data.txt

经典的算法实例

inverse models;motor;experts
neurons;stimulation;responses;signal;monkey;rat
neural networks;optimization;softassign;algorithm

mathematical-theory;neuronal networks;solitary waves;propagation;slices;discharges;patterns;pulses;tissue
images
support
shape;networks
support vector machines;ill-posed problems;no free lunch;minimum description length;basis function networks;radial basis functions;neural networks;early vision;generalization performance;computational vision
exponential stability;absolute stability;circuits;systems;model
decomposition method;machines;convergence;smo
neural network models;olfactory-bulb;oscillations;cortex;recognition
local minima;backpropagation;perceptrons;algorithm
lateral geniculate-nucleus;orientation selectivity;relay neurons;visual-cortex;cat;dynamics;cells;model;equilibrium;responses
ocular-dominance columns;striate cortex;orientation;models
neocortical pyramidal neurons;recognition;artmap;architecture;synapses
distributed representations;variable binding;connectionist;abstraction
point-processes;neuronal-activity;cells;hippocampus;models;rat;map
monkey striate cortex;horizontal connections;intrinsic connections;mathematical-theory;orientation;projection;patterns;columns
monkey striate cortex;classical receptive-field;orientation selectivity;horizontal connections;intrinsic connections;mathematical-theory;cortical-neurons;ocular dominance;neural networks;simple cells
electric fish;point process;electroreceptors;eigenmannia;precision;responses;signals
hippocampus;rat
striate cortex;models;codes;speed;responses;neurons;noise
primary somatosensory cortex;pursuit eye-movements;free arm movements;neuronal population;visual targets;3-dimensional space;receptive-field;motor cortex;reaching movements;neural networks
dynamical-systems;memory;models
information maximization;distributions
long-term dependencies;gradient descent;prediction;algorithms;systems
monte-carlo;algorithm
independent component analysis;algorithms
model;account;system
fisher information;codes;discharge;cortex;variability;receivers;neurons;motor;noise

striate cortex;neural-network;cortical maps;classification;model
stochastic completion fields;selectivity;responses;closure;cortex;curve;model
primary visual-cortex;macaque monkey;striate cortex;neural oscillators;image segmentation;networks;neurons;optimization;integration;connections
macaque striate cortex;model
cat visual-cortex;neuronal oscillations;spatial-frequency;striate cortex;selectivity;contrast;mechanisms;invariant;dynamics;behavior
blind separation

natural images;self-organization;cortical-cells;cortex;statistics;filters;scenes
layered neural networks;stochastic complexity;regression;curves
feedforward neural-network;inputs
pulse-coupled oscillators;neuronal networks;neocortical neurons;cortical-cells;populations;dynamics;modulation;mechanisms;complex;locking
lateral geniculate-nucleus;receptive-field centers;spike trains;natural scenes;macaque monkey;x-cells;y-cells;neurons;information;precision
metric-space analysis;trains;information;precision
guinea-pig heart;cultured parasympathetic neurons;intracardiac neurons;mathematical-model;intrinsic neurons;potassium currents;calcium currents;nerve-fibers;nitric-oxide;ganglion

maximum-likelihood;neural networks;em algorithm;optimization;classification
sensor fusion
finite-state automata;high-gain;memory;model;dynamics
primate orbitofrontal cortex;predictable environmental events;monkey dopamine neurons;delayed-response task;basal ganglia;network model;reinforcement signal;internal generation;reward expectation;frontal-cortex
cross-validation
generalized cross-validation;stochastic complexity;variable selection;density-estimation;regression;bias;prediction;likelihood;extension;networks
orientation selectivity;geniculocortical afferents;direction selectivity;synaptic integration;cortical-neurons;striate cortex;simple cells;area 17;cat;dynamics
cortical-neurons;in-vivo;synchronization;spiking;cortex;oscillations;computation;modulation;networks;dynamics
invariances
patient
learning algorithms
neocortical pyramidal neurons;long-term potentiation;synaptic plasticity;receptor-channels;nmda receptors;binding-sites;hippocampus;rat;depression;synapses
generalized quantile processes;density contour;sets
em algorithm;networks;mixtures;components;likelihood;analyzers
independent component analysis;associative memory;separation;algorithm;sounds

neural networks;distributed representations;dynamical recognizers;time;computation
pulse-coupled oscillators;stochastic resonance;synchronization;equation;cortex;models
recognition failure;free-recall;memory;retrieval;information;hippocampus;convolution;systems;storage;todam2
long-term potentiation;visual-cortex;simple cells;neocortical circuits;hippocampal-neurons;model;calcium;ltp;coincidence;selectivity
moving-objects;extrapolation;latency;model
neural networks;connectionist;systems
monkey visual-cortex;eye-movements;interocular correlation;binocular disparity;depth-perception;ocular vergence;neural control;neurons;convergence;responses
metric-space analysis;neural spike trains;visual-cortex;information;neurons;code;synchronization;variability;responses;patterns
a-priori distinctions;computational principles;connectionist models;neural networks;visual-cortex;memory;activation;acquisition;algorithms;storage
spatial-frequency;responses;filters
pulse-coupled oscillators;visual-cortex;asynchronous states;neurons;dynamics;cells
networks;oscillation;dynamics
neocortical pyramidal neurons;interneurons
monkey visual-cortex;population codes;cortical areas;psychophysical performance;selective attention;striate cortex;single neurons;macaque;v4;motion


