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Kak neural network : ウィキペディア英語版 | Kak neural network The Kak neural network, which was first proposed by Subhash Kak, is an instantaneously trained neural network that creates a new hidden neuron for each training sample, achieving instantaneous training for binary data and also for real data if some small additional processing is allowed. These networks, therefore, model short-term biological memory. The training algorithm for binary data creates links to the new hidden node that simply reflects the 0 and 1 values in the training vector. Hence there is no computation involved. This network has been successfully used in a variety of applications in finance, pattern recognition, signal processing, and time-series extrapolation. ==References==
*S. Kak, New algorithms for training feedforward neural networks. Pattern Recognition Letters 15, 1994, pp.295-298. *S. Kak, On generalization by neural networks. Information Sciences 111, 1998, pp. 293-302.
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