Unfiltered Data Research Articles

Linear inverse filtering improves spatial separation of nonlinear brain dynamics: a simulation study

We examined topographic variations in nonlinear measures based on scalp voltages, which were generated by two simulated current dipoles each placed in a different hemisphere of a spherical volume conductor (three-shell model). Dipole dynamics were that of a three-torus and the x-component of the Lorenz-system and scalp voltage were calculated for a configuration of 29 electrode positions. Although estimates for correlation dimension D2 and Lyapunov exponent L1 were close to the theoretical values for the original time series, the simulated scalp voltage data showed almost no topographic resolution of dipole positions. In order to enhance topographic differentiation, we constructed linear inverse filters, to focus on brain activity from a specified brain region. It turned out that the nonlinear measures for the inversely filtered time series were much closer to the expected values (with respect to the location of the dipoles used in the simulation) than when using unfiltered data. Our preliminary results indicate that inverse filtering can improve the topographic resolution of nonlinear scalp EEG estimates.

The effect of speckle filtering on scale-dependent texture estimation of a forested scene

Spatial fluctuations in microwave backscatter may be an important piece of information in discriminating tree stands. However, the presence of speckle in synthetic aperture radar (SAR) image data is a barrier to the exploitation of image texture. The authors explored a new methodology that combines a recent adaptive speckle reduction algorithm by Lopes et al. (1990) with a generic texture estimation scheme. They investigated the claim that this filter was capable of preserving backscatter texture. To understand if speckle reduction was destroying backscatter texture, they compared the strength of the relationship between forest inventory parameters and image texture as a function of spatial scale for both filtered and unfiltered images. They used Radarsat Fine mode image data: single look resolution is approximately 8.5 m, and pixel spacing is 3 m. Their study area was northern Vancouver Island, B.C., on the west coast of Canada. For the unfiltered data, they found that the ability of image texture to predict the forest parameters decreased as the texture scale increased from 3 to 13 m, suggesting greater information content in the small scale texture. For the filtered data, this relationship was much weaker at small scales and was not a function of distance. Their results suggest that the speckle filter was not retaining small scale texture, which is consistent with the theoretical hypotheses underlying its multiplicative noise model. They also show that there is significant information in small state SAR image texture that may be used as an adjunct to other spatial information for discriminating tree stands in the temperate rain forest.

X‐Ray and Optical Observations of BL Hydri

We acquired hard X-ray and unfiltered optical photometric data of the AM Herculis system BL Hydri. The X-ray data were obtained using the Proportional Counter Array detector of the Rossi X-Ray Timing Explorer satellite on 1997 October 17. The optical data were obtained using the 1.5 m telescope of the Cerro Tololo Inter-American Observatory on 1997 September 24. At the time of our observations, BL Hyi was in an unusual high-luminosity state with average visual magnitude mV ≈ 14.4 and orbital phase-averaged 2-10 keV X-ray flux ≈1.5 × 10-11 ergs cm-2 s-1, roughly 50% larger than had been seen previously. The X-ray light curves suggested that two accretion poles were active. The primary X-ray emission region was extended, covering ~45° in longitude on the white dwarf, while the secondary X-ray emission region was consistent with a point source with flux ~33% that of the primary region. The X-ray spectra were well fitted by absorbed bremsstrahlung with Gaussian emission-line models; and absorbed power law with Gaussian emission-line models. For the thermal models, the X-ray spectra were consistent with kTX ≈ 11 keV and an emission line at E ≈ 6.7-6.8 keV with equivalent width EW = 0.86-1.2 keV. The absorbed power-law models had slope α ≈ 2.1 and an emission line at E = 6.7-6.8 keV with EW = 1.1-1.5 keV. The optical data showed, 2.7% ± 0.2% rms quasi-periodic oscillations (QPOs) over the frequency range 0.2-0.8 Hz modulated strongly on the orbital period suggesting that the QPOs were connected with the dominant accretion hot spot. We did not find corresponding QPOs in the X-ray emission for an upper limit of 20% rms. There were no detections of other short-period QPOs or coherent features in either the optical or the X-ray data. The X-ray and optical data were consistent with a radiative shock model. Based primarily on the X-ray continuum and line spectrum, we infer that the mass of the white dwarf in the BL Hyi system is 0.3-0.7 M☉, depending on the relative cyclotron and hard X-ray luminosities.

