Extraction and Data Fusion for Nondestructive Evaluation of Concrete Bridge Decks

The objective of the dissertation is to improve and extend the application of impact echo (IE) and ground penetrating radar (GRP) methods in the field of concrete condition evaluation. At the beginning, an ensemble empirical mode decomposition (EEMD) approach is proposed to decompose the IE testing data into different spectral composition for defect signal extraction. The EEMD approach overcomes the challenge of extracting reflected P-wave from the IE signal that may contain strong surface wave. Then, to realize direct visualization of internal defects of concrete structures, an automated data fusion and visualization process is developed based on IE testing with source-receiver arrays. Both the simulation and experimental results demonstrate that the proposed method can effectively extract delamination regions from the IE data. In the end, the f-x variational mode decomposition (f-x VMD) method is adopted to remove the direct wave clutter of GPR Data from RC bridge decks, which are the main problem hindering the discrimination of the target of interest. The superiority and effectiveness of proposed methods are demonstrated in simulation, experiment, and field test environments over the average background subtraction method and F–K filter with dip relaxation method.Ph.D

A Significant Increase of RNAi Efficiency in Human Cells by the CMV Enhancer with a tRNAlys Promoter

RNA interference (RNAi) is the process of mRNA degradation induced by double-stranded RNA in a sequence-specific manner. Different types of promoters, such as U6, H1, tRNA, and CMV, have been used to control the inhibitory effect of RNAi expression vectors. In the present study, we constructed two shRNA expression vectors, respectively, controlled by tRNAlys and CMV enhancer-tRNAlys promoters. Compared to the vectors with tRNAlys or U6 promoter, the vector with a CMV enhancer-tRNAlys promoter silenced pokemon more efficiently on both the mRNA and the protein levels. Meanwhile, the silencing of pokemon inhibited the proliferation of MCF7 cells, but the induction of apoptosis of MCF7 cells was not observed. We conclude that the CMV enhancer-tRNAlys promoter may be a powerful tool in driving intracellular expression of shRNA which can efficiently silence targeted gene

P-Glycoprotein/MDR1 Regulates Pokemon Gene Transcription Through p53 Expression in Human Breast Cancer Cells

P-glycoprotein (Pgp), encoded by the multidrug resistance 1 (MDR1) gene, is an efflux transporter and plays an important role in pharmacokinetics. In this study, we demonstrated that the pokemon promoter activity, the pokemon mRNA and protein expression can be significantly inhibited by Pgp. Chromatin immunoprecipitation assay showed that Pgp can bind the pokemon prompter to repress pokemon transcription activity. Furthermore, Pgp regulated pokemon transcription activity through expression of p53 as seen by use of p53 siRNA transfected MCF-7 cells or p53 mutated MDA-MB-231 cells. Moreover, p53 was detected to bind with Pgp in vivo using immunoprecipitation assay. Taken together, we conclude that Pgp can regulate the expression of pokemon through the presence of p53, suggesting that Pgp is a potent regulator and may offer an effective novel target for cancer therapy

Parameters Design and Optimization of SiC MOSFET Driving Circuit with Consideration of Comprehensive Loss and Voltage Stress

In conventional parameters design, the driving circuit is usually simplified as an RLC second-order circuit, and the switching characteristics are optimized by selecting parameters, but the influence of switching characteristics on the driving circuit is not considered. In this paper, the insight mechanism for the gate-source voltage changed by overshoot and ringing caused by the high switching speed of SiC MOSFET is highlighted, and we propose an optimized design method to obtain optimal parameters of the SiC MOSFET driving circuit with consideration of parasitic parameters. Based on the double-pulse circuit, we evaluated the influence of main parameters on the gate-source voltage, including driving voltage, driving resistance, gate parasitic inductance, and stray inductance of the power circuit. A SiC-based boost PFC is constructed and tested. The test results show that the switching loss can be reduced by 7.282 W by using the proposed parameter optimization method, and the over-voltage stress of SiC MOSFET is avoided