Perceptrons: expanded edition
Compiler design in C
Constructive higher-order network that is polynomial time
Neural Networks
Advanced compiler design and implementation
Advanced compiler design and implementation
An intelligent neural network programming system (NNPS)
ACM SIGPLAN Notices
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems
Combining Artificial Neural Nets: Ensemble and Modular Multi-Net Systems
Data Structures and Algorithms
Data Structures and Algorithms
Object-oriented symbol management in syntax-directed compiler systems
ACM SIGPLAN Notices
The SNNS Neural Network Simulator
Mustererkennung 1991, 13. DAGM-Symposium
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We present a language framework for handling arbitrarily complex neural computations. The software architecture - which we call an Artificial Neural Network Compiler for Hierarchical ORganization (ANCHOR) - facilitates network hierarchy and simpler sub-mappings. We define a Net Definition Language (NDL) which is implemented in object-oriented programming paradigm; a trained network is decompiled back into NDL. ANCHOR is configured around the concept of a Superneuron which is a generalized view of a neuron-processing element and designed using reuse of object-model. The indistinguishability between a superneuron and a neuron is employed in hierarchical nesting of superneurons, up to (theoretically) infinite depth within other superneurons as well as linear or tree-structured cascading. Hierarchical decomposition of simple boolean functions has been demonstrated as proof-of-concept.