Effect of the subgrid scales on particle motion

In this study, the effects of small-scale velocity fluctuations on the motion of tracer particles is investigated by releasing particles in a turbulent channel flow at Reτ=175, and following their motion in time. Two types of numerical experiments were carried out: first, the Eulerian velocity field was evaluated by the direct numerical simulation (DNS) and the particles were advanced in time using the resolved and several filtered velocity fields to study the effect of the subgrid-scale velocity fluctuations on particle motion without the influence of modeling errors. In the second stage, the particle-motion study was performed using independent DNS and large-eddy simulations (LES), thus including the effect of interpolation and subgrid-scale stress modeling errors on the dispersion statistics. At this Reynolds number the small scales were found to have a limited effect on the statistics examined (one-particle dispersion, one-particle velocity autocorrelation, Lagrangian integral time scale, turbulent diffusivity, and two-particles rms dispersion). Only when a significant percentage of the energy was removed from the velocity field some differences were observed between filtered and unfiltered data (especially near the wall). It was found that when the dynamic eddy-viscosity model was employed, modeling errors did not affect the results as much as the filtering itself; the use of the Smagorinsky model, on the other hand, gave inaccurate results. Additional computations for finite-inertia particles have shown that these results represent a conservative estimate, in the sense that actual particles with inertia are less sensitive than the tracer particles examined in the first part of the investigation, and that LES provides improved results when particles with inertia are used.

A Procedure for the Automatic Determination of Filter Cutoff Frequency for the Processing of Biomechanical Data

This article presents and evaluates a new procedure that automatically determines the cutoff frequency for the low-pass filtering of biomechanical data. The cutoff frequency was estimated by exploiting the properties of the autocorrelation function of white noise. The new procedure systematically varies the cutoff frequency of a Butterworth filter until the signal representing the difference between the filtered and unfiltered data is the best approximation to white noise as assessed using the autocorrelation function. The procedure was evaluated using signals generated from mathematical functions. Noise was added to these signals so mat they approximated signals arising from me analysis of human movement. The optimal cutoff frequency was computed by finding the cutoff frequency that gave me smallest difference between the estimated and true signal values. The new procedure produced similar cutoff frequencies and root mean square differences to me optimal values, for me zeroth, first and second derivatives of the signals. On the data sets investigated, this new procedure performed very similarly to the generalized cross-validated quintic spline.

Orbital tuning of Cenomanian marly chalk successions: towards a Milankovitch time-scale for the Late Cretaceous

Outcrops of Cenomanian marly chalks in the Crimea (Ukraine) and SE England (UK), 2600 km apart, display conspicuous decimetrescale rhythmicity and can be correlated by using 12 biostratigraphical events. Closely spaced samples from the two sections were used to generate long timeseries of digitally captured greyscale reflectance data. Spectral analysis of these data demonstrates that if the rhythmicity is assumed to be driven by precession (bedding cycles; mode at 20 ka), it is seen to be modulated by the short eccentricity cycle (100 ka bundles). The latter signal is expressed in the sediments by the occurrence of dark marls at precession minima occurring at eccentricity maxima. Although identified in the spectra, tilt (38 ka) and the long eccentricity cycle (400 ka) are not strongly expressed. Comparison of age modelled, unfiltered greyscale data between the two sections reveals strikingly similar patterns, and enables the identification of a 80 ka hiatus in the UK chalks.

