Research Repository

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A high fidelity tissue-based cardiac surgical simulator (2005)
Journal Article
Ramphal, P. S., Coore, D. N., Craven, M. P., Forbes, N. F., Newman, S. M., Coye, A. A., …Silvera, B. C. (2005). A high fidelity tissue-based cardiac surgical simulator. European Journal of Cardio-Thoracic Surgery, 27(5), 910-916. doi:10.1016/j.ejcts.2004.12.049

Issues concerning the training and certification of surgical specialists have taken on great significance in the last decade. A realistic computer-assisted, tissue-based simulator developed for use in the training of cardiac surgical residents in the... Read More

Consideration of multiplexing in neural network hardware (1994)
Journal Article
Craven, M., Curtis, K., & Hayes-Gill, B. (1994). Consideration of multiplexing in neural network hardware. IEE Proceedings Circuits Devices and Systems, 141(3), 237-240. doi:10.1049/ip-cds:19941103

This paper presents the results of research into a scheme for overcoming the communications 'bottleneck' within hardware neural networks, utilising frequency division multiplexing of amplitude modulated neural signals. The introduction explains the p... Read More

Two quadrant analogue squarer circuit based on MOS square-law characteristic (1991)
Journal Article
Craven, M., & Hayes-Gill, B. (1991). Two quadrant analogue squarer circuit based on MOS square-law characteristic. Electronics Letters, 27(25), 2307–2308. doi:10.1049/el:19911429

A novel analogue CMOS circuit is presented which performs the arithmetical squaring of a voltage, using the square-law characteristic of the MOS transistor in saturation. The core circuit is constructed from four identical building blocks, which are... Read More

Frequency division multiplexing in analogue neural network (1991)
Journal Article
Hayes-Gill, B., & Craven, M. (1991). Frequency division multiplexing in analogue neural network. Electronics Letters, 27(11), 918-920. doi:10.1049/el:19910575

Frequency division multiplexing has been studied as a means of communication between neural layers in an analogue multilayered perceptron neural network architecture, trained using the back-propagation learning algorithm. Simulation results on networ... Read More