A neural cocktail-party processor
Biological Cybernetics
Associative recognition and storage in a model network of physiological Neurons
Biological Cybernetics
Two tapes are better than one for off-line Turing machines
STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Non-Boltzmann dynamics in networks of spiking neurons
Advances in neural information processing systems 2
Associative memory in a network of biological neurons
NIPS-3 Proceedings of the 1990 conference on Advances in neural information processing systems 3
The computational brain
On the computational power of neural nets
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Bounds for the computational power and learning complexity of analog neural nets
STOC '93 Proceedings of the twenty-fifth annual ACM symposium on Theory of computing
Threshold circuits of bounded depth
Journal of Computer and System Sciences
Neural nets with superlinear VC-dimension
Neural Computation
Circuits of the mind
Vapnik-Chervonenkis dimension of neural networks
The handbook of brain theory and neural networks
Elements of the Theory of Computation
Elements of the Theory of Computation
Analogue Neural VLSI: A Pulse Stream Approach
Analogue Neural VLSI: A Pulse Stream Approach
Introduction to Automata Theory, Languages, and Computation (3rd Edition)
Introduction to Automata Theory, Languages, and Computation (3rd Edition)
VC dimension of an integrate-and-fire neuron model
COLT '96 Proceedings of the ninth annual conference on Computational learning theory
On the effect of analog noise in discrete-time analog computations
Neural Computation
On the relevance of time in neural computation and learning
Theoretical Computer Science
Analogue VLSI Leaky Integrate-and-Fire Neurons and Their Use in a Sound Analysis System
Analog Integrated Circuits and Signal Processing
On computing Boolean functions by a spiking neuron
Annals of Mathematics and Artificial Intelligence
Learning Temporally Encoded Patterns in Networks of SpikingNeurons
Neural Processing Letters
Spiking neurons and the induction of finite state machines
Theoretical Computer Science - Natural computing
On the Computational Power of Neural Microcircuit Models: Pointers to the Literature
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Sequence Learning - Paradigms, Algorithms, and Applications
Using Analogue Vlsi Leaky Integrate-and-Fire Neurons in a Sound Analysis System.
MICRONEURO '99 Proceedings of the 7th International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems
Learning Beyond Finite Memory in Recurrent Networks of Spiking Neurons
Neural Computation
Spiking neural nets with symbolic internal state
Information Processing Letters - Special issue on applications of spiking neural networks
Parallel computation in spiking neural nets
Theoretical Computer Science
Vc dimension of an integrate-and-fire neuron model
Neural Computation
Validation testing of temporal neural networks for RBF recognition
EHAC'05 Proceedings of the 4th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications
Improved spiking neural networks for EEG classification and epilepsy and seizure detection
Integrated Computer-Aided Engineering
Spike-timing error backpropagation in theta neuron networks
Neural Computation
Adaptive synchronization of activities in a recurrent network
Neural Computation
Obstacle to training SpikeProp networks: cause of surges in training process
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Spiking neural nets with symbolic internal state
Information Processing Letters - Special issue on applications of spiking neural networks
Learning beyond finite memory in recurrent networks of spiking neurons
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Accelerating event based simulation for multi-synapse spiking neural networks
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Temporal data encoding and sequencelearning with spiking neural networks
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
Spike-timing-dependent construction
Neural Computation
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We investigate the computational power of a formal model for networks of spiking neurons. It is shown that simple operations on phase differences between spike-trains provide a very powerful computational tool that can in principle be used to carry out highly complex computations on a small network of spiking neurons. We construct networks of spiking neurons that simulate arbitrary threshold circuits, Turing machines, and a certain type of random access machines with real valued inputs. We also show that relatively weak basic assumptions about the response and threshold functions of the spiking neurons are sufficient to employ them for such computations.