Hop selection in peer-to-peer WPAN networks

Currently, wireless technology is revolutionizing the way we share information and communicate. The demands for mobility have made wireless technology the primary source for voice communication. Code-division multiple-access (CDMA) is a very popular spread spectrum application due to its claims of low transmission power, higher system capacity, ability to mitigate multipath fading and user interference. In that case, frequency-hopping code-division multiple access (FH-CDMA) has received considerable attention over the past few years. This technique will allow a better performance over a fading channel, message privacy, and immunity to narrowband interference. This paper addresses the characteristics of FH-CDMA in WPAN networks, with an emphasis on frequency-hopped Bluetooth systems. A performance evaluation of FH-CDMA is discussed and simulated. The analysis shows the interaction between the designed parameters and their effect on the network system. Most specifically, the FH-CDMA scheme provides frequency and temporal diversity to combat the effects of interference.

Representation and learning of visual information for pose recognition

Recovering position from sensor information is an important problem in mobile robotics, known as localisation. Localisation requires a map or some other description of the environment to provide the robot with a context to interpret sensor data. The mobile robot system under discussion is using an artificial neural representation of position. Building a geometrical map of the environment with a single camera and artificial neural networks is difficult. Instead it would be simpler to learn position as a function of the visual input. Usually when learning images, an intermediate representation is employed. An appropriate starting point for biologically plausible image representation is the complex cells of the visual cortex, which have invariance properties that appear useful for localisation. The effectiveness for localisation of two different complex cell models are evaluated. Finally the ability of a simple neural network with single shot learning to recognise these representations and localise a robot is examined.

Proceedings of the Eighth Australian and New Zealand Intelligent Information Systems Conference

These are the full proceedings of the conference.