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.

Enticing general engineering undergrads into signal processing with Photo-Editing and image search

The University of Cambridge is unusual in that its Department of Engineering is a single department which covers virtually all branches of engineering under one roof. In their first two years of study, our undergrads study the full breadth of engineering topics and then have to choose a specialization area for the final two years of study. Here we describe part of a course, given towards the end of their second year, which is designed to entice these students to specialize in signal processing and information engineering topics for years 3 and 4. The course is based around a photo editor and an image search application, and it requires no prior knowledge of the z-transform or of 2-dimensional signal processing. It does assume some knowledge of 1-D convolution and basic Fourier methods and some prior exposure to Matlab. The subject of this paper, the photo editor, is written in standard Matlab m-files which are fully visible to the students and help them to see how specific algorithms are implemented in detail. © 2011 IEEE.

100 Gb/s uncooled WDM system using conventional WDM components and advanced receiver signal processing

We demonstrate an uncooled WDM system using standard WDM components and receiver signal processing, with a different number of receivers to transmitters, to allow wide temperature drift of the transmitter lasers. A 100 Gb/s 8-wavelength demonstrator has been developed, which proves the feasibility of the approach over 25 km of SMF. © 2012 OSA.

Degenerate mode-group division multiplexing using MIMO digital signal processing

MIMO DSP is employed to improve the performance of degenerate mode-group division multiplexing in 8 km of conventional GI-MMF. Compensation of the mode coupling, induced by the launch and propagation, between and inside each degenerate mode-group is investigated in order to reduce the DSP complexity. © 2013 IEEE.

100 Gb/s uncooled WDM system using conventional WDM components and advanced receiver signal processing

We demonstrate an uncooled WDM system using standard WDM components and receiver signal processing, with a different number of receivers to transmitters, to allow wide temperature drift of the transmitter lasers. A 100 Gb/s 8-wavelength demonstrator has been developed, which proves the feasibility of the approach over 25 km of SMF. © 2012 Optical Society of America.

Use of semiconductor optical amplifiers in signal processing applications

We describe a 42.6 Gbit/s all-optical pattern recognition system which uses semiconductor optical amplifiers (SOAs). A circuit with three SOA-based logic gates is used to identify the presence of specific port numbers in an optical packet header.