Part I Mean Field, Boltzmann, and Hopfield Networks
Deterministic Boltzmann Learning in Networks with Asymmetric Connectivity
Contrastive Hebbian Learning in the Continuous Hopfield Model
Mean Field Networks that Learn to Discriminate Temporally Distorted Strings
Energy Minimization and the Satisfiability of Propositional Logic
Part II Reinforcement Learning
On the Computational Economics of Reinforcement Learning
Reinforcement Comparison
Learning Algorithms for Networks with Internal and External Feedback
Part III Genetic Learning
Exploring Adaptive Agency I: Theory and Methods for Simulating the Evolution of Learning
The Evolution of Learning: An Experiment in Genetic Connectionism
Evolving Controls for Unstable Systems
Part IV Temporal Processing
Back-Propagation, Weight-Elimination and Time Series Prediction
Predicting the Mackey-Glass Timeseries with Cascade-Correlation Learning
Learning in Recurrent Finite Difference Networks
Temporal Backpropagation: An Efficient Algorithm for Finite Impulse Response Neural Networks
Part V Theory and Analysis
Optimal Dimensionality Reduction Using Hebbian Learning
Basis-Function Trees for Approximation in High-Dimensional Spaces
Effects of Circuit Parameters on Convergence of Trinary Update Back-Propagation
Equivalence Proofs for Multi-Layer Perceptron Classifiers and the Bayesian Discriminant Function
A Local Approach to Optimal Queries
Part VI Modularity
A Modularization Scheme for Feedforward Networks
A Compositional Connectionist Architecture
Part VII Cognitive Modeling and Symbol Processing
From Rote Learning to System Building: Acquiring Verb Morphology in Children and Connectionist Nets
Parallel Mapping Circuitry in a Phonological Model
A Modular Neural Network Model of the Acquisition of Category Names in Children
A Computational Model of Attentional Requirements in Sequence Learning
Recall of Sequences of Items by a Neural Network
Binding, Episodic Short-Term Memory, and Selective Attention, Or Why are PDP Models Poor at Symbol Manipulation?
Analogical Retrieval Within a Hybrid Spreading-Activation Network
Appropriate Uses of Hybrid Systems
Cognitive Map Construction and Use: A Parallel Distributed Processing Approach
Part VIII Speech and Vision
Unsupervised Discovery of Speech Segments Using Recurrent Networks
Feature Extraction Using an Unsupervised Neural Network
Motor Control for Speech Skills: A Connectionist Approach
Extracting Features From Faces Using Compression Networks: Face, Identity, Emotion, and Gender Recognition Using Holons
The Development of Topography and Ocular Dominance
On Modeling Some Aspects of Higher Level Vision
Part IX Biology
Modeling Cortical Area 7a Using Stochastic Real-Valued (SRV) Units
Neuronal Signal Strength is Enhanced by Rhythmic Firing
Part X VLSI Implementation
An Analog VLSI Neural Network Cocktail Party Processor
A VLSI Neural Network with On-Chip Learning
Index