Bayesian approach to signal modelling

In this paper, an introduction to Bayesian methods in signal processing will be given. The paper starts by considering the important issues of model selection and parameter estimation and derives analytic expressions for the model probabilities of two simple models. The idea of marginal estimation of certain model parameter is then introduced and expressions are derived for the marginal probability densities for frequencies in white Gaussian noise and a Bayesian approach to general changepoint analysis is given. Numerical integration methods are introduced based on Markov chain Monte Carlo techniques and the Gibbs sampler in particular.

Technique for wavelength converting a 2.488 Gb/s signal whilst simultaneously monitoring and replacing a wavelength identifying pilot tone

A wavelength conversion device was demonstrated at the bit rate of 2.488 Gb/s with 2R (reamplification and reshaping) regenerative properties. A low frequency pilot tone was removed during the conversion process and a new one added. The wavelength converter is shown to operate well at 10 Gb/s, and tone identification/replacement should also be possible at this data rate.

Quality enhancement of a WDM signal using dispersion-imbalanced loop mirror

The nonlinear filtering of a 10Gb/s data stream in a dispersion-imbalanced fibre loop mirror has been demonstrated over a wide spectral range of 28nm. A relative extinction ratio of - 30 dB for the cw background has been achieved across the whole spectral range.

The Bayesian Approach to Signal Modelling

In this paper, an introduction to Bayesian methods in signal processing will be given. The paper starts by considering the important issues of model selection and parameter estimation and derives analytic expressions for the model probabilities of two simple models. The idea of marginal estimation of certain model parameter is then introduced and expressions are derived for the marginal probabilitiy densities for frequencies in white Gaussian noise and a Bayesian approach to general changepoint analysis is given. Numerical integration methods are introduced based on Markov chain Monte Carlo techniques and the Gibbs sampler in particular.

Molecular evolution of CXCR1, a G protein-coupled receptor involved in signal transduction of neutrophils

Human neutrophils are a type of white blood cell, which forms an early line of defense against bacterial infections. Neutrophils are highly responsive to the chemokine, interleukin-8 (IL-8) due to the abundant distribution of CXCR1, one of the IL-8 receptors on the neutrophil cell surface. As a member of the GPCR family, CXCR1 plays a crucial role in the IL-8 signal transduction pathway in neutrophils. We sequenced the complete coding region of the CXCR1 gene in worldwide human populations and five representative nonhuman primate species. Our results indicate accelerated protein evolution in the human lineage, which was likely caused by Darwinian positive selection. The sliding window analysis and the codon-based neutrality test identified signatures of positive selection at the N-terminal ligand/receptor recognition domain of human CXCR1.

Bayesian signal processing

The application of Bayes' Theorem to signal processing provides a consistent framework for proceeding from prior knowledge to a posterior inference conditioned on both the prior knowledge and the observed signal data. The first part of the lecture will illustrate how the Bayesian methodology can be applied to a variety of signal processing problems. The second part of the lecture will introduce the concept of Markov Chain Monte-Carlo (MCMC) methods which is an effective approach to overcoming many of the analytical and computational problems inherent in statistical inference. Such techniques are at the centre of the rapidly developing area of Bayesian signal processing which, with the continual increase in available computational power, is likely to provide the underlying framework for most signal processing applications.

TOPS (Task optimization in the presence of signal-dependent noise) model

This paper proposes a movement trajectory planning model, which is a maximum task achievement model in which signal-dependent noise is added to the movement command. In the proposed model, two optimization criteria are combined, maximum task achievement and minimum energy consumption. The proposed model has the feature that the end-point boundary conditions for position, velocity, and acceleration need not be prespecified. Consequently, the method can be applied not only to the simple point-to-point movement, but to any task. In the method in this paper, the hand trajectory is derived by a psychophysical experiment and a numerical experiment for the case in which the target is not stationary, but is a moving region. It is shown that the trajectory predicted from the minimum jerk model or the minimum torque change model differs considerably from the results of the psychophysical experiment. But the trajectory predicted from the maximum task achievement model shows good qualitative agreement with the hand trajectory obtained from the psychophysical experiment. © 2004 Wiley Periodicals, Inc.

