Description: Single-layer neural networks can be trained using various learning algorithms. The best-known algorithms are the Adaline, Perceptron and Backpropagation algorithms for supervised learning. The first two are specific to single-layer neural networks while the third can be generalized to multi-layer perceptrons.-Single-layer neural networks can be train ed using various learning algorithms. The best - known algorithms are the Adaline. 102206 and Backpropagation algorithms fo r supervised learning. The first two are specific ic to single-layer neural networks while the th ird can be generalized to multi-layer perceptr ons. Platform: |
Size: 818401 |
Author:陈伟 |
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Description: Single-layer neural networks can be trained using various learning algorithms. The best-known algorithms are the Adaline, Perceptron and Backpropagation algorithms for supervised learning. The first two are specific to single-layer neural networks while the third can be generalized to multi-layer perceptrons.-Single-layer neural networks can be train ed using various learning algorithms. The best- known algorithms are the Adaline. 102206 and Backpropagation algorithms fo r supervised learning. The first two are specific ic to single-layer neural networks while the th ird can be generalized to multi-layer perceptr ons. Platform: |
Size: 818176 |
Author:陈伟 |
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Description: A single perceptron code with backpropagation training algorithm designed for classification problems. Platform: |
Size: 1024 |
Author:Paulo |
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Description: The Adaline is essentially a single-layer backpropagation network. It is trained on a pattern recognition task, where the aim is to classify a bitmap representation of the digits 0-9 into the corresponding classes. Due to the limited capabilities of the Adaline, the network only recognizes the exact training patterns. When the application is ported into the multi-layer backpropagation network, a remarkable degree of fault-tolerance can be achieved.
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Size: 3072 |
Author:ali |
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