Monetary Policy Evaluation with Noisy Information

This paper investigates the implications of noisy information regarding the measurement of economic activity for the evaluation of monetary policy. A common implicit assumption in such evaluations is that policymakers observe the current state of the economy promptly and accurately and can therefore adjust policy based on this information. However, in reality, decisions are made in real time when there is considerable uncertainty about the true state of affairs in the economy. Policy must be made with partial information. Using a simple model of the U.S. economy, I show that failing to account for the actual level of information noise in the historical data provides a seriously distorted picture of feasible macroeconomic outcomes and produces inefficient policy rules. Naive adoption of policies identified as efficient when such information noise is ignored results in macroeconomic performance worse than actual experience. When the noise content of the data is properly taken into account, policy reactions are cautious and less sensitive to the apparent imbalances in the unfiltered data. The resulting policy prescriptions reflect the recognition that excessively activist policy can increase rather than decrease economic instability.

Continuous gravity recording with Scintrex CG-3M meters:a promising tool for monitoring active zones

We acquired continuous series of microgravity measurements using several Scintrex CG-3M gravity meters for several weeks in 1997. The meters with 1 mGal resolution were installed side by side in a stable reference station at the ORSTOM research centre to perform identical data acquisition. We present and compare the instrumental responses obtained for the various gravity meters (measurement series of gravity field, standard deviation, internal temperature, tilts) and analyse their correlation with simultaneous recordings of meteorological parameters. The data have been processed in order to (1) establish the mid-to long-term relative stability and the accuracy of the instruments, (2) estimate the contribution of instrumental effects to gravity data measurements and (3) quantify the amplitude of the time variations of the gravity field that might be detected with such instruments. This study emphasizes the sensitivity of some instrumental responses of the Scintrex CG-3M gravity meters (such as internal temperature or tilt) to local atmospheric-pressure variations. This sensitivity can lead to non-negligible perturbations of the gravity measurements through automatic corrections applied in real-time mode by the integrated software. We show that most of these instrumental artefacts can be easily removed in data post-processing by using simultaneous atmospheric-pressure data. After removal of an accurate Earth tide model, the instrumental drift and the instrumental effects, the temporal series are compared by computing differential signals. These residual signals obtained over a period of several weeks exhibit the following characteristics: (1) the gravity residuals have a maximum amplitude ranging from 5 to 10 mGal and from 10 to 15 μGal for filtered and unfiltered data, respectively; and (2) the standard error, tilts and internal temperature measurements of the various gravity meters are very consistent; their respective residual amplitudes are ±2 mGal, ±3 arcsec and ±0.05 mK. In order to calibrate the gravity meters precisely in the measurement range used in this study, we have measured a calibration line established in the framework of the fourth intercomparison of absolute and relative gravity meters. This calibration was achieved with an accuracy of 5 μGal. This result is consistent with other field tests already performed with such gravity meters. In addition, we also checked the accuracy of the tilt sensors by increasing the electronic read-out by a factor of 10. The tilt response of the whole gravity meter to a small induced inclinometric variation indicates that the precision of the tilt measurements is about a few tenths of an arc second. This study reveals that temporal variations of the gravity field could potentially be detected in the field with an accuracy of about 5–15 mGal by permanent networks of Scintrex CG-3M gravity meters set up a few kilometres apart. This result is of particular interest in field surveys of temporal gravity changes related to some environmental or geodynamical processes, where the expected gravity variations are greater than a few tens of mGal. In particular, in volcanological applications, the continuous monitoring of active volcanoes with such permanent networks of gravity meters co-located with subcentimetre-accuracy GPS receivers should be very helpful to understand internal magmatic processes better and to detect possible gravity and inclinometric signals occurring during pre-eruptive phases. In this field, continuous microgravity recordings associated with classical reiteration networks will probably improve hazard mitigation in the near future

Experimental Study of a Precision, Hydrodynamic Wheel Spindle for Submicron Cylindrical Grinding

