Search for Periodic Gravitational Wave Sources with the Explorer Detector

We have developped a procedure for the search of periodic signals in the data of gravitational wave detectors. We report here the analysis of one year of data from the resonant detector Explorer, searching for pulsars located in the Galactic Center (GC). No signals with amplitude greater than $\bar{h}= 2.9~10^{-24}$, in the range 921.32-921.38 Hz, were observed using data collected over a time period of 95.7 days, for a source located at $\alpha=17.70 \pm 0.01$ hours and $\delta=-29.00 \pm 0.05$ degrees. Our procedure can be extended for any assumed position in the sky and for a more general all-sky search, even with a frequency correction at the source due to the spin-down and Doppler effects.Comment: One zipped file (Latex+eps figures). 33 pages, 14 figures. This and related material also at http://grwav3.roma1.infn.it

VLBI observations of jupiter with the initial test station of LOFAR and the nancay decametric array

AIMS: To demonstrate and test the capability of the next generation of low-frequency radio telescopes to perform high resolution observations across intra-continental baselines. Jupiter's strong burst emission is used to perform broadband full signal cross-correlations on time intervals of up to hundreds of milliseconds. METHODS: Broadband VLBI observations at about 20 MHz on a baseline of ~50000 wavelengths were performed to achieve arcsecond angular resolution. LOFAR's Initial Test Station (LOFAR/ITS, The Netherlands) and the Nancay Decametric Array (NDA, France) digitize the measured electric field with 12 bit and 14 bit in a 40 MHz baseband. The fine structure in Jupiter's signal was used for data synchronization prior to correlation on the time-series data. RESULTS: Strong emission from Jupiter was detected during snapshots of a few seconds and detailed features down to microsecond time-scales were identified in dynamic spectra. Correlations of Jupiter's burst emission returned strong fringes on 1 ms time-scales over channels as narrow as a hundred kilohertz bandwidth. CONCLUSIONS: Long baseline interferometry is confirmed at low frequencies, in spite of phase shifts introduced by variations in ionospheric propagation characteristics. Phase coherence was preserved over tens to hundreds of milliseconds with a baseline of ~700 km. No significant variation with time was found in the correlations and an estimate for the fringe visibility of 1, suggested that the source was not resolved. The upper limit on the source region size of Jupiter Io-B S-bursts corresponds to an angular resolution of ~3 arcsec. Adding remote stations to the LOFAR network at baselines up to thousand kilometers will provide 10 times higher resolution down to an arcsecond.Comment: 6 pages, 4 figures. Nigl, A., Zarka, P., Kuijpers, J., Falcke, H., Baehren, L., VLBI observations of Jupiter with the Initial Test Station of LOFAR and the Nancay Decametric Array, A&A, 471, 1099-1104, accepted on 31/05/200

Time and Frequency Independent Manipulation of Audio in Real Time

Analog audio implies time-frequency dependence. With digitally sampled audio, this timefrequency dependence can be broken and either variable can be manipulated independently of the other, in real time. This paper will mostly focus on the frequency domain algorithm called the Phase Vocoder which breaks this time-frequency dependence. We will start by looking at Fourier Theory and the effect of discrete sampling. Then we will look at the Phase Vocoder\u27s theory of operation, as well as improvements made by Puckette, Laroche, and Dolson, to name a few. Through all of this, simple examples will be presented in order to gain intuition into the principles at hand. Towards the end, a time domain approach for time-frequency independence called Granular Synthesis will be explored. We will compare it to the Phase Vocoder, and see how our understanding of one changes how we think and make decisions for the other. Finally we will propose some ideas for further improvement to real-time time-frequency independent manipulation of audio

Theory and realization of novel algorithms for random sampling in digital signal processing

