Decimation Of Data Research Articles

Optimized design of windowed-sinc anti-aliasing filters for phase-preserving decimation of hydrophone data.

Passive acoustic monitoring generates large data sets for which decimation is beneficial to analysis and portability for data sharing. Among the goals for effective decimation are avoidance of aliasing in the passband, accurate and complete control of the attenuation profile, phase preservation, and high efficiency in processing. We present an approach to decimator design that addresses each of these goals, and we demonstrate its application to ocean audio recordings. Anti-aliasing is achieved by windowed-sinc filters that also preserve phase. Control of the passband attenuation profile is based on the specification of the maximum allowed attenuation at a certain percentage of the final output Nyquist frequency. The window type is selected to meet the stopband attenuation requirement. Efficiency is achieved through optimization of the anti-aliasing filters applied in each decimation stage, and through parallelization of processing. The best combination of the sinc function's cutoff frequency and the mainlobe bandwidth of the window function generates the shortest qualifying filter, optimizing the trade-off between filter performance and computational load. Parallelization is enabled by applying the overlap-add method to contiguous segments of audio data, consistent with the commonly used storage of contiguous audio data in files of limited duration. Beyond addressing common goals for effective decimation of audio data, the approach presented is deployable in open-source environments.

Modeling river bed morphology, roughness, and surface sedimentology using high resolution terrestrial laser scanning

Recent advances in technology have revolutionized the acquisition of topographic data, offering new perspectives on the structure and morphology of the Earth's surface. These developments have had a profound impact on the practice of river science, creating a step change in the dimensionality, resolution, and precision of fluvial terrain models. The emergence of “hyperscale” survey methods, including structure from motion photogrammetry and terrestrial laser scanning (TLS), now presents the opportunity to acquire 3‐D point cloud data that capture grain‐scale detail over reach‐scale extents. Translating these data into geomorphologically relevant products is, however, not straightforward. Unlike traditional survey methods, TLS acquires observations rapidly and automatically, but unselectively. This results in considerable “noise” associated with backscatter from vegetation and other artifacts. Moreover, the large data volumes are difficult to visualize; require very high capacity storage; and are not incorporated readily into GIS and simulation models. In this paper we analyze the geomorphological integrity of multiscale terrain models rendered from a TLS survey of the braided River Feshie, Scotland. These raster terrain models are generated using a new, computationally efficient geospatial toolkit: the topographic point cloud analysis toolkit (ToPCAT). This performs an intelligent decimation of point cloud data into a set of 2.5‐D terrain models that retain information on the high‐frequency subgrid topography, as the moments of the locally detrended elevation distribution. The results quantify the degree of terrain generalization inherent in conventional fluvial DEMs and illustrate how subgrid topographic statistics can be used to map the spatial pattern of particle size, grain roughness, and sedimentary facies at the reach scale.

Development and validation of a phase shift and attenuation free filtering for exploitation of CFD data

A causal filtering method is developed to perform decimation and storage of aerodynamic data without signal distortion. When done without precaution, decimation of instantaneous computed flow fields for storage and subsequent exploitation generates aliasing. Use of a low-pass filter limits the creation of spurious noise but attenuates signal amplitudes and shifts phases. The proposed filtering method combines the application of a low-pass filter before decimation, during the aerodynamic simulation, with that of a corrective filter, applied in the frequency domain after the full storage. This corrective filter is designed to correct attenuation and phase distortion caused by the low-pass filter. The method is validated on analytical signals and successfully applied to turbulent shear layer and noise radiation problems.

Experimental comparison of connectivity measures with simulated EEG signals

Directional connectivity measures exist with different theoretical backgrounds, i.e., information theoretic, parametric-modeling based or phase related. In this paper, we perform the first comparison in this extend of a set of conventional and directed connectivity measures [cross-correlation, coherence, phase slope index (PSI), directed transfer function (DTF), partial-directed coherence (PDC) and transfer entropy (TE)] with eight-node simulation data based on real resting closed eye electroencephalogram (EEG) source signal. The ability of the measures to differentiate the direct causal connections from the non-causal connections was evaluated with the simulated data. Also, the effects of signal-to-noise ratio (SNR) and decimation were explored. All the measures were able to distinguish the direct causal interactions from the non-causal relations. PDC detected less non-causal connections compared to the other measures. Low SNR was tolerated better with DTF and PDC than with the other measures. Decimation affected most the results of TE, DTF and PDC. In conclusion, parametric-modeling-based measures (DTF, PDC) had the highest sensitivity of connections and tolerance to SNR in simulations based on resting closed eye EEG. However, decimation of data has to be carefully considered with these measures.

