Wayne E. Hubbard

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The ability of learning networks to generalize can be greatly enhanced by providing constraints from the task domain. This paper demonstrates how such constraints can be integrated into a backpropagation network through the architecture of the network. This approach has been successfully applied to the recognition of handwritten zip code digits provided by(More)
We present an application of back-propagation networks to handwritten digit recognition. Minimal preprocessing of the data was required, but architecture of the network was highly constrained and specifically designed for the task. The input of the network consists of normalized images of isolated digits. The method has 1 % error rate and about a 9% reject(More)
The authors describe a complementary metal-oxide-semiconductor (CMOS) very-large-scale integrated (VLSI) circuit implementing a connectionist neural-network model. It consists of an array of 54 simple processors fully interconnected with a programmable connection matrix. This experimental design tests the behavior of a large network of processors integrated(More)
This paper describes the construction of a system that recognizes hand-printed digits, using a combination of classical techniques and neural-net methods. The system has been trained and tested on real-world data, derived from zip codes seen on actual U.S. Mail. The system rejects a small percentage of the examples as unclassifiable, and achieves a very low(More)
MOS charge storage has been demonstrated as an effective method to store the weights in VLSI implementations of neural network models by several workers 2 . However, to achieve the full power of a VLSI implementation of an adaptive algorithm, the learning operation must built into the circuit. We have fabricated and tested a circuit ideal for this purpose(More)
Electronic neural networks can perform the function of associative memory. Given an input pattern, the network searches through its stored memories to find which of them best matches the input. Thus the network does a combination of content-addressable search and error correction. The number of random memories that a network can store is limited to a(More)
A word recognition system has been developed at NIST to read free-formatted text paragraphs containing handprinted characters. The system has been developed and tested using samples of handprint from NIST Special Database 1. This database of binary images contains 2,100 different writers’ printings of the Preamble to the U. S. Constitution. Each writer was(More)
method is at an early stage of investigation, and development in many directions is possible. Challenging open problems include the relationship between the model types and their discriminating powers, convergence of classiication performance under approximate uniformity, and alternative methods for model combination. Moreover , the study of the method(More)