Signal Processing

Nuclear Test Ban Treaty Verification: Improving Test Ban Monitoring with Empirical and Model-Based Signal Processing

by Steven J. Gibbons

D B Harris, S J Gibbons, A J Rodgers, M E Pasyanos,
IEEE Signal Processing Magazine (impact factor: 4.91). 05/2012; 29(3):57-70.

Study of the signals provided by lightning magnetic direction finder

by Angel Gonzalez-Lizardo

Vector-dependent Functionally Pooled ARX Models for the Identification of Systems Under Multiple Operating Conditions

by Fotis Kopsaftopoulos

Proceedings of the 16th IFAC Symposium on System Identification, (SYSID), Brussels, Belgium, July 2012.

Social interactions, musical arrangement, and the production of digital audio in Istanbul recording studios

by Eliot Bates

PhD Dissertation, University of California, Berkeley, 2008

The detection of low magnitude seismic events using array-based waveform correlation

by Steven J. Gibbons

Geophysical Journal International, Vol. 165, No. 1. (April 2006), pp. 149-166, doi:10.1111/j.1365-246X.2006.02865.x
by Steven J. Gibbons, Frode Ringdal

It has long been accepted that occurrences of a known signal are most effectively detected by cross-correlating the... more It has long been accepted that occurrences of a known signal are most effectively detected by cross-correlating the incoming data stream with a waveform template. Such matched signal detectors have received very little attention in the field of detection seismology because there are relatively few instances in which the form of an anticipated seismic signal is known a priori. Repeating events in highly confined geographical regions have been observed to produce very similar waveforms and good signals from events at a given site can be exploited to detect subsequent co-located events at lower magnitudes than would be possible using traditional power detectors. Even greater improvement in signal detectability can be achieved using seismic arrays; running correlation coefficients from single sensors can be stacked over an array or network to result in a network correlation coefficient displaying a significant array gain. If two events are co-located, the time separating the corresponding patterns in the wave train as indicated by the cross-correlation function is identical for all seismic stations and this property means that the correlation coefficient traces are coherent even when the waveforms are not. We illustrate the power of array-based waveform correlation using the 1997 August 16 Kara Sea event. The weak event that occurred 4 hr after the main event was barely detected using an STA/LTA detector on the SPITS array but is readily detected by signal matching on a single channel. The main event was also recorded by the far more distant NORSAR array but no conventional detection can be made for the second event. A clear detection is, however, made when the correlation coefficient traces are beamformed over all sensors of the array. We estimate the reduction in detection threshold of a test signal on a regional seismic array using waveform correlation by scaling down a master signal and immersing it into seismic noise. We show that, for this case, waveform correlation using a single channel detects signals of approximately 0.7 orders of magnitude lower than is possible using an STA/LTA detector on the array beam. Waveform matching on the full array provides an additional improvement of approximately 0.4 magnitude units. We describe a case study in which small seismic events at the Barentsburg coal mine on Spitsbergen were detected using the signals from a major rockburst as master waveforms. Many spurious triggers occurred in this study whereby short sections of signal exhibited coincidental similarity with unrelated incoming wave fronts. We demonstrate how such false alarms can almost always be identified and screened out automatically by performing frequency–wavenumber analysis upon the set of individual correlation coefficient traces.

Improvements to Seismic Monitoring of the European Arctic Using Three-Component Array Processing at SPITS

by Steven J. Gibbons

S. J. Gibbons, J. Schweitzer, F. Ringdal, T. Kværna, S. Mykkeltveit, B. Paulsen
Bulletin of the Seismological Society of America, Vol. 101, No. 6. (01 December 2011), pp. 2737-2754, doi:10.1785/0120110109

