Band-pass filters with steep skirt selectivity.
Band pass filters with low passband insertion loss and steep skirt selectivity by use of resonators with moderate Q values
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Band pass filters with low passband insertion loss and steep skirt selectivity by use of resonators with moderate Q values
Preflight calibration and matching of solar cells for band pass filter experiment to evaluate cell performance in space
High performance active RC band pass filter design providing for independent adjustment of poles
Active RC bandpass filter for space fluxgate magnetometer, using state variable synthesis
The sol-mean atmospheric pressures measured at the two Viking landers exhibit fluctuations ranging in period from seasonal to a few days. The time series are highly nonstationary, which severely limits standard methods such as power-spectrum analysis. Advantage is taken of the rather precise annual periodicity of these data to design sharp numerical filters and use them to split the series at each lander into six time series, each containing oscillations associated with a discrete frequency band. This analysis reveals 2- to 4-sol waves during the cold seasons at both landers, and 8-sol waves during the spring at Lander 2, confirming previous results from spectral analysis. As previously predicted, high-frequency waves appear suppressed during the second dust storm. Certain low-frequency signals, probably associated with the global dust storms, are detected and demonstrated to be significant for the first time.
A nonlinear analysis of a multifilter phase-lockloop (MPLL) by using the method of harmonic balance is presented. The particular MPLL considered has a low-pass filter and a band-pass filter in parallel. An analytic expression for the relationship between the input signal phase deviation and the phase error is determined for sinusoidal FM in the absence of noise. The expression is used to determine bounds on the proper operating region for the MPLL and to investigate the jump phenomenon previously observed. From these results the proper modulation index, modulating frequency, etc. used for the design of a MPLL are determined. Data for the loop unlock boundary obtained from the theoretical expression are compared to data obtained from analog computer simulations of the MPLL.
An approach toward low-pass, high-pass and band-pass filtering is presented. Convolution coefficients possessing the filtering speed associated with a moving smoothing average without suffering a loss of resolution are discussed. Resolution was retained because the coefficients represented the equivalance of applying high order two-dimensional regression calculations to an image without considering the time-consuming summations associated with the usual normal equations. The smoothing (low-pass) and roughing (high-pass) aspects of the filters are a result of being derived from regression theory. The coefficients are universal integer valves completely described by filter size and surface order, and possess a number of symmetry properties. Double convolution lead to a single set of coefficients with an expanded mask which can yield band-pass filtering and the surface normal. For low order surfaces (0,1), the two-dimensional convolute integers were equivalent to a moving smoothing average.
We use seismic waves that pass through the hypocentral region of the 2016 M6.5 Norcia earthquake together with Deep Learning (DL) to distinguish between foreshocks, aftershocks and time-to-failure (TTF). Binary and N-class models defined by TTF correctly identify seismograms in test with > 90% accuracy. We use raw seismic records as input to a 7 layer CNN model to perform the classification. Here we show that DL models successfully distinguish seismic waves pre/post mainshock in accord with lab and theoretical expectations of progressive changes in crack density prior to abrupt change at failure and gradual postseismic recovery. Performance is lower for band-pass filtered seismograms (below 10 Hz) suggesting that DL models learn from the evolution of subtle changes in elastic wave attenuation. Tests to verify that our results indeed provide a proxy for fault properties included DL models trained with the wrong mainshock time and those using seismic waves far from the Norcia mainshock; both show degraded performance. Our results demonstrate that DL models have the potential to track the evolution of fault zone properties during the seismic cycle. If this result is generalizable it could improve earthquake early warning and seismic hazard analysis.
For analysis of the data obtained from the cross beam systems it was deemed desirable to compute the auto- and cross-correlation functions by both digital and analog methods to provide a cross-check of the analysis methods and an indication as to which of the two methods would be most suitable for routine use in the analysis of such data. It is the purpose of this appendix to provide a concise description of the equipment and procedures used for the electronic analog analysis of the cross beam data. A block diagram showing the signal processing and computation set-up used for most of the analog data analysis is provided. The data obtained at the field test sites were recorded on magnetic tape using wide-band FM recording techniques. The data as recorded were band-pass filtered by electronic signal processing in the data acquisition systems.
Modified phase-locked loop (PLL) generates clock from incoming data signal. To minimize effects of threshold phase-detector gain variations, the PLL uses a dither oscillator, a dither band-pass filter, and correlator instead of coherent amplitude detector.
A rapid scanning two dimensional laser velocimeter (LV) has been used to measure simultaneously the vortex vertical and axial velocity distributions in the Langley Vortex Research Facility. This system utilized a two dimensional Bragg cell for removing flow direction ambiguity by translating the optical frequency for each velocity component, which was separated by band-pass filters. A rotational scan mechanism provided an incremental rapid scan to compensate for the large displacement of the vortex with time. The data were processed with a digital counter and an on-line minicomputer. Vaporized kerosene (0.5 micron to 5 micron particle sizes) was used for flow visualization and LV scattering centers. The overall measured mean-velocity uncertainity is less than 2 percent. These measurements were obtained from ensemble averaging of individual realizations.