Random sampling is a technique which overcomes the alias problem in regular sampling. The randomization, however, destroys the symmetry property of the transform kernel of the discrete Fourier transform. Hence, when transforming a randomly sampled sequence to its frequency spectrum, the Fast Fourier transform cannot be applied and the computational complexity is N(^2). The objectives of this research project are (1) To devise sampling methods for random sampling such that computation may be reduced while the anti-alias property of random sampling is maintained : Two methods of inserting limited regularities into the randomized sampling grids are proposed. They are parallel additive random sampling and hybrid additive random sampling, both of which can save at least 75% of the multiplications required. The algorithms also lend themselves to the implementation by a multiprocessor system, which will further enhance the speed of the evaluation. (2) To study the auto-correlation sequence of a randomly sampled sequence as an alternative means to confirm its anti-alias property : The anti-alias property of the two proposed methods can be confirmed by using convolution in the frequency domain. However, the same conclusion is also reached by analysing in the spatial domain the auto-correlation of such sample sequences. A technique to evaluate the auto-correlation sequence of a randomly sampled sequence with a regular step size is proposed. The technique may also serve as an algorithm to convert a randomly sampled sequence to a regularly spaced sequence having a desired Nyquist frequency. (3) To provide a rapid spectral estimation using a coarse kernel : The approximate method proposed by Mason in 1980, which trades the accuracy for the speed of the computation, is introduced for making random sampling more attractive. (4) To suggest possible applications for random and pseudo-random sampling : To fully exploit its advantages, random sampling has been adopted in measurement Random sampling is a technique which overcomes the alias problem in regular sampling. The randomization, however, destroys the symmetry property of the transform kernel of the discrete Fourier transform. Hence, when transforming a randomly sampled sequence to its frequency spectrum, the Fast Fourier transform cannot be applied and the computational complexity is N"^. The objectives of this research project are (1) To devise sampling methods for random sampling such that computation may be reduced while the anti-alias property of random sampling is maintained : Two methods of inserting limited regularities into the randomized sampling grids are proposed. They are parallel additive random sampling and hybrid additive random sampling, both of which can save at least 75% , of the multiplications required. The algorithms also lend themselves to the implementation by a multiprocessor system, which will further enhance the speed of the evaluation. (2) To study the auto-correlation sequence of a randomly sampled sequence as an alternative means to confirm its anti-alias property : The anti-alias property of the two proposed methods can be confirmed by using convolution in the frequency domain. However, the same conclusion is also reached by analysing in the spatial domain the auto-correlation of such sample sequences. A technique to evaluate the auto-correlation sequence of a randomly sampled sequence with a regular step size is proposed. The technique may also serve as an algorithm to convert a randomly sampled sequence to a regularly spaced sequence having a desired Nyquist frequency. (3) To provide a rapid spectral estimation using a coarse kernel : The approximate method proposed by Mason in 1980, which trades the accuracy for the speed of the computation, is introduced for making random sampling more attractive. (4) To suggest possible applications for random and pseudo-random sampling : To fully exploit its advantages, random sampling has been adopted in measurement instruments where computing a spectrum is either minimal or not required. Such applications in instrumentation are easily found in the literature. In this thesis, two applications in digital signal processing are introduced. (5) To suggest an inverse transformation for random sampling so as to complete a two-way process and to broaden its scope of application. Apart from the above, a case study of realizing in a transputer network the prime factor algorithm with regular sampling is given in Chapter 2 and a rough estimation of the signal-to-noise ratio for a spectrum obtained from random sampling is found in Chapter 3. Although random sampling is alias-free, problems in computational complexity and noise prevent it from being adopted widely in engineering applications. In the conclusions, the criteria for adopting random sampling are put forward and the directions for its development are discussed

Window Functions and Their Applications in Signal Processing

Window functions—otherwise known as weighting functions, tapering functions, or apodization functions—are mathematical functions that are zero-valued outside the chosen interval. They are well established as a vital part of digital signal processing. Window Functions and their Applications in Signal Processing presents an exhaustive and detailed account of window functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. Comprehensively reviewing previous research and recent developments, this book: Provides suggestions on how to choose a window function for particular applications Discusses Fourier analysis techniques and pitfalls in the computation of the DFT Introduces window functions in the continuous-time and discrete-time domains Considers two implementation strategies of window functions in the time- and frequency domain Explores well-known applications of window functions in the fields of radar, sonar, biomedical signal analysis, audio processing, and synthetic aperture rada

Window Functions and Their Applications in Signal Processing

Window functions—otherwise known as weighting functions, tapering functions, or apodization functions—are mathematical functions that are zero-valued outside the chosen interval. They are well established as a vital part of digital signal processing. Window Functions and their Applications in Signal Processing presents an exhaustive and detailed account of window functions and their applications in signal processing, focusing on the areas of digital spectral analysis, design of FIR filters, pulse compression radar, and speech signal processing. Comprehensively reviewing previous research and recent developments, this book: Provides suggestions on how to choose a window function for particular applications Discusses Fourier analysis techniques and pitfalls in the computation of the DFT Introduces window functions in the continuous-time and discrete-time domains Considers two implementation strategies of window functions in the time- and frequency domain Explores well-known applications of window functions in the fields of radar, sonar, biomedical signal analysis, audio processing, and synthetic aperture rada

