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Spiking neurons and synaptic stimuli: Neural response comparison using coincidence-factor (2009)
Book Chapter
Sarangdhar, M., & Kambhampati, C. (2009). Spiking neurons and synaptic stimuli: Neural response comparison using coincidence-factor. In S. Ao, & L. Gelman (Eds.), Lecture Notes in Electrical Engineering; Advances in Electrical Engineering and Computational Science (681-692). Springer Verlag. https://doi.org/10.1007/978-90-481-2311-7_58

In this chapter, neural responses are generated by changing the Inter-Spike-Interval (ISI) of the stimulus. These responses are subsequently compared and a coincidence factor is obtained. Coincidence-factor, a measure of similarity, is expected to ge... Read More about Spiking neurons and synaptic stimuli: Neural response comparison using coincidence-factor.

Predicting cardiovascular risks using pattern recognition and data mining. (2009)
Thesis
Nguyen, T. T. T. (2009). Predicting cardiovascular risks using pattern recognition and data mining. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4209582

This thesis presents the use of pattern recognition and data mining techniques into risk prediction models in the clinical domain of cardiovascular medicine. The data is modelled and classified by using a number of alternative pattern recognition and... Read More about Predicting cardiovascular risks using pattern recognition and data mining..

Quantum recurrent neural networks for filtering (2009)
Thesis
Ahamed, W. U. (2009). Quantum recurrent neural networks for filtering. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4209270

The essence of stochastic filtering is to compute the time-varying probability densityfunction (pdf) for the measurements of the observed system. In this thesis, a filter isdesigned based on the principles of quantum mechanics where the schrodinger w... Read More about Quantum recurrent neural networks for filtering.