A neuron-weighted learning algorithm and its hardware implementation in associative memories
1993
A novel learning algorithm for a neuron-weighted associative memory (NWAM) is presented. The learning procedure is cast as a global minimization, solved by a gradient descent rule. An analog neural network for implementing the learning method is described. Some computer simulation experiments are reported. >
Keywords:
- Parallel computing
- Computer science
- Online machine learning
- Instance-based learning
- Active learning (machine learning)
- Artificial neural network
- Learning classifier system
- Leabra
- Wake-sleep algorithm
- Stability (learning theory)
- Algorithm
- Machine learning
- Theoretical computer science
- Artificial intelligence
- Content-addressable memory
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