maximum-likelihood
central-nervous-system;neocortical pyramidal neurons;cultured hippocampal-neurons;time-varying signals;synaptic transmission;quantal analysis;spike trains;release probability;transmitter release;cable structures
trees;cells

contextual influences;lateral interactions;contour integration;neural networks;cat;v1;oscillations;orientation;connections;segmentation
arrays
belief networks
neural fields;asynchronous states;prefrontal cortex;pattern-formation;dynamics;model;locking;representation;excitations;orientation
visual experience;face recognition;algorithm;responses;brain;maps
recurrent neural networks;finite-state automata;long-term dependencies;distributed representations;computational capabilities;phoneme recognition;learning algorithm;time;inference;machines
neocortical pyramidal neurons;organizing neural network;calcium action-potentials;distal apical dendrites;long-term potentiation;object recognition;visual-cortex;pattern-recognition;self-organization;rat
independent component analysis
long-term potentiation;excitatory synaptic transmission;postsynaptic action-potentials;coincidence detection;pyramidal cells;dynamic objects;visual-cortex;barrel cortex;neurons;plasticity

hippocampal place cells;patterns
optimization problems
freely-moving rat;theta-rhythm;place cells;pyramidal neurons;cingulate cortex;memory sequences;nmda channels;unit-activity;spatial map;ca3 region
spike trains;responses;stimulus;cortex

primary visual-cortex;self-organizing map;blind separation;maximum-likelihood;neural networks;striate cortex;natural images;complex cells;sparse code;algorithm
blind separation;projection pursuit;neural networks;algorithm;signals
neural-network;olfactory-bulb;visual-cortex;pattern-recognition;explicit memory;model;amnesia;representation;neocognitron;architecture
recurrent neural networks;connectionist;representation
lateral geniculate-nucleus;cat visual-cortex;receptive-field properties;mediating excitatory input;pig thalamic neurons;simple cells;direction selectivity;electrophysiological properties;striate cortex;x-cells
frequency discrimination;nerve fibers;intensity discrimination;amplitude-modulation;quantitative model;rate suppression;tones;noise;responses;system
hearing-impaired listeners;basilar-membrane responses;intensity discrimination;frequency discrimination;level discrimination;amplitude-modulation;quantitative model;chinchilla cochlea;rate suppression;sensation level
inverse models;em algorithm;architecture;competition;experts
energy functions;convergence;networks;space
separation;algorithm
empirically observed statistics;tonically active neurons;classification;primates;striatum
primary visual-cortex;neurons;v1
approximation;machines
nets
neural oscillators;time-delay;cortex
independent component analysis;adaptive source separation;blind separation;information;algorithms;networks
cat neocortical neurons;coupled oscillators;networks;excitability;curves
mathematical-theory;populations;dynamics;equilibrium;network;tissue;nets
lateral-line lobe;weakly electric fish;neocortical pyramidal neurons;rat hippocampal-neurons;electrosensory system;sensory searchlight;channels;release;cells;brain
synaptic weight noise;fault-tolerance;performance
currents;channels
networks
neural networks;absolute stability;model;circuits
synaptic plasticity;quantal amplitude;model;hippocampus;competition;cooperation;synapses;memory
machines
feedforward neural networks;function-approximation;bounds
block
anteroventral cochlear nucleus;auditory-nerve fibers;cat visual-cortex;stochastic resonance;fire models;coincidence detection;discharge patterns;neuronal dynamics;phase precession;bushy cells
karhunen-loeve procedure
continuous probability-distributions;stochastic complexity;statistical-mechanics;density-estimation;thermodynamic depth;mutual information;fisher information;spike trains;entropy;bounds
long-term potentiation;neurotransmitter release;calcium channels;transmitter release;voltage dependence;cerebellar synapse;gaba(b) receptor;time course;facilitation;hippocampus
visual-cortex;synaptic plasticity;hebbian synapses;area ca1;hippocampus;induction;neurons;memory;model
connectionist system
independent component analysis;blind;separation
classification;perceptrons
visual-cortex
neural networks;visual-cortex;trains;monkey
spike trains;precision;neurons
single units;cortical-neurons;frontal-cortex;discharge;patterns;information;modulation;cells;synchronization;connectivity
coincidence detector;neuronal oscillations;temporal integration;cortical neuron;cerebral-cortex;visual-cortex;dynamics;cat;synchronization;connectivity
neural networks;nonparametric regression;model selection;distributions;mixtures
handwritten digit recognition;neural networks;memory;synapses;model;potentiation;classifiers;neurons;systems;trees
fire neurons;stochastic resonance;purkinje-cells;model;dynamics;cortex;responses;networks;dopamine;synchronization
neural networks;food arousal;model cpgs;evolution;aplysia;behavior;locomotion;walking;program;system