In a round turbulent jet at room temperature, measurement of the shear correlation coefficient as a function of frequency (through band-pass filters) has given a rather direct verification of Kolmogoroff's local-isotropy hypothesis. One-dimensional power spectra of velocity and temperature fluctuations, measured in unheated and heated jets, respectively, have been contrasted. Under the same conditions, the two corresponding transverse correlation functions have been measured and compared. Finally, measurements have been made of the mean thermal wakes behind local (line) heat sources in the unheated turbulent jet, and the order of magnitude of the temperature fluctuations has been determined.
The structure of the turbulence in the mixing region for the first few diameters downstream from the outlet of a circular subsonic jet is characterized at three Mach numbers, 0.3, 0.5, and 0.7, with most of the measurements taken at M = 0.3. Profiles of turbulence intensity showed that downstream of the lip intensity is independent of axial distance, while in the core intensity varies by a factor of eight between the jet outlet and the end of the core. A digital data reduction program was used to calculate the auto- and cross-correlations of axial velocity fluctuations and the power spectral densities. Convection velocities were measured using broadband, hot wire signals and signals that were digitally filtered for band-passes about center frequencies of 0.8, 1.3, 1.6, and 3.2 kHz. The center frequency of 1.3 kHz corresponded to the peak energy in the core spectrum. The results support the hypothesis that the coherent pressure field is driven by the intermittent fluctuations at the core boundary, which in turn are related to the large (low frequency) eddies.
As new analytical instruments and techniques emerge with increased dimensionality, a corresponding need is seen for data processing logic which can appropriately address the data. Two-dimensional measurements reveal enhanced unknown mixture analysis capability as a result of the greater spectral information content over two one-dimensional methods taken separately. It is noted that two-dimensional convolute integers are merely an extension of the work by Savitzky and Golay (1964). It is shown that these low-pass, high-pass and band-pass digital filters are truly two-dimensional and that they can be applied in a manner identical with their one-dimensional counterpart, that is, a weighted nearest-neighbor, moving average with zero phase shifting, convoluted integer (universal number) weighting coefficients.
The detection of clear-air turbulence (CAT) ahead of an aircraft in real-time by an infrared (IR) radiometer is discussed. It is noted that the alter time and reliability depend on the band-pass of the IR filter used and on the altitude of the aircraft. Results of flights tests indicate that a bandpass of 20 to 40 microns appears optimal for altering the aircraft crew to CAT at times before encounter of 2 to 9 min. Alert time increases with altitude, as the atmospheric absorption determining the horizontal weighting is reduced.
A sample of statistics, namely the seasonal cycle of baroclinic storms, as represented by bandpass filtered geopotential height variances at 850 mb is presented. The particular filter used is that suggested by Blackmon and White (1982), and retains periods of approximately 2.5 to 10 days. The time series of height (at each grid point) were filtered by removing the annual and semiannual cycles for that point, and by removing zonal wavenumbers higher than 20. The bandpass filter was then applied. The height variances of the filtered fields were then computed for each winter season, each spring, each summer season, and each fall season. These variances were then averaged by season. Maps of the standard deviation are shown. Figures show clearly the seasonal cycle of bandpass fluctuations. The major seasonal variation is seen to consist mostly of a summertime weakening and shift; spring and fall appear nearly identical to winter. The corresponding results at 500 mb are similar, but with the stormtrack variance being slightly larger in spring and fall compared to winter.
A method for calculating the increase in received telemetry signal power required to compensate for the use of a radio frequency interference (RFI) filter in front of the DSN receiving system low-noise amplifier is described. The telemetry system for which the degradation is calculated is an uncoded PCM/PM system in which the NRZ data directly modulates the carrier at a modulation level which leaves a discrete carrier. A phase-locked loop in the RF receiver tracks the discrete carrier and coherently demodulates the PCM data. The RFI filter may be a series of Butterworth, Tchebychev, or Bessel low-pass, high-pass, band-pass, or band-reject filters, each with arbitrary bandwidth, number of poles, and, for band-pass or band-reject filters, resonant frequency. The only restriction is that the RFI filter must have only simple poles. Numerical results are presented for the RFI filters the DSN plans to place in front of the S-band FET, S-band maser, and X-band maser low noise amplifiers. The main conclusion is that the filters will produce negligible degradation at data rates below 4 Mbps.
Computation of a single geoidal height from gravity acceleration data formally requires that the latter be known everywhere on the earth. A computational procedure based on linear inverse theory for estimating geoidal heights from incomplete sets of data is presented. The same scheme can be used to estimate gravity accelerations from altimetry-derived geoids. The systematic error owing to lack of data and the choice of a particular inverse operator is described by using resolution functions and their spherical harmonic expansions. An rms value of this error is also estimated by assuming a spectrum for the unknown geoid. The influence of the size of the data region, the spacing between data, the filtering applied to the data, and the model weighting function chosen are all quantified in a spherical geometry. The examples presented show that when low degree spherical harmonic coefficients are available - from satellite orbit analysis - a band-passed version of the geoid can be constructed from local gravity data, even with a relatively restricted data set.