Direct support and general support maintenance manual : translator, signal data CV-3098/G (NSN 5895-00-237-2472) for satellite communication terminal AN/FSC-78(V).

"June 1978."

High-resolution spatial processing in underwater acoustics /

Mode of access: Internet.

Closed-Loop Deep Brain Stimulation: Bidirectional Neuroprosthetics for Tremor and BCI

Thesis (Ph.D.)--University of Washington, 2016-06

Pitch jump probability measures for the analysis of snoring sounds in apnea

Obstructive sleep apnea (OSA) is a highly prevalent disease in which upper airways are collapsed during sleep, leading to serious consequences. The gold standard of diagnosis, called polysomnography (PSG), requires a full-night hospital stay connected to over ten channels of measurements requiring physical contact with sensors. PSG is inconvenient, expensive and unsuited for community screening. Snoring is the earliest symptom of OSA, but its potential in clinical diagnosis is not fully recognized yet. Diagnostic systems intent on using snore-related sounds (SRS) face the tough problem of how to define a snore. In this paper, we present a working definition of a snore, and propose algorithms to segment SRS into classes of pure breathing, silence and voiced/unvoiced snores. We propose a novel feature termed the 'intra-snore-pitch-jump' (ISPJ) to diagnose OSA. Working on clinical data, we show that ISPJ delivers OSA detection sensitivities of 86-100% while holding specificity at 50-80%. These numbers indicate that snore sounds and the ISPJ have the potential to be good candidates for a take-home device for OSA screening. Snore sounds have the significant advantage in that they can be conveniently acquired with low-cost non-contact equipment. The segmentation results presented in this paper have been derived using data from eight patients as the training set and another eight patients as the testing set. ISPJ-based OSA detection results have been derived using training data from 16 subjects and testing data from 29 subjects.

Detecting finite bandwidth periodic signals in stationary noise using the signal coherence spectrum

All signals that appear to be periodic have some sort of variability from period to period regardless of how stable they appear to be in a data plot. A true sinusoidal time series is a deterministic function of time that never changes and thus has zero bandwidth around the sinusoid's frequency. A zero bandwidth is impossible in nature since all signals have some intrinsic variability over time. Deterministic sinusoids are used to model cycles as a mathematical convenience. Hinich [IEEE J. Oceanic Eng. 25 (2) (2000) 256-261] introduced a parametric statistical model, called the randomly modulated periodicity (RMP) that allows one to capture the intrinsic variability of a cycle. As with a deterministic periodic signal the RMP can have a number of harmonics. The likelihood ratio test for this model when the amplitudes and phases are known is given in [M.J. Hinich, Signal Processing 83 (2003) 1349-13521. A method for detecting a RMP whose amplitudes and phases are unknown random process plus a stationary noise process is addressed in this paper. The only assumption on the additive noise is that it has finite dependence and finite moments. Using simulations based on a simple RMP model we show a case where the new method can detect the signal when the signal is not detectable in a standard waterfall spectrograrn display. (c) 2005 Elsevier B.V. All rights reserved.

Recent developments in all-optical nonlinear data processing

Photonic technologies for data processing in the optical domain are expected to play a major role in future high-speed communications. Nonlinear effects in optical fibres have many attractive features and great, but not yet fully explored potential for optical signal processing. Here we provide an overview of our recent advances in developing novel techniques and approaches to all-optical processing based on fibre nonlinearities.

Exploiting sensitivity of nonorthogonal joint diagonalisation as a security mechanism in steganography

We have recently proposed the framework of independent blind source separation as an advantageous approach to steganography. Amongst the several characteristics noted was a sensitivity to message reconstruction due to small perturbations in the sources. This characteristic is not common in most other approaches to steganography. In this paper we discuss how this sensitivity relates the joint diagonalisation inside the independent component approach, and reliance on exact knowledge of secret information, and how it can be used as an additional and inherent security mechanism against malicious attack to discovery of the hidden messages. The paper therefore provides an enhanced mechanism that can be used for e-document forensic analysis and can be applied to different dimensionality digital data media. In this paper we use a low dimensional example of biomedical time series as might occur in the electronic patient health record, where protection of the private patient information is paramount.

The application of parallel processing methods to vibrational analysis

The trend in modal extraction algorithms is to use all the available frequency response functions data to obtain a global estimate of the natural frequencies, damping ratio and mode shapes. Improvements in transducer and signal processing technology allow the simultaneous measurement of many hundreds of channels of response data. The quantity of data available and the complexity of the extraction algorithms make considerable demands on the available computer power and require a powerful computer or dedicated workstation to perform satisfactorily. An alternative to waiting for faster sequential processors is to implement the algorithm in parallel, for example on a network of Transputers. Parallel architectures are a cost effective means of increasing computational power, and a larger number of response channels would simply require more processors. This thesis considers how two typical modal extraction algorithms, the Rational Fraction Polynomial method and the Ibrahim Time Domain method, may be implemented on a network of transputers. The Rational Fraction Polynomial Method is a well known and robust frequency domain 'curve fitting' algorithm. The Ibrahim Time Domain method is an efficient algorithm that 'curve fits' in the time domain. This thesis reviews the algorithms, considers the problems involved in a parallel implementation, and shows how they were implemented on a real Transputer network.