Hydrodynamic journal bearings have been widely used in various types of rotating machinery, ranging from heavy duty, high-impact applications, such as the crank shaft of an internal combustion engine and turbine rotor, to high-precision, light load applications, such as precision spindles in cylindrical grinding machines. Although extensive theoretical and experimental results have been presented for hydrodynamic bearings, the available literature seems to be limited for precision hydrodynamic bearing spindles. In this study, practical methods have been developed to quantify the performance of a hydrodynamic wheel spindle operating in the horizontal mode to produce precision parts with submicron roundness tolerance and very fine surface finish. These methods can easily and cost effectively be implemented on various machines in an actual production environment for effective predictive maintenance. The main experimental results show that the long-term drift of the spindle at steady state is less than 1 μm vertically and 0.2 μm horizontally, and the radial error motion of the spindle based on unfiltered data is less than 1.6 μm for all the speeds tested. It is also found that the shaft center position (vertical lift and horizontal shift) at the cold condition is substantially different from that in the steady-state warm condition. From the results, an optimal spindle speed is recommended.

Monetary Policy Evaluation with Noisy Information

This paper investigates the implications of noisy information regarding the measurement of economic activity for the evaluation of monetary policy. A common implicit assumption in such evaluations is that policymakers observe the current state of the economy promptly and accurately and can therefore adjust policy based on this information. However, in reality, decisions are made in real time when there is considerable uncertainty about the true state of affairs in the economy. Policy must be made with partial information. Using a simple model of the U.S. economy, I show that failing to account for the actual level of information noise in the historical data provides a seriously distorted picture of feasible macroeconomic outcomes and produces inefficient policy rules. Naive adoption of policies identified as efficient when such information noise is ignored results in macroeconomic performance worse than actual experience. When the noise content of the data is properly taken into account, policy reactions are cautious and less sensitive to the apparent imbalances in the unfiltered data. The resulting policy prescriptions reflect the recognition that excessively activist policy can increase rather than decrease economic instability.

Improving digital elevation models over ice sheets using AVHRR-based photoclinometry

AbstractAdvanced very high-resolution radiometer (AVHRR) images and a radar-altimetry-based digital elevation model (DEM) covering part of the northeast Greenland ice stream are combined to create an improved topographic map of the area using photoclinometry. In this application of photoclinometry, a DEM is used to establish the photometric relationship for two AVHRR images of a snow surface. Slopes from the DEM are compared with AVHRR data that are filtered (i.e. blurred) to the resolution of the DEM to give an empirical photometric determination. This is then used to convert unfiltered AVHRR data into quantitative slope measurements of the surface in the along-sun direction in each image, resolving features not present (or poorly represented) in the DEM. Co-registration of the images is based on the assumption that the two slope fields from the images describe one continuous smooth surface. The combined slopes are then converted to topography. In the test case, the technique adds topographic details with spatial scales of ~3 to ~20 km. A comparison of our results with airborne laser elevation profiles demonstrates that the new technique recovers most of the topography that is missed by the DEM. The improved topographic map reveals a ten-fold increase in local surface relief over the ice-stream feature, and shows the presence of shallow troughs over the shear margins of the feature.

Improving digital elevation models over ice sheets using AVHRR-based photoclinometry

AbstractAdvanced very high-resolution radiometer (AVHRR) images and a radar-altimetry-based digital elevation model (DEM) covering part of the northeast Greenland ice stream are combined to create an improved topographic map of the area using photoclinometry. In this application of photoclinometry, a DEM is used to establish the photometric relationship for two AVHRR images of a snow surface. Slopes from the DEM are compared with AVHRR data that are filtered (i.e. blurred) to the resolution of the DEM to give an empirical photometric determination. This is then used to convert unfiltered AVHRR data into quantitative slope measurements of the surface in the along-sun direction in each image, resolving features not present (or poorly represented) in the DEM. Co-registration of the images is based on the assumption that the two slope fields from the images describe one continuous smooth surface. The combined slopes are then converted to topography. In the test case, the technique adds topographic details with spatial scales of ~3 to ~20 km. A comparison of our results with airborne laser elevation profiles demonstrates that the new technique recovers most of the topography that is missed by the DEM. The improved topographic map reveals a ten-fold increase in local surface relief over the ice-stream feature, and shows the presence of shallow troughs over the shear margins of the feature.

