Constructive higher-order network that is polynomial time
Neural Networks
Experiments of Fast Learning with High Order Boltzmann Machines
Applied Intelligence
Modified high-order neural network for invariant pattern recognition
Pattern Recognition Letters
Persian/arabic handwritten word recognition using M-band packet wavelet transform
Image and Vision Computing
Commutativity as prior knowledge in fuzzy modeling
Fuzzy Sets and Systems
Applications of self-organization networks spatially isomorphic to patterns
Information Sciences: an International Journal
A new feature extractor invariant to intensity, rotation, and scaling of color images
Information Sciences: an International Journal
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The classification and recognition of two-dimensional patterns independently of their position, orientation, and size by using high-order networks are discussed. A method is introduced for reducing and controlling the number of weights of a third-order network used for invariant pattern recognition. The method leads to economical networks that exhibit high recognition rates for translated, rotated, and scaled, as well as locally distorted, patterns. The performance of these networks at recognizing types and handwritten numerals independently of their position, size, and orientation is compared with and found superior to the performance of a layered feedforward network to which image features extracted by the method of moments are presented as input