Foundations and Tools for Neural Modeling

Stochastic model of the place cell discharge
- Integrate-and-fire model with correlated inputs
- Noise modulation by stochastic neurons of the integrate-and fire type
- Bayesian modelling of neural networks
- Neural networks of the hopfield type
- Stability properties of BSB models
- Storage capacity of the exponential correlation associative memory
- A new input-output function for binary hopfield neural networks
- On the three layer neural networks using sigmoidal functions
- The capacity and attractor basins of associative memory models
- A modular attractor model of semantic access
- Priming an artificial associative memory
- What does a peak in the landscape of a Hopfield associative memory look like?
- Periodic and synchronic firing in an ensemble of identical stochastic units: Structural stability
- Driving neuromodules into synchronous chaos
- Aging and lévy distributions in sandpiles
- Finite size effects in neural networks
- On the computational power of limited precision weights neural networks in classification problems: How to calculate the weight range so that a solution will exist
- Estimating exact form of generalisation errors
- A network model for the emergence of orientation maps and local lateral circuits
- A neural network model for the self-organization of cortical grating cells
- Extended nonlinear hebbian learning for developing sparse-distributed representation
- Cascade error projection: A learning algorithm for hardware implementation
- Unification of supervised and unsupervised training
- On-line optimization of radial basis function networks with orthogonal techniques
- A fast orthogonalized FIR adaptive filter structure using recurrent hopfield-like network
- Using temporal neighborhoods to adapt function approximators in reinforcement learning
- Autonomous clustering for machine learning
- Bioinspired framework for general-purpose learning
- Learning efficient rulesets from fuzzy data with a genetic algorithm
- Self-organizing cases to find paradigms
- Training higher order Gaussian synapses
- On-line gradient learning algorithms for K-nearest neighbor classifiers
- Structure adaptation in artificial neural networks through adaptive clustering and through growth in state space
- Sensitivity analysis of radial basis function networks for fault tolerance purposes
- Association with multi-dendritic radial basis units
- A Boolean neural network controlling task sequences in a noisy environment
- SOAN: Self organizing with adaptive neighborhood neural network
- Topology preservation in SOFM: An euclidean versus manhattan distance comparison
- Supervised VQ learning based on temporal inhibition
- Improving the LBG algorithm
- Sequential learning algorithm for PG-RBF network using regression weights for time series prediction
- Parallel fuzzy learning
- Classification and feature selection by a self-organizing neural network
- SA-prop: Optimization of multilayer perceptron parameters using simulated annealing
- Mobile robot path planning using genetic algorithms
- Do plants optimize?
- Heuristic generation of the initial population in solving job shop problems by evolutionary strategies
- Randomness in heuristics: An experimental investigation for the maximum satisfiability problem
- Solving the packing and strip-packing problems with genetic algorithms
- Multichannel pattern recognition neural network
- A biologically plausible maturation of an ART network
- Adaptive resonance theory microchips
- Application of ART2-A as a pseudo-supervised paradigm to nuclear reactor diagnostics
- Supervised ART-I: A new neural network architecture for learning and classifying multi-valued input patterns
- Conscious and intentional access to unconscious decision-making module in ambiguous visual perception
- A psychophysical approach to the mechanism of human stereovision
- Neuronal coding and color sensations
- Neurocomputational models of visualisation: A preliminary report
- Self-organization of shift-invariant receptive fields
- Pattern recognition system with top-down process of mental rotation
- Segmentation of occluded objects using a hybrid of selective attention and symbolic knowledge
- Hypercolumn model: A modified model of neocognitron using hierarchical self-organizing maps
- Attentional strategies for object recognition