Early increases in ischaemic heart disease mortality dissociated from and later changes associated with respiratory mortality after cold weather in south east England.

STUDY OBJECTIVE: To identify the time courses and magnitude of ischaemic heart (IHD), respiratory (RES), and all cause mortality associated with common 20-30 day patterns of cold weather in order...

Circadian Rhythm Estimation by Core Body Temperature Filtered with Simultaneously Recorded Physiological Data

In field measurements, monitoring of core body temperature is influenced by physical activities; therefore, the estimation of circadian rhythm from the data may not be exact. The purpose of this study is to design a core body temperature filter in order to reduce artifacts induced by physical activities using simultaneously recorded physiological data such as heart rate data. The effects of physical activities on core body temperature and heart rate are assessed through three experiments. Based on the above knowledge, a core body temperature filter was designed. The filter removes part of rectal temperature data as artifact when heart rate rises above a predetermined threshold. As a result, most of the spike-like noise was removed and the filtered temperature data showed sinusoidal variation more than the unfiltered data. The mesor of the estimated rhythm significantly decreased. This filtering method can provide more precise information about circadian rhythm, especially in field measurements.

Sea surface heights obtained from Modular Ocean Model simulation and comparison with Topex/Poseidon data for the Indian Ocean

The Modular Ocean Model (MOM) is perhaps the most versatile ocean model available today for the simulation of the large scale circulation of the ocean. The Topex/Poseidon altimeter which has been operating since September 1992 has been providing sea surface heights (SSH) of the accuracy of 5–10 cms with a repeat cycle of 10 days. We examine in this paper, the SSH in the Indian Ocean obtained from a global simulation of MOM with a resolution of 1° in the longitude, 1/3° in the latitude between 30°S and 30°N and 20 levels in the vertical with climatological windforcing and restoring conditions on temperature and salinity. They are compared with the SSH from the Topex/Poseidon altimeter after suitable filtering in the time domain to remove smaller time and length scales. In addition, unfiltered data from both sources are analysed by estimating the cross-spectral density to find the coherence and crossphase at different frequencies. The agreement between the two, over most of the Northern Indian Ocean, especially the Arabian Sea and the Bay of Bengal is quite good.

Determination of glucose concentrations in an aqueous matrix from NIR spectra using optimal time-domain filtering and partial least-squares regression.

We have investigated the use of a time-domain optimal filtering method to simultaneously minimize both the baseline variation and high-frequency noise in near-infrared (NIR) spectrophotometric absorption data of glucose dissolved in a simple aqueous (deionized water) matrix. By coupling a third-order (six-pole) digital Butterworth bandpass filter with partial least-squares (PLS) regression modeling, glucose concentrations were determined for a set of test data with a standard error of prediction (SEP) of 10.53 mg/dl (mean percent error: 4.24%) using seven PLS factors. Compared to the unfiltered test data for six PLS factors and a SEP = 17.00 (mean percent error: 7.38%) this results shows more than a 38% decrease in the error. The glucose concentrations ranged from 51 mg/dl to 493 mg/dl, and the NIR spectral region between 2088 nm and 2354 nm (4789 cm-1 and 4248 cm-1) was used to develop the optimal PLS model. The optimal PLS model was determined from a sequence of three-dimensional performance response maps for different numbers of PLS factors (2-10). A total of 99 NIR spectra were generated for glucose dissolved in deionized water using a NIRsystems 5000 dispersive spectrophotometer. Nine of these spectra were generated for only water, which were averaged and subtracted from the remaining 90 spectra to generate the training and test data sets, thereby, removing the intrinsic high background absorption due to the water. The training set consisted of 57 spectra and associated glucose concentration target values, and the test set was comprised of the remaining 33 spectra and target values. Performance results were compared for three different digital Butterworth bandpass filters (four-poles, six-poles, and eight-poles), and a digital Gaussian filter design approach (i.e., Fourier filtering).

