Data transmission by pulse compression

Pulse compression techniques originated in radar.The present work is concerned with the utilization of these techniques in general, and the linear FM (LFM) technique in particular, for comnunications. It introduces these techniques from an optimum communications viewpoint and outlines their capabilities.It also considers the candidacy of the class of LFM signals for digital data transmission and the LFM spectrum. Work related to the utilization of LFM signals for digital data transmission has been mostly experimental and mainly concerned with employing two rectangular LFM pulses (or chirps) with reversed slopes to convey the bits 1 and 0 in an incoherent node.No systematic theory for LFM signal design and system performance has been available. Accordingly, the present work establishes such a theory taking into account coherent and noncoherent single-link and multiplex signalling modes. Some new results concerning the slope-reversal chirp pair are obtained. The LFM technique combines the typical capabilities of pulse compression with a relative ease of implementation. However, these merits are often hampered by the difficulty of handling the LFM spectrum which cannot generally be expressed closed-form. The common practice is to obtain a plot of this spectrum with a digital computer for every single set of LFM pulse parameters.Moreover, reported work has been Justly confined to the spectrum of an ideally rectangular chirp pulse with no rise or fall times.Accordingly, the present work comprises a systerratic study of the LFM spectrum which takes the rise and fall time of the chirp pulse into account and can accommodate any LFM pulse with any parameters.It· formulates rather simple and accurate prediction criteria concerning the behaviour of this spectrum in the different frequency regions. These criteria would facilitate the handling of the LFM technique in theory and practice.

Adaptive pulse shaping through BER Feedback

We propose a simplified approach to optical signal pre-distortion based on adaptive pulse shaping through unconventional use of a MZ modulator. The scheme allows natural tailoring of transmitted pulses by optimising the received pulse.

Sequential pyrolysis of willow SRC at low and high heating rates:implications for selective pyrolysis

The main aim of the work is to investigate sequential pyrolysis of willow SRC using two different heating rates (25 and 1500 °C/min) between 320 and 520 °C. Thermogravimetric analysis (TGA) and pyrolysis - gas chromatography - mass spectroscopy (Py-GC-MS) have been used for this analysis. In addition, laboratory scale processing has been undertaken to compare product distribution from fast and slow pyrolysis at 500 °C. Fast pyrolysis was carried out using a 1 kg/h continuous bubbling fluidized bed reactor, and slow pyrolysis using a 100 g batch reactor. Findings from this study show that heating rate and pyrolysis temperatures have a significant influence on the chemical content of decomposition products. From the analytical sequential pyrolysis, an inverse relationship was seen between the total yield of furfural (at high heating rates) and 2-furanmethanol (at low heating rates). The total yield of 1,2-dihydroxybenzene (catechol) was found to be significant higher at low heating rates. The intermediates of catechol, 2-methoxy-4-(2-propenyl)phenol (eugenol); 2-methoxyphenol (guaiacol); 4-Hydroxy-3,5-dimethoxybenzaldehyde (syringaldehyde) and 4-hydroxy-3-methoxybenzaldehyde (vanillin), were found to be highest at high heating rates. It was also found that laboratory scale processing alters the pyrolysis bio-oil chemical composition, and the proportions of pyrolysis product yields. The GC-MS/FID analysis of fast and slow pyrolysis bio-oils reveals significant differences. © 2011 Elsevier Ltd. All rights reserved.

Pulse tail suppression in laser diode output by tunable notch filter

Efficient suppression of relaxation oscillations in the output signal from an overdriven gain-switched laser diode was demonstrated. Several quantum-well distributed feedback laser diodes from different manufacturers were used for experimental analysis. A five-fold increase in the peak power was achieved for the tail-free operation. It was found that spectral filtering removed the nonlinearly chirped components resulting in pulse shortening by a factor of three.

Adaptive pulse shaping through BER Feedback

In this paper, we propose a simplified approach to optical signal predistortion based on adaptive pulse shaping through asymmetrical control of a Mach-Zehnder modulator above its switching voltage. The scheme allows natural tailoring of transmitted pulses by optimizing the received pulse. We demonstrate enhancement of the power tolerance in nonrepeated systems and improved OSNR/BER performance and dispersion tolerance in ultra-long-haul fiber systems operating at 10 Gb/s and 20 Gb/s channel rates. The improved performance is demonstrated through simulations and experiment.

Sequential grouping of pure-tone percepts evoked by the segregation of components from a complex tone

A sudden change applied to a single component can cause its segregation from an ongoing complex tone as a pure-tone-like percept. Three experiments examined whether such pure-tone-like percepts are organized into streams by extending the research of Bregman and Rudnicky (1975). Those authors found that listeners struggled to identify the presentation order of 2 pure-tone targets of different frequency when they were flanked by 2 lower frequency “distractors.” Adding a series of matched-frequency “captor” tones, however, improved performance by pulling the distractors into a separate stream from the targets. In the current study, sequences of discrete pure tones were substituted by sequences of brief changes applied to an otherwise constant 1.2-s complex tone. Pure-tone-like percepts were evoked by applying 6-dB increments to individual components of a complex comprising harmonics 1–7 of 300 Hz (Experiment 1) or 0.5-ms changes in interaural time difference to individual components of a log-spaced complex (range 160–905 Hz; Experiment 2). Results were consistent with the earlier study, providing clear evidence that pure-tone-like percepts are organized into streams. Experiment 3 adapted Experiment 1 by presenting a global amplitude increment either synchronous with, or just after, the last captor prior to the 1st distractor. In the former case, for which there was no pure-tone-like percept corresponding to that captor, the captor sequence did not aid performance to the same extent as previously. It is concluded that this change to the captor-tone stream partially resets the stream-formation process, and so the distractors and targets became likely to integrate once more. (PsycINFO Database Record (c) 2011 APA, all rights reserved)

