Keywords:
- (adaptive) learning rate
- (artificial) neural network
- activation function
- adalaine
- adaptive resonance theory
- adaptive steepness
- application
- architecture
- artificial neural network
- associative memory
- backpropagation
- backpropagation neural networks
- benchmarks
- bias
- bidirectional associative memory
- Boolean logic
- case study
- combinatorial optimization
- comparison of weight initialization methods
- complexity
- connectionism
- connectionist network
- construction of networks
- control
- curve fit
- data compression
- definition
- error backpropagation
- feedback network
- feedforward network
- formalization
- functional-link network
- fundamentals
- fuzzy-neural system
- gain
- generalization
- generalization performance
- hardware implementation
- high order neural network
- high order perceptron
- high order perceptrons
- high(er) order neural network
- high(er) order perceptron
- Hopfield network
- hybrid system
- image processing
- initial weight
- initial weight distribution
- initial weights
- interconnection strength
- interconnection strength distribution
- learing rate
- learning
- learning rate
- liquid crystal light valve
- liquid crystal light valve (LCLV)
- LVQ
- madalaine
- mnemonic notation
- modelling of cognitive phenomena
- multilayer neural network
- multilayer perceptron
- neocognitron
- network analysis
- network size
- network topology
- neural computation
- neural computing
- neural expert system
- neural network
- neural network classification
- neural network connectivity
- neural network determination
- neural network initialization
- neural network optimization
- neural network simulator
- neural network statics
- neural network topology
- neural-evolutionary system
- neurocomputing
- nomenclature
- non-negative neural networks
- object-oriented
- ontogenic neural network
- OpenSimulator
- optical computing
- optical implementation
- optical multilayer neural network
- optical multilayer perceptron
- optical neural network
- optimal network size
- optimality criteria
- optimization
- parameters
- pattern classification
- perceptron
- prediction
- pruning
- radial basis function
- random weight initialization
- real-world benchmark
- recurrent neural network
- self-organizing feature map
- Sesame
- sigma-pi connection
- Sigma-Pi neural network
- sigmoid steepness
- signal processing
- slope
- software implementation
- spatial light modulator
- speech processing
- standardization
- statistics
- supervised learning
- terminology
- time series analysis
- topological taxonomy
- topology
- training
- training time
- unsupervised learning
- weight discretization
- weight distribution
- weight initialization
Publications of Emile Fiesler sorted by first author
| 1 | 2 |
B
| Do Backpropagation trained neural networks have normal weight distributions?, and , in: International Conference on Artificial neural Networks, 1993 |
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| Activity Report 1996, , , , and , Idiap-Com-01-1997 |
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C
| Extended Cauchy Machines, and , in: Proceedings of the International Conference on Neural Information Processing, 1996 |
| Generalized Cauchy Machines, and , in: Neurocomputing, 1996 |
| Ontogenic High Order Cauchy Machines, and , in: Proceedings of the SIPAR Workshop '95: Parallel and Distributed Systems, Biel School of Engineering, 1995 |
E
| Non-Ontogenic Sparse Neural Networks, , and , in: Proceedings of the International Conference on Neural Networks, IEEE, IEEE, 1995 |
F
| CRC Comprehensive Dictionary of Electrical Engineering, , CRC Press, 1997 |
| Neural Network Classification and Formalization, , in: Computer Standards & Interfaces, 16(03), 1994 |
| Neural Network Formalization, , Idiap-RR-01-1992 |
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| Handbook of Neural Computation, Institute of Physics and Oxford University Press, The Computational Intelligence Library, 1996 |
| Supervised Ontogenic Networks, and , in: Handbook of Neural Computation, 1996 |
| Neural Network Topologies, , in: Handbook of Neural Computation, 1996 |
| A Connectionist System for Two-Dimensional Representation of Multivariate Location Data, and , in: Proceedings of the Fifth International Workshop on Artificial Intelligence for High Energy Physics, AIHENP, Lausanne, Switzerland, Elsevier Science, 1997 |
L
| Connectionist Quantization Functions, , and , in: Proceedings of the '96 SIPAR-Workshop on Parallel and Distributed Computing, Scientific and Parallel Computing Group, University of Geneva, Geneva, Switzerland, 1996 |
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M
| Neural Network Adaptations to Hardware Implementations, and , Idiap-RR-17-1997 |
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| Hardware-Friendly Learning Algorithms for Neural Networks: An Overview, and , in: Proceedings of the Fifth International Conference on Microelectronics for Neural Networks and Fuzzy Systems: MicroNeuro'96, EPFL and CSEM, Lausanne, Switzerland, IEEE Computer Society Press, 1996 |
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| Neural Network Adaptations to Hardware Implementations, and , in: Handbook of Neural Computation, Institute of Physics Publishing and Oxford University Publishing, 1997 |
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| Discrete All-Positive Multilayer Perceptrons for Optical Implementation, , and , in: Optical Engineering, 37(4), 1998 |