The detectability of low magnitude seismic events in the European Arctic is determined primarily by the small-aperture... more The detectability of low magnitude seismic events in the European Arctic is determined primarily by the small-aperture International Monitoring System arrays ARCES and SPITS. In August 2004, the SPITS array was upgraded to a broadband array with an increase in the sampling rate from 40 to 80 Hz. Most important, however, for the detection and location of small-magnitude seismic events was the deployment of three-component instruments at six of the nine sites. Detection and correct classification of secondary phases are of paramount importance for events observed by only a small number of stations at regional distances; and, in the absence of the strong Lg phases typically observed for continental propagation paths, multiple three-component stations were deemed necessary to exploit the higher S-phase amplitudes anticipated on the horizontal sensors. We demonstrate improved signal-to-noise ratios (SNRs) for S phases on horizontal beams for several events close to Novaya Zemlya. Horizontal component f-k analysis improves direction estimates and phase classification for low-SNR signals. We demonstrate secondary phases that are misidentified by vertical-only f-k analysis but which are correctly classified by three-component array processing. A significant problem with array processing at SPITS is the overlap in slowness space of regional P and S phases. Phase identification is improved greatly by comparing the coherence between vertical traces with the coherence between horizontal traces. Considerations in the routine array processing of SPITS data are reviewed, including the need for elevation corrections in slowness estimation and the need to take into account azimuth-dependent variation of apparent velocity estimates for regional phases.

Tidal flow local mean velocities in noisy signals.

by Roger Falconer - Cardiff University

Paper 57:  Yin, J., Lloyd, P. M. and Falconer, R. A. 2001. Tidal flow local mean velocities in noisy signals. Flow Measurement and Instrumentation. 12(1), 25-28.

Abstract
A new method was developed to calculate the local mean velocity of unsteady tidal flow from the... more Abstract
A new method was developed to calculate the local mean velocity of unsteady tidal flow from the experimental data using Sontek-ADV and Ultrasonic meters with noisy signals. The method is mainly to analyse a time series of velocity signals in order to obtain a time series of a Moving-Averaged velocity. The paper presents the details of the method. The processing shows acceptable results.

Steepest Descent Least Mean Square Algorithm (LMS) Based Adaptive Filter for Noise Cancellation in Speech Signals

by Udayanto Dwi Atmojo

Presented in 6th SEAMS GMU International Conference on Mathematics and Its Applications 2011 in Yogyakarta, Indonesia, July 12-15, 2011

This paper considers Least Mean Square (LMS) algorithm to subsequently modify adaptive filter weights. The... more This paper considers Least Mean Square (LMS) algorithm to subsequently modify adaptive filter weights. The corresponding filter is used to cancel noise caused by diesel engine interference contained in speech signal. The design is then implemented on LabView software. The simulation shows that the design can reduce interference, thus increasing signal to noise ratio (SNR) of the speech signal by more than 100%

ECG Signal Preprocessing using LabView : LMS based Adaptive Filter for Powerline Interference Cancellation

by Udayanto Dwi Atmojo

Published in International Conference on Information Technology and Electrical Engineering (CITEE) 2011 in Yogyakarta, Indonesia on 20 July 2011. Co authored by Dr Eka Firmansyah

This paper considers Least Mean Square (LMS) algorithm to subsequently modify adaptive filter wieghts. The... more This paper considers Least Mean Square (LMS) algorithm to subsequently modify adaptive filter wieghts. The corresponding filter is used to cancel noise caused by powerline interference contained in Electrocardiograph (ECG) signal. The design is then implemented on LabView software. The simulation shows that the design can reduce powerline interference. Average powerline noise power contained in the signal is attenuated by more than 20 times.

Establishing “Zone of Silence”: LMS Adaptive Filter Implementation for Noise Cancellation

by Udayanto Dwi Atmojo

Published in International Conference on Informatics for Development (ICID) 2011 in Yogyakarta, Indonesia on 26th November 2011

This paper considers an implementation of Least
Mean Square (LMS) adaptive filter for noise cancellation. In... more This paper considers an implementation of Least
Mean Square (LMS) adaptive filter for noise cancellation. In this
paper, the adaptive filter is used to create a “Zone of Silence”.
The paper considers the use of LMS adaptive filter to cancel
engine noise in a target area by generating a signal that will
interfere destructively with the noise signal, hence cancels the
noise introduced in the target area. The proposed model is
simulated using LabView software. The resuts show that the
proposed model can cancel out noise average power up to 7900
times.

