Learning in the recurrent random neural network
Neural Computation
G-networks with multiple classes of negative and positive customers
Theoretical Computer Science
Traffic and video quality with adaptive neural compression
Multimedia Systems - Special issue on multimedia networking
Random neural networks with multiple classes of signals
Neural Computation
On Approximate Computer System Models
Journal of the ACM (JACM)
On the Optimum Checkpoint Interval
Journal of the ACM (JACM)
Minimizing wasted space in partitioned segmentation
Communications of the ACM
The distribution of a program in primary and fast buffer storage
Communications of the ACM
Performance Evaluation
A Probability Model of Uncertainty in Data Bases
Proceedings of the Second International Conference on Data Engineering
A Unified Approach to the Evaluation of a Class of Replacement Algorithms
IEEE Transactions on Computers
Video quality and traffic QoS in learning-based subsampled and receiver-interpolated video sequences
IEEE Journal on Selected Areas in Communications
Function approximation with spiked random networks
IEEE Transactions on Neural Networks
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This is Part I of an interview with Professor Erol Gelenbe, conducted by Professor Cristian Calude. Gelenbe holds the Dennis Gabor Chair Professorship in the Electrical and Electronic Engineering Department at Imperial College London and is an associate editor for this publication. This interview also appeared in the October 2010 issue of the Bulletin of the European Association for Computer Science and is printed here with permission. --Editor