Spatial Sampling Study for the Tropical Pacific with Observed Sea Surface Temperature Fields

Abstract Using weekly averaged sea surface temperature (SST) data with a horizontal resolution of 1° latitude and 1° longitude during 1984-93, basic statistics [such as mean-square error (MSE), correlation length scales, etc.] for unfiltered, low-passed (including interannual change and monthly mean climatology) and high-passed (with a timescale shorter than 1 yr) fields are analyzed. Sampling error formalism proposed by Nakamoto et al. was examined for its practical application. It is found that the MSE caused by the low-frequency-high-frequency interference term is so small that MSE of unfiltered data can be expressed as the sum of MSEs from low-frequency parts and high-frequency parts. The root-mean-square error (rmse) from unflitered data is smaller than 0.3°C except in the near-coastal regions. A maximum rmse belt is found in the equatorial front area in eastern near-equatorial Pacific. The spatial patterns of rmse for unfiltered, high- and low-passed datasets are similar and also similar to those of...

Reduction of physiological fluctuations in fMRI using digital filters.

Data obtained from functional magnetic resonance imaging are often limited by a low signal-to-noise ratio. The time-course data obtained from activated regions contain both system noise and physiological noise, primarily linked to the heart and respiratory rates, that are superimposed on task induced signals. Time averaging of a practical number of data sets is not very effective in improving the signal-to-noise ratio because neither system nor physiological noise is truly random. In this paper, a method is presented for filtering unwanted physiological fluctuations, including aliased signals that are formed as a result of long repetition time (TR) values. A pulse oximeter was used to obtain cardiac and respiratory information during the scanning period. Finite impulse response band-reject digital filters were designed to remove the physiological fluctuations. For comparison, cross-correlation analyses were performed at the same level of statistical significance on both filtered and unfiltered data. We demonstrate that this method can improve the detection of weak signals without increasing the probability of false positives.

MRPII and stand‐alone finite schedulers: the relationships

Discusses the relationships between finite schedulers which operate on output from a higher level in a conventional MRPII system, and so‐called stand‐alone schedulers which essentially operate directly on orders. Presents two graphical models – a demand flow model and a flowpipe model – which help to explain the differences between such schedulers and are used to illustrate the key features of each. Coupled schedulers tend to work on demand which has already been smoothed or planned in some way and can be described as planning‐led, whereas stand‐alone schedulers work from unfiltered data, with the operator reacting to schedule quality (due‐date performance, resource activation levels, etc.) and thence adjusting resource and rerunning. Ascribes the growth of the stand‐alone scheduler, at least in part, to the greatly increased computing power available quite inexpensively on modern equipment.

On the Effects of Filtering on Convective-Core Statistics

Analysis of convective events north of Australia during the equatorial Monsoon Experiment (EMEX) reinforces accumulating evidence that convective cores over the tropical ocean are weak, with small diameters and vertical velocities. Superposition of smaller-scale turbulence on the convective core signal could yield artificially small cores, and thus produce sampling bias by aircraft. To investigate this potential source of bias, a side-by-side analysis of filtered and unfiltered vertical velocity data was performed while investigating the EMEX convective cores. Data were collected by the NOAA P3 and NCAR Electra using filtered (Graham filter) and non-filtered cores. The effects of filtering vertical velocity data to identify updraft and downdraft cores were noticeable but smaller than expected. Updraft cores had a vertical velocity greater than 1 m/sec for at least 500 m, and downdraft cores were defined analogously so that the filter eliminated events with less than a 500 m apparent diameter. Median and 10 percent core diameters were increased by 20-25 percent at most, with larger increases at higher levels (fewer small events). The maximum vertical velocity was changed only by changing the individual events in the distribution, but changes were detectable. At the lower levels, where many small, weak cores are introduced by filtering, average vertical velocity for the updraft cores was lowered by up to around 10 percent. Mass flux was changed the least, since diameter and mean vertical velocity respond to filtering in opposite ways. The filtering procedure increased total mass flux slightly due to inclusion of more upward moving air into the sample.