An Image Processing Technique for the Translation of ASL Finger-Spelling to Digital Audio or Text. Paper Presented at the Instructional Technology and Education of the …

by Chance Glenn

Structural health monitoring by Lyapunov exponents of non‐linear time series

by Sara Casciati

Casciati F. and Casciati S. (2006). “Structural health monitoring by Lyapunov exponents of nonlinear time series”. Structural Control & Health Monitoring, 13(1), 132-146. ISSN: 1545-2255.

DATE AND PLACE OF PUBLICATION: January-February 2006; John Wiley & Sons, Ltd., Chichester PO19 8SQ, W Sussex, England.

ABSTRACT. In this study, structural health monitoring is pursued by collecting multi-channel measurements and by... more ABSTRACT. In this study, structural health monitoring is pursued by collecting multi-channel measurements and by computing, directly from them, the Lyapunov exponents. The latter quantities are invariants of the dynamic system, so that their different values, associated with different time histories obtained from the same structure, denote damage. First, the problem is framed in the general theory. The structural health monitoring strategy is then formulated, with special care being devoted to its capability of localizing damage. The procedure is finally validated by using the time histories which were collected during the experimental tests on the model of a monumental arch.

KEY WORDS: dynamic system; Kolmogorov entropy; Lyapunov dimension; Lyapunov exponents; observed variables space; structural health monitoring

Generation of spatiotemporally correlated spike trains and local field potentials using a multivariate autoregressive process

by Diego Gutnisky

Gutnisky DA, Josić K. Journal Neurophysiology 2010 May;103(5):2912-30. Epub 2009 Dec 23

Experimental advances allowing for the simultaneous recording of activity at multiple sites have significantly... more Experimental advances allowing for the simultaneous recording of activity at multiple sites have significantly increased our understanding of the spatiotemporal patterns in neural activity. The impact of such patterns on neural coding is a fundamental question in neuroscience. The simulation of spike trains with predetermined activity patterns is therefore an important ingredient in the study of potential neural codes. Such artificially generated spike trains could also be used to manipulate cortical neurons in vitro and in vivo. Here, we propose a method to generate spike trains with given mean firing rates and cross-correlations. To capture this statistical structure we generate a point process by thresholding a stochastic process that is continuous in space and discrete in time. This stochastic process is obtained by filtering Gaussian noise through a multivariate autoregressive (AR) model. The parameters of the AR model are obtained by a nonlinear transformation of the point-process correlations to the continuous-process correlations. The proposed method is very efficient and allows for the simulation of large neural populations. It can be optimized to the structure of spatiotemporal correlations and generalized to nonstationary processes and spatiotemporal patterns of local field potentials and spike trains.

Blind Signal Processing Algorithms

by Athanasios Margaris

Proceedings of the 12th International Workshop on Systems, Signal, and Image Processing (IWSSIP 2005), 22-24 September 2005, Chalkida, Greece, pages 105-109, Co-authored with E.Kotsialos

Speech event detection using multiband modulation energy

by Georgios Evangelopoulos

DEMONic Dominoes, measuring the speed of the domino effect

by Ron Larham

This is a one part version of the paper on measuring the speed of propogation of the wave of collapse in an array of dominoes published in/on the Citizen Scientist on-line journal in 2007. This version was produced in 2009, and is now posted here as the Citizen Scientist web site is no longer available.

It has been suggested that I should submit this (or a version of it) to a journal, but I can't think of a suitable one at present.

Note: I forgot to upload a copy when this entry was first created, that has now been corrected
.

