Frequency Components of Signals Producing the Upper Bound of Absolute Error Generated by the Charge Output Accelerometers

Sliding Mode Control with Perturbation Estimation (SMCPE) is a recent control routine which steers uncertain dynamic systems with disturbances to follow a desired trajectory. It eliminates the conventional requirement for the knowledge of uncertainty upper bound. A perturbation estimation scheme provides a tool for robustness. This text offers an additional robustizing mechanism: selection of time-varying sliding functions utilizing frequency shaping techniques. Frequency shaping together with sliding mode control introduces a behavior for selectively penalizing tracking errors at certain frequency ranges. This combination provides two advantages concurrently: (a) It filters out certain frequency components of the perturbations therefore eliminating the possible excitation on the unmodelled dynamics, and (b) it drives the state to the desired trajectory despite perturbations. The crucial point is that a priori knowledge of the perturbation upper bound is not necessary to eliminate the perturbation effects at the designated frequencies. Numerical examples prove the effectiveness of this novel scheme.

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A tight upper bound of the average absolute error in a constant step-size sign algorithm

IEEE Transactions on Acoustics Speech and Signal Processing ◽

10.1109/29.46562 ◽

1989 ◽

Vol 37 (11) ◽

pp. 1774-1776 ◽

Cited By ~ 21

Author(s):

E. Eweda

Keyword(s):

Upper Bound ◽

Absolute Error ◽

Average Absolute Error ◽

Step Size ◽

Sign Algorithm

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Experiments on nonlinear interactions in the transition of a free shear layer

Journal of Fluid Mechanics ◽

10.1017/s0022112073001394 ◽

1973 ◽

Vol 59 (1) ◽

pp. 1-21 ◽

Cited By ~ 47

Author(s):

Richard W. Miksad

Keyword(s):

Experimental Study ◽

Shear Layer ◽

Upper Bound ◽

Finite Amplitude ◽

Mode Competition ◽

Nonlinear Interactions ◽

Free Shear Layer ◽

Number Of Components ◽

Frequency Components ◽

Fluctuation Energy

An experimental study is made of nonlinear interactions in a laminar free shear layer. Two disturbances (f1 and f2), excited by sound, amplify and grow independently for small amplitudes. At larger amplitudes the disturbances interact to generate fluctuations of sum and difference frequencies (f2 ± f1). Harmonics and subharmonics of f1 and f2 are also generated and all fluctuations interact to generate additional fluctuations of the form (nf2/m) ± (pf1/q); n, p = 1,2,3,…, m, q = 1,2. Nonlinear mode competition suppresses the growth of f1 or f2, depending on their relative amplitudes, and contributes to finite amplitude equilibration. An upper bound on the modal integral of total u′r.m.s.2 fluctuation energy is found. Fluctuation energy tends to be distributed among all possible frequency components, and its upper bound does not increase as the number of components increases.

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Simulations of high-resolution images of amorphous silicon films

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s042482010014419x ◽

1986 ◽

Vol 44 ◽

pp. 544-545

Author(s):

G. Y. Fan ◽

J. M. Cowley

Keyword(s):

Electron Microscope ◽

High Frequency ◽

Fourier Transformation ◽

Amorphous Materials ◽

Low Frequency ◽

Chromatic Aberration ◽

Structure Information ◽

Frequency Components ◽

High Resolution Images ◽

Spatial Frequency Spectrum

It is well known that the structure information on the specimen is not always faithfully transferred through the electron microscope. Firstly, the spatial frequency spectrum is modulated by the transfer function (TF) at the focal plane. Secondly, the spectrum suffers high frequency cut-off by the aperture (or effectively damping terms such as chromatic aberration). While these do not have essential effect on imaging crystal periodicity as long as the low order Bragg spots are inside the aperture, although the contrast may be reversed, they may change the appearance of images of amorphous materials completely. Because the spectrum of amorphous materials is continuous, modulation of it emphasizes some components while weakening others. Especially the cut-off of high frequency components, which contribute to amorphous image just as strongly as low frequency components can have a fundamental effect. This can be illustrated through computer simulation. Imaging of a whitenoise object with an electron microscope without TF limitation gives Fig. 1a, which is obtained by Fourier transformation of a constant amplitude combined with random phases generated by computer.

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The proof of the upper bound in the multifractal formalism for chirps

Journal of Approximation Theory ◽

10.1016/s0021-9045(03)00010-8 ◽

2004 ◽

Vol 130 (2) ◽

pp. 99-110

Author(s):

M BENSLIMANE

Keyword(s):

Upper Bound ◽

Multifractal Formalism

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Sex Differences in Time Production Revisited

Journal of Individual Differences ◽

10.1027/1614-0001/a000059 ◽

2012 ◽

Vol 33 (1) ◽

pp. 35-42 ◽

Cited By ~ 22

Author(s):

Joseph Glicksohn ◽

Yamit Hadad

Keyword(s):

Sex Differences ◽

Individual Differences ◽

Sex Difference ◽

Absolute Error ◽

Internal Clock ◽

Target Duration ◽

Log P ◽

Men And Women ◽

Time Production ◽

T Score

Individual differences in time production should indicate differences in the rate of functioning of an internal clock, assuming the existence of such a clock. And sex differences in time production should reflect a difference in the rate of functioning of that clock between men and women. One way of approaching the data is to compute individual regressions of produced duration (P) on target duration (T), after log transformation, and to derive estimates for the intercept and the slope. One could investigate a sex difference by comparing these estimates for men and women; one could also contrast them by looking at mean log(P). Using such indices, we found a sex difference in time production, female participants having a relatively faster internal clock, making shorter time productions, and having a smaller exponent. The question is whether a sex difference in time production would be found using other methods for analyzing the data: (1) the P/T ratio; (2) an absolute discrepancy (|P-T|) score; and (3) an absolute error (|P-T|/T) score. For the P/T ratio, female participants have a lower mean ratio in comparison to the male participants. In contrast, the |P-T| and |P-T|/T indices seem to be seriously compromised by wide individual differences.

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