On the Fly Audio Processing for the Vocal Conditioning Unit

The Vocal Conditioning Unit was a device designed, constructed, and programmed as a senior design project in Electrical and Computer Engineering by Tim Lester and Grady White. The device’s intended goal was to perform a role similar to Auto-Tune, but as a standalone device similar to effects pedals used by guitarists and other musicians on stage. On-the-fly audio processing, however, was deprioritized in the design of the original device due to other design considerations. In this thesis project, the original design of the Vocal Conditioning Unit is analyzed, and critical functionalities of the device are identified. Then, the device is redesigned to perform on-the-fly audio processing using a lower end microprocessor. Finally, comparisons are made between the original design and the new design, with consideration given to the issues still existing with both designs. Several possible solutions to on-the-fly processing for the Vocal Conditioning Unit were found, and all solutions technically perform pitch detection and adjustment. However, audio quality issues exist in all solutions

Novel Techniques for Tissue Imaging and Characterization Using Biomedical Ultrasound

The use of ultrasound technology in the biomedical field has been widely increased in recent decades. Ultrasound modalities are considered more safe and cost effective than others that use ionizing radiation. Moreover, the use of high-frequency ultrasound provides means of high-resolution and precise tissue assessment. Consequently, ultrasound elastic waves have been widely used to develop non-invasive techniques for tissue assessment. In this work, ultrasound waves have been used to develop non-invasive techniques for tissue imaging and characterization in three different applications.;Currently, there is a lack of imaging modalities to accurately predict minute structures and defects in the jawbone. In particular, the inability of 2D radiographic images to detect bony periodontal defects resulted from infection of the periodontium. They also may carry known risks of cancer generation or may be limited in accurate diagnosis scope. Ultrasonic guided waves are sensitive to changes in microstructural properties, while high-frequency ultrasound has been used to reconstruct high-resolution images for tissue. The use of these ultrasound techniques may provide means for early diagnosis of marrow ischemic disorders via detecting focal osteoporotic marrow defect, chronic nonsuppurative osteomyelitis, and cavitations in the mandible (jawbone). The first part of this work investigates the feasibility of using guided waves and high frequency ultrasound for non-invasive human jawbone assessment. The experimental design and the signal/image processing procedures for each technique are developed, and multiple in vitro studies are carried out using dentate and non-dentate mandibles. Results from both the ultrasonic guided waves analysis and the high frequency 3D echodentographic imaging suggest that these techniques show great potential in providing non-invasive methods to characterize the jawbone and detect periodontal diseases at earlier stages.;The second part of this work describes indirect technique for characterization via reconstructing high-resolution microscopic images. The availability of well-defined genetic strains and the ability to create transgenic and knockout mice makes mouse models extremely significant tools in different kinds of research. For example, noninvasive measurement of cardiovascular function in mouse hearts has become a valuable need when studying the development or treatment of various diseases. This work describes the development and testing of a single-element ultrasound imaging system that can reconstruct high-resolution brightness mode (B-mode) images for mouse hearts and blood vessels that can be used for quantitative measurements in vitro. Signal processing algorithms are applied on the received ultrasound signals including filtering, focusing, and envelope detection prior to image reconstruction. Additionally, image enhancement techniques and speckle reduction are adopted to improve the image resolution and quality. The system performance is evaluated using both phantom and in vitro studies using isolated mouse hearts and blood vessels from APOE-KO and its wild type control. This imaging system shall provide a basis for early and accurate detection of different kinds of diseases such as atherosclerosis in mouse model.;The last part of this work is initialized by the increasing need for a non-invasive method to assess vascular wall mechanics. Endothelial dysfunction is considered a key factor in the development of atherosclerosis. Flow-mediated vasodilatation (FMD) measurement in brachial and other conduit arteries has become a common method to assess the endothelial function in vivo. In spite of the direct relationship that could be between the arterial wall multi-component strains and the FMD response, direct measurement of wall strain tensor due to FMD has not yet been reported in the literature. In this work, a noninvasive direct ultrasound-based strain tensor measuring (STM) technique is presented to assess changes in the mechanical parameters of the vascular wall during post-occlusion reactive hyperemia and/or FMD, including local velocities and displacements, diameter change, local strain tensor and strain rates. The STM technique utilizes sequences of B-mode ultrasound images as its input with no extra hardware requirement. The accuracy of the STM algorithm is assessed using phantom, and in vivo studies using human subjects during pre- and post-occlusion. Good correlations are found between the post-occlusion responses of diameter change and local wall strains. Results indicate the validity and versatility of the STM algorithm, and describe how parameters other than the diameter change are sensitive to reactive hyperemia following occlusion. This work suggests that parameters such as local strains and strain rates within the arterial wall are promising metrics for the assessment of endothelial function, which can then be used for accurate assessment of atherosclerosis