In response to a challenge in a (now not so) recent paper to measure the propagation speed of the wave of collapse of... more In response to a challenge in a (now not so) recent paper to measure the propagation speed of the wave of collapse of an array of dominoes (the Domino Effect), a novel method of measuring the speed of such waves has been developed using sound recordings of the collapse and DEMON (Detection of Modulation on Noise) analysis to extract the frequency of domino impacts and hence the speed of propagation of the domino wave. This paper presents this method and a discussion of the other published measurements and models and some comments on the precess of mathematical modelling.


This is a companion piece to my paper "Validation of a Model of the Domino Effect" also on Academia.edu

Multidimensional Wave Field Signal Theory: Transfer Function Relationships

by Natalie Baddour

Mathematical Problems in Engineering
Volume 2012 (2012), Article ID 478295, 27 pages
doi:10.1155/2012/478295

The transmission of information by propagating or diffusive waves is common to many fields of engineering and physics.... more The transmission of information by propagating or diffusive waves is common to many fields of engineering and physics. Such physical phenomena are governed by a Helmholtz (real wavenumber) or pseudo-Helmholtz (complex wavenumber) equation. Since these equations are linear, it would be useful to be able to use tools from signal theory in solving related problems. The aim of this paper is to derive multidimensional input/output transfer function relationships in the spatial domain for these equations in order to permit such a signal theoretic approach to problem solving. This paper presents such transfer function relationships for the spatial (not Fourier) domain within appropriate coordinate systems. It is shown that the relationships assume particularly simple and computationally useful forms once the appropriate curvilinear version of a multidimensional spatial Fourier transform is used. These results are shown for both real and complex wavenumbers. Fourier inversion of these formulas would have applications for tomographic problems in various modalities. In the case of real wavenumbers, these inversion formulas are presented in closed form, whereby an input can be calculated from a given or measured wavefield.

On-chip CMOS compatible reconfigurable optical delay line with separate carrier tuning for microwave photonic signal processing

by Maurizio Burla

Optics Express, Vol. 19, Issue 22, pp. 21475-21484 (2011)
http://dx.doi.org/10.1364/OE.19.021475

We report, for the first time, an integrated photonic signal processor consisting of a reconfigurable optical delay... more We report, for the first time, an integrated photonic signal processor consisting of a reconfigurable optical delay line (ODL) with a separate carrier tuning (SCT) unit and an optical sideband filter on a single CMOS compatible photonic chip. The processing functionalities are carried out with optical ring resonators as building blocks. We show that the integrated approach together with the use of SCT technique allows the implementation of a wideband, fully-tunable ODL with reduced complexity. To highlight the functionalities of the processor, we demonstrate a reconfigurable microwave photonic filter where the ODL has been configured in a bandwidth over 1 GHz.

© 2011 OSA

Response Surface Models to Detect and Localize Distributed Cracks in a Complex Continuum

by Sara Casciati

Casciati S. (2010). “Response surface models to detect and localize distributed cracks in a complex continuum”. Journal of Engineering Mechanics – ASCE, 136(9), 1131-1142. ISSN: 0733-9399.

DATE AND PLACE OF PUBLICATION: September 2010; ASCE – American Society of Civil Engineers, Reston, VA 20191-4400, USA.

ABSTRACT:Linear response surface
RS models are used to represent the relationship between samples of response time... more ABSTRACT:Linear response surface
RS models are used to represent the relationship between samples of response time histories measured by sensors placed across a structure. Different structural states of a general time-variant system are considered for short intervals capturing a linearized model of each state. Within this framework, the error associated with each RS model is sensitive to a modification of the structural state. A method that relates the changes of the statistical characterization of the error to the occurrence of a structural modification is developed for damage detection. The localization of damage is then pursued by identifying the largest discrepancies resulting from the comparison between the statistics of the sum of the squares of the error obtained at each sensor location. The generality of the method is shown by applying it to the experimental data of a realistic structure, which is representative of a continuous body affected by distributed cracking.

KEYWORDS: Dynamics; Vibration; Structural response; Statistics; Damage; Monitoring; Masonry; Cracking

Stability for second-order chaotic sigma delta quantization

by Lauren Bandklayder

(with Rachel Ward, preprint)