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Training of CC4 Neural Network with Spread Unary Coding
- Computer ScienceArXiv
- 2015
The modified CC4 algorithm is adapted to train the neural networks using spread unary inputs and it is shown that the number of misclassified points is not particularly sensitive to the chosen radius of generalization.
FC Networks for Prediction Applications
- Computer Science
These generalized networks, called FC networks, are compared against Backpropagation and Radial Basis Function networks and shown to have excellent performance for prediction of time-series and pattern recognition.
Instantaneously Trained Neural Networks
- Computer ScienceArXiv
- 2006
This paper presents a review of instantaneously trained neural networks (ITNNs). These networks trade learning time for size and, in the basic model, a new hidden node is created for each training…
A new corner classification approach to neural network training
- Computer Science
- 1998
The corner classification approach to neural network training has the excellent capability ofprescriptive learning, where the network weights areprescribed merely by inspection of the training…
Delta Learning Rule for the Active Sites Model
- Computer ScienceArXiv
- 2010
The recently proposed Active Sites model is extended by developing a delta rule to increase memory capacity and the binary neural network is extended to a multi-level (non-binary) neural network.
Instantaneous Learning Neural Networks.
- Computer Science
- 1999
This talk discusses several types of neural networks with the instantaneous learning property, including the CC4 Corner Classification neural network, and some comparison of generalization performance is presented.
Extracting Generalized Descriptions from a Binary Feedforward Network
- Computer ScienceAppl. Artif. Intell.
- 1998
This study develops a technique to extract generalized descriptions from the hidden layer weights of a binary feedforward network. We extend the Boolean-like training algorithm with recurrent…
The Basic Kak Neural Network with Complex Inputs
- Computer ScienceArXiv
- 2006
This introduction to the basic Kak network with complex inputs is being presented, which is part of a larger hierarchy of learning schemes that include quantum models.
Instantaneously trained neural networks with complex inputs
- Computer Science
- 2003
The development of the 3C algorithm is the main contribution of the thesis, which adapts the time-efficient corner classification approach to train feedforward neural networks to handle complex inputs using prescriptive learning, where the network weights are assigned simply upon examining the inputs.
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