40Gbit/s single channel dispersion managed pulse propagation in standard fibre over 509km

Error free propagation of a single polarisation optical time division multiplexed 40Gbit/s dispersion managed pulse data stream over 509km has been achieved in standard (non-dispersion shifted) fibre. Dispersion compensating fibre was used after each amplifier to reduce the high local dispersion of the standard fibre. © IEE 1999.

Experimental optimization of triangular pulse generation in normal dispersion fiber for all optical processing applications

We experimentally investigate a multi-parameter optimization of conditions for generation of triangular pulses in normal dispersion fiber. We find that triangular pulses suitable for all optical processing applications can be generated for a wide range of input pulse chirps but that triangular pulse quality and stability is improved with increased input pulse chirp.

Development of novel NMR pulse sequences

To elucidate the structures of orgamc molecules in solution using pulse FT NMR, heteronuclear pulse sequence experiments to probe carbon-13 (13C) and proton (1H) spin systems are invaluable. The one-dimensional insensitive nucleus detected PENDANT experiment finds popular use for structure determination via one-bond 13C-1H scalar couplings. PENDANT facilitates the desired increase in 13C signal-to-noise ratio, and unlike many other pulse sequence experiments (e.g., refocused INEPT and DEPT), allows the simultaneous detection of 13C quaternary nuclei. The tlrst chapter herein details the characterisation of PENDANT and the successful rectification of spectral anomalies that occur when it is used without proton broadband decoupling. Multiple-bond (long-range) l3C-1H scalar coupling correlations can yield important bonding information. When the molecule under scrutiny is devoid of proton spectral crowding, and more sensitive 'inverse' pulse sequence experiments are not available, one may use insensitive nucleus detected long-range selective one-dimensional correlation methods, rather than more time consuming and insensitive multidimensional analogues. To this end a novel long-range selective one-dimensional correlation pulse sequence experiment has been invented. Based on PENDANT, the new experiment is shown to rival the popular selective INEPT technique because it can determine the same correlations while simultaneously detecting isolated 13C quaternary nuclei. INEPT cannot facilitate this, potentially leaving other important quaternary nuclei undetected. The novel sequence has been modified further to yield a second novel experiment that simultaneously yields selective 13C transient nOe data. Consequently, the need to perform the two experiments back-to-back is conveniently removed, and the experimental time reduced. Finally, the SNARE pulse sequence was further developed. SNARE facilitates the reduction of experimental time by accelerating the relaxation of protons upon which pulse sequences, to which SNARE is appended, relies. It is shown, contrary to the original publication, that reiaxation time savings can be derived from negative nOes.

Sequential, Bayesian geostatistics:a principled method for large data sets

The principled statistical application of Gaussian random field models used in geostatistics has historically been limited to data sets of a small size. This limitation is imposed by the requirement to store and invert the covariance matrix of all the samples to obtain a predictive distribution at unsampled locations, or to use likelihood-based covariance estimation. Various ad hoc approaches to solve this problem have been adopted, such as selecting a neighborhood region and/or a small number of observations to use in the kriging process, but these have no sound theoretical basis and it is unclear what information is being lost. In this article, we present a Bayesian method for estimating the posterior mean and covariance structures of a Gaussian random field using a sequential estimation algorithm. By imposing sparsity in a well-defined framework, the algorithm retains a subset of “basis vectors” that best represent the “true” posterior Gaussian random field model in the relative entropy sense. This allows a principled treatment of Gaussian random field models on very large data sets. The method is particularly appropriate when the Gaussian random field model is regarded as a latent variable model, which may be nonlinearly related to the observations. We show the application of the sequential, sparse Bayesian estimation in Gaussian random field models and discuss its merits and drawbacks.

Projected sequential Gaussian processes: flexible interpolation for large data sets

Recently within the machine learning and spatial statistics communities many papers have explored the potential of reduced rank representations of the covariance matrix, often referred to as projected or fixed rank approaches. In such methods the covariance function of the posterior process is represented by a reduced rank approximation which is chosen such that there is minimal information loss. In this paper a sequential framework for inference in such projected processes is presented, where the observations are considered one at a time. We introduce a C++ library for carrying out such projected, sequential estimation which adds several novel features. In particular we have incorporated the ability to use a generic observation operator, or sensor model, to permit data fusion. We can also cope with a range of observation error characteristics, including non-Gaussian observation errors. Inference for the variogram parameters is based on maximum likelihood estimation. We illustrate the projected sequential method in application to synthetic and real data sets. We discuss the software implementation and suggest possible future extensions.