Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Orthogonal Transforms for Digital Signal Processing
Orthogonal Transforms for Digital Signal Processing
Biologically Motivated Approach to Face Recognition
IWANN '93 Proceedings of the International Workshop on Artificial Neural Networks: New Trends in Neural Computation
Biologically Motivated Approach to Face Recognition
IWANN '93 Proceedings of the International Workshop on Artificial Neural Networks: New Trends in Neural Computation
IWANN '93 Proceedings of the International Workshop on Artificial Neural Networks: New Trends in Neural Computation
IWANN '96 Proceedings of the International Workshop on Artificial Neural Networks: From Natural to Artificial Neural Computation
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume IV-Volume 7472 - Volume 7472
Automatic Face Recognition via Wavelets and Mathematical Morphology
ICPR '96 Proceedings of the 13th International Conference on Pattern Recognition - Volume 2
Journal of Cognitive Neuroscience
Color image processing in a cellular neural-network environment
IEEE Transactions on Neural Networks
Complex-valued multistate neural associative memory
IEEE Transactions on Neural Networks
Face recognition: a convolutional neural-network approach
IEEE Transactions on Neural Networks
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Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partial-defined multiple-valued function on the single MVN and an arbitrary mapping described by partial-defined or fully-defined Boolean function (which can be not threshold) on the single UBN. The fast-converged learning algorithms are existing for both types of neurons. Such features of the MVN and UBN may be used for solution of the different kinds of problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN) for solution of the image processing and image analysis problems. Another effective application of the MVN is their use as the basic neurons in the neural networks oriented to the image recognition.