POLLACK, 1993 - Google Patents
High-level connectionist models(Final Report)POLLACK, 1993
- Document ID
- 14732291908414974045
- Author
- POLLACK J
- Publication year
External Links
- 230000006399 behavior 0 abstract description 4
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
- G06N3/04—Architectures, e.g. interconnection topology
-
- 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
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Pham et al. | NEURAL N€ IWORKS FOR IDENTIFICATION, PREDICTION AND CONTROL | |
Churchland | Cognitive activity in artificial neural networks | |
Pomerleau et al. | Neural network simulation at Warp speed: How we got 17 million connections per second | |
Berke et al. | Applications of artificial neural nets in structural mechanics | |
US5056037A (en) | Analog hardware for learning neural networks | |
POLLACK | High-level connectionist models(Final Report) | |
AU7413000A (en) | Method for training a neural network | |
Adamson et al. | A recurrent network that learns to pronounce English text | |
DK0935212T3 (en) | n-tuple or RAM based neural network classification system and method | |
Puskorius et al. | Extensions and enhancements of decoupled extended Kalman filter training | |
Jacobs et al. | A modular connectionist architecture for learning piecewise control strategies | |
Dumek et al. | Novel approaches to the IHCP: neural networks and expert systems | |
CA2318502A1 (en) | N-tuple or ram based neural network classification system and method | |
Gusciora | Back propagation on Warp | |
EBERHART | Analog hardware for learning neural networks(Patent Application) | |
Bebis et al. | BACK-PROPAGATIONleCREASING RATE OF CONVERGENCE BY PREDICTABLE PATTERN LOADING | |
Munro et al. | Integration and differentiation in dynamic recurrent neural networks | |
EBERHARDT | Analog hardware for learning neural networks(Patent) | |
Hudon et al. | A comparative study of neural network models | |
Boné et al. | Yet Another Neural Network Simulator | |
TAWEL | Neural network with dynamically adaptable neurons(Patent Application) | |
ATKESON | Using modular neural networks with local representations to control dynamic systems(Annual Report, 1 Sep. 1989- 30 Sep. 1990) | |
Holub et al. | A digital antennal lobe for pattern equalization: analysis and design | |
Savran | A multilayer feedforward fuzzy neural network | |
Toomarian et al. | Fast temporal neural learning using teacher forcing |