Direct Digital RF Technology - Challenges for Beyond Nyquist Frequency Range

2018 ◽  
Author(s):  
Noriharu Suematsu
Keyword(s):  
Nyquist Frequency ◽  
Frequency Range ◽  
Digital Rf

scholarly journals Linear Stochastic Models in Discrete and Continuous Time

Econometrics ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 35
Author(s):  
D. Stephen G. Pollock
Keyword(s):  
Moving Average ◽  
Limited Range ◽  
Autoregressive Moving Average ◽  
Nyquist Frequency ◽  
Frequency Range ◽  
White Noise Process ◽  
Moving Average Models ◽  
Data Points ◽  
Underlying Processes ◽  
Autoregressive Moving Average Models

The econometric data to which autoregressive moving-average models are commonly applied are liable to contain elements from a limited range of frequencies. If the data do not cover the full Nyquist frequency range of [0,π] radians, then severe biases can occur in estimating their parameters. The recourse should be to reconstitute the underlying continuous data trajectory and to resample it at an appropriate lesser rate. The trajectory can be derived by associating sinc fuction kernels to the data points. This suggests a model for the underlying processes. The paper describes frequency-limited linear stochastic differential equations that conform to such a model, and it compares them with equations of a model that is assumed to be driven by a white-noise process of unbounded frequencies. The means of estimating models of both varieties are described.

Seismic Time History Data Precision and Time Interval Requirement

2020 ◽  
Author(s):  
Dali Li
Keyword(s):  
Response Spectrum ◽  
Total Duration ◽  
Time History ◽  
Response Spectra ◽  
Design Parameters ◽  
Time Interval ◽  
Nyquist Frequency ◽  
Frequency Range ◽  
History Data ◽  
Data Points

Abstract This paper provides the seismic time history data precision and time interval requirement for seismic dynamic analysis. U.S.NRC SRP 3.7.1 “Seismic Design Parameters” Acceptance Criteria for Design Time Histories specifies the power spectral density Nyquist Frequency, time interval, and total duration; however, it does not have the requirement for Response Spectra. The response spectrum bandwidth is inverse-proportional to time interval of the time history. For the time interval of 0.005 seconds, the bandwidth for the response spectrum is between 0.194 Hz and 80.5 Hz; the PSD Nyquist frequency is 100 Hz. For 20.48 seconds time history, 4096 data points are required. The response spectrum between 1.28 Hz and 13.6 Hz has the peak flat magnitude value; the magnitude drops to 0.707 of the peak value from 1.28 Hz to 0.194 Hz and from 13.6 Hz to 80.5 Hz. This paper also provides the time interval requirement for various response spectrum peak flat magnitude value; i.e., the response spectrum highest flat magnitude of 27.2 Hz requires a time interval of 0.0025 seconds time history. For 20.48 seconds time history, 8192 data points are required. For CSDRS, the time interval of 0.005 seconds is adequate for the frequency range of interest between 0.36 Hz and 57.2 Hz. For HRHF, the time interval of 0.0025 seconds is required to analyze the frequency range of interest between 0.36 Hz and 114.4 Hz.

Density-based discrimination of protein and RNA in the ribosome

1992 ◽  
Vol 50 (1) ◽  
pp. 464-465
Author(s):  
Joachim Frank
Keyword(s):  
Transfer Function ◽  
Spatial Frequency ◽  
Three Dimensional ◽  
Wiener Filter ◽  
Dark Field Image ◽  
Dark Field ◽  
Frequency Range ◽  
Bright Field ◽  
Contrast Transfer Function ◽  
Pass Filter

Cryo-electron microscopy combined with single-particle reconstruction techniques has allowed us to form a three-dimensional image of the Escherichia coli ribosome.In the interior, we observe strong density variations which may be attributed to the difference in scattering density between ribosomal RNA (rRNA) and protein. This identification can only be tentative, and lacks quantitation at this stage, because of the nature of image formation by bright field phase contrast. Apart from limiting the resolution, the contrast transfer function acts as a high-pass filter which produces edge enhancement effects that can explain at least part of the observed variations. As a step toward a more quantitative analysis, it is necessary to correct the transfer function in the low-spatial-frequency range. Unfortunately, it is in that range where Fourier components unrelated to elastic bright-field imaging are found, and a Wiener-filter type restoration would lead to incorrect results. Depending upon the thickness of the ice layer, a varying contribution to the Fourier components in the low-spatial-frequency range originates from an “inelastic dark field” image. The only prospect to obtain quantitatively interpretable images (i.e., which would allow discrimination between rRNA and protein by application of a density threshold set to the average RNA scattering density may therefore lie in the use of energy-filtering microscopes.

Evaluation of Special Hearing Aids for Deaf Children

1971 ◽  
Vol 36 (4) ◽  
pp. 527-537 ◽  
Author(s):  
Norman P. Erber
Keyword(s):  
Hearing Aids ◽  
High Frequency ◽  
Hearing Aid ◽  
Low Frequency ◽  
Acoustic Stimulation ◽  
Deaf Children ◽  
Frequency Range ◽  
Frequency Limit ◽  
Unpublished Studies ◽  
Published Research

Two types of special hearing aid have been developed recently to improve the reception of speech by profoundly deaf children. In a different way, each special system provides greater low-frequency acoustic stimulation to deaf ears than does a conventional hearing aid. One of the devices extends the low-frequency limit of amplification; the other shifts high-frequency energy to a lower frequency range. In general, previous evaluations of these special hearing aids have obtained inconsistent or inconclusive results. This paper reviews most of the published research on the use of special hearing aids by deaf children, summarizes several unpublished studies, and suggests a set of guidelines for future evaluations of special and conventional amplification systems.

The influence of external conditions on sound pressure in the pistonphone at the infrasound frequency range

2020 ◽  
pp. 67-72
Author(s):  
A. V. Konkov ◽  
D. V. Golovin
Keyword(s):  
Environmental Conditions ◽  
Sound Pressure ◽  
Primary Method ◽  
Frequency Range ◽  
External Conditions ◽  
Numerical Estimations

The influence of environmental conditions on a sound pressure reproduced by the primary method in the measuring chambers of the Pistonphone in the frequency range from 1 mHz to 250 Hz is estimated. Numerical estimations of influence of environmental conditions on sound pressure in pistonphone measuring chambers are given and special requirements to system of maintenance of required external conditions are specified.

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