22,265 research outputs found
Broadband Seismic Noise: Classification and Green\u27s Function Estimation
This thesis aims at a better understanding of the spatial and temporal variations of the amplitudes as well as the statistical properties of the (urban) seismic noise. A new statistical time series classification is presented which is used to conduct an analysis of the spatial and temporal variations of seismic noise between 8 mHz and 45 Hz in a metropolitan area. Furthermore, it is used to realise data selection approaches for the estimation of Green\u27s functions from seismic noise
A Scalable Correlator Architecture Based on Modular FPGA Hardware, Reuseable Gateware, and Data Packetization
A new generation of radio telescopes is achieving unprecedented levels of
sensitivity and resolution, as well as increased agility and field-of-view, by
employing high-performance digital signal processing hardware to phase and
correlate large numbers of antennas. The computational demands of these imaging
systems scale in proportion to BMN^2, where B is the signal bandwidth, M is the
number of independent beams, and N is the number of antennas. The
specifications of many new arrays lead to demands in excess of tens of PetaOps
per second.
To meet this challenge, we have developed a general purpose correlator
architecture using standard 10-Gbit Ethernet switches to pass data between
flexible hardware modules containing Field Programmable Gate Array (FPGA)
chips. These chips are programmed using open-source signal processing libraries
we have developed to be flexible, scalable, and chip-independent. This work
reduces the time and cost of implementing a wide range of signal processing
systems, with correlators foremost among them,and facilitates upgrading to new
generations of processing technology. We present several correlator
deployments, including a 16-antenna, 200-MHz bandwidth, 4-bit, full Stokes
parameter application deployed on the Precision Array for Probing the Epoch of
Reionization.Comment: Accepted to Publications of the Astronomy Society of the Pacific. 31
pages. v2: corrected typo, v3: corrected Fig. 1
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Modelling and extraction of fundamental frequency in speech signals
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.One of the most important parameters of speech is the fundamental frequency of vibration of voiced sounds. The audio sensation of the fundamental frequency is known as the pitch. Depending on the tonal/non-tonal category of language, the fundamental frequency conveys intonation, pragmatics and meaning. In addition the fundamental frequency and intonation carry speaker gender, age, identity, speaking style and emotional state. Accurate estimation of the fundamental frequency is critically important for functioning of speech processing applications such as speech coding, speech recognition, speech synthesis and voice morphing. This thesis makes contributions to the development of accurate pitch estimation research in three distinct ways: (1) an investigation of the impact of the window length on pitch estimation error, (2) an investigation of the use of the higher order moments and (3) an investigation of an analysis-synthesis method for selection of the best pitch value among N proposed candidates. Experimental evaluations show that the length of the speech window has a major impact on the accuracy of pitch estimation. Depending on the similarity criteria and the order of the statistical moment a window length of 37 to 80 ms gives the least error. In order to avoid excessive delay as a consequence of using a longer window, a method is proposed
ii where the current short window is concatenated with the previous frames to form a longer signal window for pitch extraction. The use of second order and higher order moments, and the magnitude difference function, as the similarity criteria were explored and compared. A novel method of calculation of moments is introduced where the signal is split, i.e. rectified, into positive and negative valued samples. The moments for the positive and negative parts of the signal are computed separately and combined. The new method of calculation of moments from positive and negative parts and the higher order criteria provide competitive results. A challenging issue in pitch estimation is the determination of the best candidate from N extrema of the similarity criteria. The analysis-synthesis method proposed in this thesis selects the pitch candidate that provides the best reproduction (synthesis) of the harmonic spectrum of the original speech. The synthesis method must be such that the distortion increases with the increasing error in the estimate of the fundamental frequency. To this end a new method of spectral synthesis is proposed using an estimate of the spectral envelop and harmonically spaced asymmetric Gaussian pulses as excitation. The N-best method provides consistent reduction in pitch estimation error. The methods described in this thesis result in a significant improvement in the pitch accuracy and outperform the benchmark YIN method
Analytical evaluation of tilting proprotor wind tunnel test requirements
Specific test requirements related to the wind tunnel testing of the XV-15 advanced tilt rotor research aircraft were determined. The following analytical tools were developed: (1) digital simulation of the XV-15, incorporating a simplified tunnel support model, control system loop, measurement lags, gust disturbances, and sensor noise, (2) specialization of existing data analysis programs to the high order XV-15 dynamical model (transfer function program, a time series analysis program, an advanced maximum likelihood parameter identification program), (3) several auxiliary programs to provide estimates of damping from transfer functions as well as calculations of model decomposition of system response. The following results were discussed: (1) modelling of the aircraft, instrumentation, and controls, (2) results of the rotor/cantilever wing model and coupled wing, (3) examples of data prediction with system identification techniques, and (4) detailed conclusions and recommendations
Non-invasive vascular assessment using photoplethysmography
Photoplethysmography (PPG) has become widely accepted as a valuable clinical tool
for performing non-invasive biomedical monitoring. The dominant clinical application
of PPG has been pulse oximetry, which uses spectral analysis of the peripheral blood
supply to establish haemoglobin saturation. PPG has also found success in screening for
venous dysfunction, though to a limited degree.