Extraction, PCR amplification, and sequencing of mitochondrial DNA from scent mark and feces in the giant panda

To expand the feasibility of applying simple, efficient, non-invasive DNA preparation methods using samples that can be obtained from giant pandas living in the wild, we investigated the use of scent markings and fecal samples. Giant panda-specific oligonucleotide primers were used to amplify a portion of the mitochondrial DNA control region as well as a portion of the mitochondrial DNA cytochrome b gene and tRNA(Thr) gene region. A 196 base pair (bp) fragment in the control region and a 449 bp fragment in the cytochrome b gene and tRNA(Thr) gene were successfully amplified. Sequencing of polymerase chain reaction (PCR) products demonstrated that the two fragments are giant panda sequences. Furthermore, under simulated field conditions we found that DNA can be extracted from fecal samples aged as long as 3 months. Our results suggest that the scent mark and fecal samples are simple, efficient, and easily prepared DNA sources. (C) 1998 Wiley-Liss, Inc.

Detection of usual and atypical aldehyde dehydrogenase alleles by mismatch amplification mutation assay

The genotypes of liver mitochondrial high-affinity aldehyde dehydrogenase-2 (ALDH2) are strongly associated with the drinking behavior and the alcohol liver diseases, since the individuals with atypical ALDH(2)(2) allele have higher levels of acetaldehyde in their plasma. The atypical ALDH(2)(2) allele has a nucleotide base transition (G-->A) in its exon 12. Based on this point mutation, we developed a rapid, reliable and inexpensive method, mismatch amplification mutation assay (MAMA), for the determination of human ALDH2 usual and atypical alleles. Two pairs of primers were designed for the amplification of the usual ALDH(2)(1) allele and the atypical ALDH(2)(2) allele, respectively. If the sample for the detection was heterozygous, it could be amplified by both of the primers. The product of polymerase chain reaction (PCR) of ALDH2 exon 12 could be easily screened by electrophoresis on a 2% agarose gel. The results of the MAMA method were further confirmed by sequencing. In the total of fifty samples from unrelated healthy Chinese Han people from Wuhan, China, the frequency of atypical ALDH(2)(2) allele was found to be 12%.

Transmission performance of adaptively modulated optical OFDM modems using subcarrier modulation over SMF IMDD links for access and metropolitan area networks.

Detailed investigations are undertaken, for the first time, of the transmission performance of recently proposed novel Adaptively Modulated Optical OFDM (AMOOFDM) modems using Subcarrier Modulation (AMOOFDM-SCM) in single-channel, SMF-based IMDD links without optical amplification and chromatic dispersion compensation. The cross-talk effect induced by beatings among subcarriers of various types is a crucial factor limiting the maximum achievable AMOOFDM-SCM performance. By applying single sideband modulation and/or spectral gapping to AMOOFDM-SCM, three AMOOFDM-SCM designs of varying complexity are proposed, which achieve >60Gb/s signal transmission over 20 km, 40 km and 60 km. Such performances are >1.5 times higher than those supported by conventional AMOOFDM modems.

Colourless adaptively modulated optical OFDM transmitters using SOAs as intensity modulators.

The wavelength dependent transmission performance of adaptively modulated optical OFDM (AMOOFDM) signals is investigated, for the first time, over optical amplification- and chromatic dispersion compensation-free IMDD SMF systems using semiconductor optical amplifiers (SOAs) as intensity modulators. A theoretical SOA model describing both optical gain saturation and gain spectral dynamics is developed, based on which optimum SOA operating conditions are identified for various wavelengths varying in a broad range of 1510 nm- 1590 nm. Results show that, SOA intensity modulators operating at the identified optimum conditions enable the realization of colourless AMOOFDM transmitters within the aforementioned wavelength window. Such transmitters are capable of supporting >30 Gb/s signal transmission over 60 km SMFs.