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| Discrete All-Positive Multilayer Perceptrons for Optical Implementation, , and , Idiap-RR-02-1997 |
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| Incorporation of Liquid-Crystal Light Valve Non-Linearities in Optical Multilayer Neural Networks, , and , in: Applied Optics, 35(26), 1996 |
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| Overcoming Inaccuracies in Optical Multilayer Perceptrons, , and , in: Proceedings of the First International Symposium on Neuro-Fuzzy Systems (AT'96), Lausanne, Switzerland, AATI, 1996 |
| The Effects of Optical Thresholding in Backpropagation Neural Networks, , and , in: Proceedings of the International Conference on Artificial Neural Networks (ICANN'95 and NeuroNimes'95), ENNS, Paris, France, EC2 & Cie, 1995 |
| Results on the Steepness in Backpropagation Neural Networks, , and , in: Proceedings of the '94 SIPAR-Workshop on Parallel and Distributed Computing, SI Group for Parallel Systems, 1994 |
| Neural Networks with Adaptive Learning Rate and Momentum Terms, and , Idiap-RR-04-1995 |
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| Image Classification by Neural Networks for the Quality Control of Watches, , and , Idiap-RR-10-1996 |
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| Image Classification by Neural Networks for the Quality Control of Watches, , and , in: Proceedings ISAI /IFIS 1996, ITESM, Cancun, Mexico, ITESM, 1996 |
P
| Sparse Initial Topologies for High Order Perceptrons, , and , in: Proceedings of the International Conference on Neural Networks, IEEE, 1996 |
| Boolean Logic Inspired High Order Perceptron Construction, , and , in: SIPAR Workshop'95 Parallel and Distributed Systems, SIPAR SI Group for Parallel Systems, Biel School of Engineering, Computer Science Department, 1995 |
|
S
| Adaptive Multilayer Optical Neural Network Design, and , Idiap-RR-04-1994 |
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| Optical Multilayer Perceptrons based on Liquid Crystal Devices, , , and , in: Optics and Information, Cercle SFO/SEE d'Opto-informatique, Mulhouse, France, European Optical Society (EOS), 1995 |
| An All-Optical Forward Propagation Multilayer Neural Network, and , in: From Natural to Artificial Neural Computation, Springer Verlag, 1995 |
| A Method for All-Positive Optical Multilayer Perceptrons, , and , in: Proceedings of the Third IEEE International Conference on Electronics, Circuits, and Systems, University of Patras, Rhodos, Greece, IEEE, 1996 |
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| Adaptive Multilayer Optical Neural Network with Optical Thresholding, and , in: Optical Engineering, 34(08), 1995 |
| Handwritten Digit Recognition with Binary Optical Perceptron, , , and , Idiap-RR-15-1997 |
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| An Optical Thresholding Perceptron, , , , and , in: Proceedings of the Workshop on Optics and Computer Science, Geneva, Switzerland, 1997 |
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| An Optical Thresholding Perceptron, , , , and , Idiap-RR-16-1997 |
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| Handwritten Digit Recognition with Binary Optical Perceptron, , , and , in: Proceedings of the International Conference on Artificial Neural Networks (ICANN'97), Springer-Verlag, 1997 |
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T
| Adapting the 2-Class Recursive Deterministic Perceptron Neural Network to m Classes, , , and , in: Proceedings of the International Conference on Neural Networks, IEEE, IEEE, 1997 |
| High Order and Multilayer Perceptron Initialization, and , in: IEEE Transactions on Neural Networks, 8(02), 1997 |
| Optimal Setting of Weights, Learning Rate, and Gain, and , Idiap-RR-04-1997 |
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| Pruning of Neural Networks, and , Idiap-RR-03-1997 |
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| Two neural network construction methods, and , in: Neural Processing Letters, 6(01), 1997 |
| A Boolean Approach to Construct Neural Networks for Non-Boolean Problems, and , in: Proceedings of the 8th IEEE International Conference on Tools with Artificial Intelligence, IEEE, 1996 |
| Evaluating pruning methods, and , in: 1995 International Symposium on Artificial Neural Networks (ISANN'95), 1995 |
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| High Order and Multilayer Perceptron Initialization, and , Idiap-RR-07-1994 |
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| Weight Initialization for High Order and Multilayer Perceptrons, and , in: Proceedings of the '94 SIPAR--Workshop on Parallel and Distributed Computing, SI Group for Parallel Systems, 1994 |
| Neural Network Pruning and Pruning Parameters, and , in: The 1st Workshop on Soft Computing, Dept. of Information Electronics Nagoya University, 1996 |
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| Neural Network Initialization, and , in: From Natural to Artificial Neural Computation, Springer Verlag, 1995 |
| Gain Elimination form Backpropagation Neural Networks, , and , in: Proceedings of the International Conference on Neural Networks, IEEE, Perth, IEEE, 1995 |
| Modular Object-Oriented Neural Network Simulators and Topology Generalizations, , and , in: Proceedings of the International Conference on Artificial Neural Networks (ICANN 94), Sorrento, Italy, Springer-Verlag, 1994 |
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| 1 | 2 |