Arterial Disease (AD) is a condition where blood flow in the arteries of the body is
reduced,a condition known as ischaernia. Ischaernia can result in pain in the affected
areas, such as chest pain for an ischearnic heart, but does not always produce symptoms.
The most common form of AD is arteriosclerosis, which affects around 5% of the population over 50 years old. Arteriosclerosis, more commonly known as 'hardening of the arteries' is a condition that results in a gradual thickening, hardening and loss of
elasticity in the walls of the arteries, reducing overall blood flow. This thesis investigates the possibility of employing PPG to perform vascular assessment, specifically arterial assessment, in two ways. PPG based perfusion monitoring may allow identification of ischaernia in the periphery. To further investigate this premise, prospective experimental trials are performed, firstly to assess the viability of PPG based perfusion monitoring and culminating in the development of
a more objective method for determining ABPI using PPG based vascular assessment. A complex interaction between the heart and the connective vasculature, detected at the
measuring site, generates the PPG signal. The haemodynamic properties of the
vasculature will affect the shape of the PPG waveform, characterising the PPG signal
with the properties of the intermediary vasculature. This thesis investigates the
feasibility of deriving quantitative vascular parameters from the PPG signal. A
quantitative approach allows direct identification of pathology, simplifying vascular assessment. Both forward and inverse models are developed in order to investigate this topic. Application of the models in prospective experimental trials with both normal subjects and subjects suffering PVD have shown encouraging results.
It is concluded that the PPG signal contains information on the connective vasculature
of the subject. PPG may be used to perform vascular assessment using either perfusion based techniques, where the magnitude of the PPG signal is of interest, or by directly
assessing the connective vasculature using PPG, where the shape of the PPG signal is of
interest.
it is argued that PPG perfusion based techniques for performing the ABPI diagnosis
protocol can offer greater sensitivity to the onset of PAD, compared to more
conventional methods. It is speculated that the PPG based ABPI diagnosis protocol
could provide enhanced PAD diagnosis, detecting the onset of the disease and allowing a treatmenpt lan to be formed soonert han was possible previously. The determination of quantitative vascular parameters using PPG shape could allow
direct vascular diagnosis, reducing subjectivity due to interpretation. The prospective trials investigating PPG shape analysis concentrated on PVD diagnosis, but it is speculated that quantitative PPG shaped based vascular assessment could be a powerful tool in the diagnosis of many vascular based pathological conditions
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Technical Review of Residential Programmable Communicating Thermostat Implementation for Title 24-2008
THE APPLICATION OF REAL-TIME SOFTWARE IN THE IMPLEMENTATION OF LOW-COST SATELLITE RETURN LINKS
Digital Signal Processors (DSPs) have evolved to a level where it is feasible
for digital modems with relatively low data rates to be implemented entirely with
software algorithms. With current technology it is still necessary for analogue
processing between the RF input and a low frequency IF but, as DSP technology
advances, it will become possible to shift the interface between analogue and digital
domains ever closer towards the RF input. The software radio concept is a long-term
goal which aims to realise software-based digital modems which are completely
flexible in terms of operating frequency, bandwidth, modulation format and source
coding. The ideal software radio cannot be realised until DSP, Analogue to Digital
(A/D) and Digital to Analogue (D/A) technology has advanced sufficiently. Until
these advances have been made, it is often necessary to sacrifice optimum
performance in order to achieve real-time operation. This Thesis investigates practical
real-time algorithms for carrier frequency synchronisation, symbol timing
synchronisation, modulation, demodulation and FEC. Included in this work are novel
software-based transceivers for continuous-mode transmission, burst-mode
transmission, frequency modulation, phase modulation and orthogonal frequency
division multiplexing (OFDM).
Ideal applications for this work combine the requirement for flexible baseband
signal processing and a relatively low data rate. Suitable applications for this work
were identified in low-cost satellite return links, and specifically in asymmetric
satellite Internet delivery systems. These systems employ a high-speed (>>2Mbps)
DVB channel from service provider to customer and a low-cost, low-speed (32-128
kbps) return channel. This Thesis also discusses asymmetric satellite Internet delivery
systems, practical considerations for their implementation and the techniques that are
required to map TCP/IP traffic to low-cost satellite return links
Access Windows by Iris Recognition
This project aims to design and develop an iris recognition system for accessing Microsoft Windows. The system is built using digital camera and Pentium 4 with SVGA display adapter. MATLAB ver. 7.0 is used to preprocess the taken images convert the images into code and compare the picture code with the stored database. The project involves two main steps: (1) applying image processing techniques on the picture of an eye for data acquisition. (2)applying Neural Networks techniques for identification .The image processing techniques display the steps for getting a very clear iris image necessary for extracting data from the acquisition of eye image in standard lighting and focusing. In a use of your images, the images are enhanced and segmented into 100 parts. The standard deviation is computed for every part in which the values are used for identification using NN techniques. Locating the iris is done by following the darkness density of the pupil. For all networks, the weights and output values are stored in a text file to be used later in identification. The Backprobagation network succeeded in identification and getting best results because it attained to (False Acceptance Rate = 10% - False Rejection Rate = 10%), while the Linear Associative Memory network attained to (False Acceptance Rate = 20% - False Rejection Rate = 20%
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