10 Gbit/s bit interleaving CDR for low-power PON

A novel, low power, downstream clock and data recovery (CDR)- decimator architecture is proposed for next generation, energy efficient 10 Gbit/s optical network units (ONUs). The architecture employs a new time division multiplexing bit-interleaving downstream concept for passive optical networks (Bi-PON) allowing early decimation of the incoming data and lowering of the processing speed to the user rate of the ONU, thus reducing the power consumption significantly.

Out-of-Network Events Can Be of Great Importance for Improving Results of Local Earthquake Tomography

In most local earthquake tomography (LET) studies the data are selected according to the azimuthal-gap (GAP) criterion, which means rejecting all the sources outside the station network perimeter. In this article I show that in some cases this cri- terion is inappropriate and can be a reason for significant decimation of the relevant data, in turn leading to lower quality inversion results. This study presents several qua- litativeandquantitativeargumentsforwhytheGAPcriterionisnotadequate.Thefactof great importance to out-of-network events for improving the results of tomographic inversion is supported by synthetic testing using realistic distribution of events in the area of Central Java and station locations according to the Merapi Amphibious Ex- periments project. I consider three models with different criteria of event selection: (1) dataset with GAP < 180°, (2) dataset with GAP < 280°, and (3) dataset with all events within a radius of 5°. The synthetic modeling reproduces the real situation when neither coordinates of sources nor starting 1D models are initially known. The recon- structionresultsshowthatthebestresolutionisobtainedformodel3withalldataavail- able, while the worst solution is observed in model 1. This study demonstrates that the commonlyusedGAPcriterionthatrejectstheout-of-networkeventsisinjuriousforLET tomography. In future experiments and when reconsidering the old datasets, I encour- age the use of data from all events to improve the results of tomographic inversion, though at large distances from networks (at least, up to 400-500 km).

Theoretically correct decimation of GPS data

As the spectrum of GPS applications continuously widens, it becomes usual to collect GPS data at a high rate and to decimate them to slower rates depending on the applications. It is shown in this paper that the decimation process is not as trivial as it sounds. Some important rules are presented that have to be observed for the decimation to be theoretically correct. Two decimation algorithms are proposed. The first one follows these rules, but it is shown that it gives rather poor results in terms of measurement noise (yielding a noise reduction by a factor of 2 for a decimation from 1 to 30 seconds). The second one is not perfectly “correct”, but is more successful in reducing the noise (achieving a reduction by a factor of 5.5 for a 1–30 decimation), and it proves to be adequate for all practical purposes.

Modal identification of boiler plant structures by seismic records(Identification based on a single-input/multi-output model).

This paper deals with an experimental modal analysis method for large-scale structures such as boiler plants in thermal power stations. Practical and accurate modal identification has been carried out by the proposed method, which is composed of two stages : (1) processing transfer functions by autoregressive (AR) spectral analysis, and (2) a curve-fitting technique to extract modal parameters. Seismic records of base acceleration are utilized as input data, and a series of response acceleration records at various points of the structure are utilized as multi-output data. This method is examined using time-series data of seismic response simulation. Introduction of two techniques, namely, decimation of time data and FPE criterion to optimize the order of the AR model, have realized effective and accurate identification. This method has actually been applied to in-situ seismic observation data of a boiler plant in operation. As a result of these investigations, this kind of modal identification has proven to be an effective tool for seismic modeling of large-scale structures.

Modal identification of boiler plant structures using seismic and microtremor records.

This paper deals with a modal identification method for large-scale structures such as boiler plants in thermal power stations. Practical and accurate modal identification has been carried out using seismic and microtremor records observed in boiler plants in operation. Based on the multi-input/output identification method, 3-D mode shapes were identified from the microtremor records. They are in good agreement with the results of the FEM simulation. Identification using seismic records was then executed by the following two stages in order to evaluate the amplitude dependence of modal damping ratios : ( 1 ) processing frequency transfer functions by the autoregressive (AR) spectral analysis, and ( 2 ) an extraction of modal parameters by a curve-fitting technique. Introduction of two techniques, namely, decimation of time data and FPE criterion to optimize the order of AR models, have realized effective and accurate identification. As a result of this study, our modal identitication method has proven to be effective for seismic modeling of large scale structures.