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Preface
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Neural Networks: Automata and
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Neural Networks: Automata and
Index
Contents
Contents
Preface
Status of this document
Motivation
^{1.1}
Introduction
Neural networks and formal models of language and computation
Organization of the document
Finite-state machines and neural nets
McCulloch and Pitts' neural logical calculus
What functions can a neuron compute?
Nets with circles and finite-state machines
Mealy machines
Moore machines
Deterministic finite-state automata
Minsky's neural automata
Finite-state automata and regular languages
Sequence processing with neural nets
Processing sequences
State-based sequence processors
Discrete-time recurrent neural networks
Neural Mealy machines
Neural Moore machines
Other architectures without hidden state
Application of DTRNN to sequence processing
Learning algorithms for DTRNN
Gradient-based algorithms
Non-gradient methods
Architecture-coupled methods
Learning problems
Papers
Computational capabilities of DTRNN
Languages, grammars and automata
Grammars and Chomsky's hierarchy.
Chomsky's hierarchy of grammars
DTRNN behaving as finite-state machines
DTRNN based on threshold units
DTRNN based on sigmoid units
Featured papers
Turing computability with DTRNN
Turing machines
Super-Turing capabilities of DTRNN
Grammatical inference with DTRNN
Grammatical inference (GI)
Discrete-time recurrent neural networks for grammatical inference
Representing and learning
Open questions on grammatical inference with DTRNN
Stability and generalization
Automaton extraction algorithms
State-space partition methods
Clustering methods
Using Kohonen's self-organizing maps
Featured papers
Inference of finite-state machines
Inference of context-free grammars
Index
List of abbreviations
Bibliography
Debian User 2002-01-21