Sparse signal representation by adaptive non-uniform B-spline dictionaries on a compact interval

Non-uniform B-spline dictionaries on a compact interval are discussed in the context of sparse signal representation. For each given partition, dictionaries of B-spline functions for the corresponding spline space are built up by dividing the partition into subpartitions and joining together the bases for the concomitant subspaces. The resulting slightly redundant dictionaries are composed of B-spline functions of broader support than those corresponding to the B-spline basis for the identical space. Such dictionaries are meant to assist in the construction of adaptive sparse signal representation through a combination of stepwise optimal greedy techniques.

Nonlinear pulse shaping in fibres for pulse generation and optical processing

The development of new all-optical technologies for data processing and signal manipulation is a field of growing importance with a strong potential for numerous applications in diverse areas of modern science. Nonlinear phenomena occurring in optical fibres have many attractive features and great, but not yet fully explored, potential in signal processing. Here, we review recent progress on the use of fibre nonlinearities for the generation and shaping of optical pulses and on the applications of advanced pulse shapes in all-optical signal processing. Amongst other topics, we will discuss ultrahigh repetition rate pulse sources, the generation of parabolic shaped pulses in active and passive fibres, the generation of pulses with triangular temporal profiles, and coherent supercontinuum sources. The signal processing applications will span optical regeneration, linear distortion compensation, optical decision at the receiver in optical communication systems, spectral and temporal signal doubling, and frequency conversion. © Copyright 2012 Sonia Boscolo and Christophe Finot.

Phase discrimination and simultaneous frequency conversion of the orthogonal components of an optical signal by four-wave mixing in an SOA

Simultaneous conversion of the two orthogonal phase components of an optical input to different output frequencies has been demonstrated by simulation and experiment. A single stage of four-wave mixing between the input signal and four pumps derived from a frequency comb was employed. The nonlinear device was a semiconductor optical amplifier, which provided overall signal gain and sufficient contrast for phase sensitive signal processing. The decomposition of a quadrature phase-shift keyed signal into a pair of binary phase-shift keyed outputs at different frequencies was also demonstrated by simulation.

Full-field electronic dispersion compensation of a 10 Gbit/s OOK signal over 4 x 124 km field-installed single-mode fibre

We experimentally demonstrate the use of full-field electronic dispersion compensation (EDC) to achieve a bit error rate of 5 x 10(-5) at 22.3 dB optical signal-to-noise ratio for single-channel 10 Gbit/s on-off keyed signal after transmission over 496 km field-installed single-mode fibre with an amplifier spacing of 124 km. This performance is achieved by designing the EDC so as to avoid electronic amplification of the noise content of the signal during full-field reconstruction. We also investigate the tolerance of the system to key signal processing parameters, and numerically demonstrate that single-channel 2160 km single mode fibre transmission without in-line optical dispersion compensation can be achieved using this technique with 80 km amplifier spacing and optimized system parameters.

Photonic processing for wideband cancellation and spectral discrimination of RF signals

Photonic signal processing is used to implement common mode signal cancellation across a very wide bandwidth utilising phase modulation of radio frequency (RF) signals onto a narrow linewidth laser carrier. RF spectra were observed using narrow-band, tunable optical filtering using a scanning Fabry Perot etalon. Thus functions conventionally performed using digital signal processing techniques in the electronic domain have been replaced by analog techniques in the photonic domain. This technique was able to observe simultaneous cancellation of signals across a bandwidth of 1400 MHz, limited only by the free spectral range of the etalon. © 2013 David M. Benton.

Optical information capacity processing

The never-stopping increase in demand for information transmission capacity has been met with technological advances in telecommunication systems, such as the implementation of coherent optical systems, advanced multilevel multidimensional modulation formats, fast signal processing, and research into new physical media for signal transmission (e.g. a variety of new types of optical fibers). Since the increase in the signal-to-noise ratio makes fiber communication channels essentially nonlinear (due to the Kerr effect for example), the problem of estimating the Shannon capacity for nonlinear communication channels is not only conceptually interesting, but also practically important. Here we discuss various nonlinear communication channels and review the potential of different optical signal coding, transmission and processing techniques to improve fiber-optic Shannon capacity and to increase the system reach.