Webb, 1998 - Google Patents
Temporal Pattern Learning in a Spiking Neuron ChainWebb, 1998
- Document ID
- 16473802508700061875
- Author
- Webb B
- Publication year
- Publication venue
- From Animals to Animats 5: Proceedings of the Fifth International Conference on Simulation of Adaptive Behavior
External Links
Snippet
Matt Southall: mjs@ psychology. nottingham. ac. uk, Ext. 18311 Tom Scutt: Tom. Scutt@ nottingham. ac. uk Barbara Webb: Barbara. Webb@ nottingham. ac. uk Ext 15295 A simple neural network demonstrates the ability to learn Morse code-like temporal patterns …
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/08—Learning methods
- G06N3/082—Learning methods modifying the architecture, e.g. adding or deleting nodes or connections, pruning
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/06—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
- G06N3/063—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means
- G06N3/0635—Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons using electronic means using analogue means
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
- G06N3/049—Temporal neural nets, e.g. delay elements, oscillating neurons, pulsed inputs
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computer systems based on biological models
- G06N3/02—Computer systems based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
- G06N3/0472—Architectures, e.g. interconnection topology using probabilistic elements, e.g. p-rams, stochastic processors
Similar Documents
Publication | Publication Date | Title |
---|---|---|
KR100567465B1 (en) | Dynamic Synapses for Signal Processing in Neural Networks | |
Bohte | The evidence for neural information processing with precise spike-times: A survey | |
US8849735B2 (en) | Solving the distal reward problem through linkage of STDP and dopamine signaling | |
Ruf et al. | Learning temporally encoded patterns in networks of spiking neurons | |
JP2016538632A (en) | Method and apparatus for tagging a class using supervised learning | |
Ryckebusch et al. | Modeling small oscillating biological networks in analog VLSI | |
Hoshino et al. | Role of itinerancy among attractors as dynamical map in distributed coding scheme | |
Scutt et al. | Designing a nervous system for an adaptive mobile robot | |
Wallis | Spatio-temporal influences at the neural level of object recognition | |
Maass | On the relevance of time in neural computation and learning | |
Alstrøm et al. | Versatility and adaptive performance | |
Webb | Temporal Pattern Learning in a Spiking Neuron Chain | |
Maass et al. | Theory of the computational function of microcircuit dynamics | |
Cataldo et al. | Computational model of a central pattern generator | |
Zakharov | Information capacity of a neural network with redundant connections between neurons | |
Alnajjar et al. | A simple aplysia-like spiking neural network to generate adaptive behavior in autonomous robots | |
Buhmann et al. | Influence of noise on the behaviour of an autoassociative neural network | |
González-Nalda et al. | Topos: Spiking neural networks for temporal pattern recognition in complex real sounds | |
Soule et al. | Evolving a strongly recurrent neural network to simulate biological neurons | |
Kupfermann et al. | The use of genetic algorithms to explore neural mechanisms that optimize rhythmic behaviors: Quasi-realistic models of feeding behavior in Aplysia | |
Jimenez-Romero | A Heterosynaptic Spiking Neural System for the Development of Autonomous Agents | |
Kiselev | Statistical approach to unsupervised recognition of spatio-temporal patterns by spiking neurons | |
Rowe | Neural networks: a bridge between neuroscience and psychology | |
Webb | Spiking neuron controllers for a sound localising robot | |
SU1672482A1 (en) | Neurons simulators |