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Indent Level
Color Curly Brackets (indicating CPC extensions to IPC)
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CPC
COOPERATIVE PATENT CLASSIFICATION
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G06N
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
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G06N 3/00
Computer systems based on biological models (analogue computers simulating functional aspects of living beings G06G 7/60)
G06N 3/002
.
{
Biomolecular computers, i.e. using biomolecules, proteins, cells (using DNA G06N 3/123; using neurons G06N 3/061)
}
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G06N 3/004
.
{
Artificial life, i.e. computers simulating life
}
G06N 3/006
. .
{
based on simulated virtual individual or collective life forms , e.g. single "avatar", social simulations, virtual worlds (computer games A63F 13/00; medical simulations G06F 19/00; information retrieval G06F 17/30873; image processing G06T; telecommunication protocols H04L 29/06034)
}
G06N 3/008
. .
{
based on physical entities controlled by simulated intelligence so as to replicate intelligent life forms, e.g. robots replicating pets or humans in their appearance or behavior (toys or dolls A63H 3/00; industrial robot control G05B 19/00, B25J 9/00; artificial neural networks G06N 3/00; rule based artificial intelligence G06N 5/00)
}
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G06N 3/02
.
using neural network models (for adaptive control G05B 13/00; for image pattern matching G06K 9/00; for image data processing G06T 1/20; for phonetic pattern matching G10L 15/16)
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G06N 3/04
. .
Architectures, e.g. interconnection topology
G06N 3/0409
. . .
{
Adaptive Resonance Theory [ART
}
 networks]
G06N 3/0418
. . .
{
using chaos or fractal principles
}
G06N 3/0427
. . .
{
in combination with an expert system
}
G06N 3/0436
. . .
{
in combination with fuzzy logic
}
G06N 3/0445
. . .
{
Feedback networks, e.g. hopfield nets, associative networks
}
G06N 3/0454
. . .
{
using a combination of multiple neural nets
}
G06N 3/0463
. . .
{
Neocognitrons
}
G06N 3/0472
. . .
{
using probabilistic elements, e.g. p-rams, stochastic processors
}
G06N 3/0481
. . .
{
Non-linear activation functions, e.g. sigmoids, thresholds
}
G06N 3/049
. . .
{
Temporal neural nets, e.g. delay elements, oscillating neurons, pulsed inputs
}
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G06N 3/06
. .
Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
G06N 3/061
. . .
{
using biological neurons, e.g. biological neurons connected to an integrated circuit
}
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G06N 3/063
. . .
using electronic means
G06N 3/0635
. . . .
{
using analogue means
}
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G06N 3/067
. . .
using optical means
G06N 3/0675
. . . .
{
using electro-optical, acousto-optical or opto-electronic means
}
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G06N 3/08
. .
Learning methods
G06N 3/082
. . .
{
modifying the architecture, e.g. adding or deleting nodes or connections, pruning
}
G06N 3/084
. . .
{
Back-propagation
}
G06N 3/086
. . .
{
using evolutionary programming, e.g. genetic algorithms
}
G06N 3/088
. . .
{
Non-supervised learning, e.g. competitive learning
}
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G06N 3/10
. .
Simulation on general purpose computers
G06N 3/105
. . .
{
Shells for specifying net layout
}
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G06N 3/12
.
using genetic models
G06N 3/123
. .
{
DNA computers, i.e. information processing using biological DNA
}
G06N 3/126
. .
{
Genetic algorithms, i.e. information processing using digital simulations of the genetic system
}
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G06N 5/00
Computer systems utilising knowledge based models
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G06N 5/003
.
{
Dynamic search techniques, heuristics, branch-and-bound (G06F9/44L3B, G06N 5/046 take precedence; for optimisation G06Q10/00B; for game playing G06F19/00B)
}
G06N 5/006
. .
{
Automatic theorem proving
}
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G06N 5/02
.
Knowledge representation
{
(G06N 5/04 takes precedence)
}
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G06N 5/022
. .
{
Knowledge engineering, knowledge acquisition
}
G06N 5/025
. . .
{
Extracting rules from data (learning in general G06F 15/18)
}
G06N 5/027
. .
{
Frames
}
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G06N 5/04
.
Inference methods or devices
G06N 5/041
. .
{
Abduction
}
G06N 5/042
. .
{
Backward inferencing
}
G06N 5/043
. .
{
Distributed expert systems, blackboards
}
G06N 5/045
. .
{
Explanation of inference steps
}
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G06N 5/046
. .
{
Forward inferencing, production systems
}
G06N 5/047
. . .
{
Pattern matching networks, RETE
}
G06N 5/048
. .
{
Fuzzy inferencing
}
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G06N 7/00
Computer systems based on specific mathematical models
G06N 7/005
.
{
Probabilistic networks
}
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G06N 7/02
.
using fuzzy logic (G06N 3/00, G06N 5/00 take precedence; for adaptive control G05B 13/00)
G06N 7/023
. .
{
Learning or tuning the parameters of a fuzzy system
}
G06N 7/026
. .
{
Development tools for entering the parameters of a fuzzy system
}
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G06N 7/04
. .
Physical realisation
G06N 7/043
. . .
{
Analogue or partially analogue implementation
}
G06N 7/046
. . .
{
Implementation by means of a neural network (neural networks using fuzzy logic G06N 3/0436)
}
G06N 7/06
. .
Simulation on general purpose computers
G06N 7/08
.
using chaos models or non-linear system models
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G06N 99/00
Subject matter not provided for in other groups of this subclass
G06N 99/002
.
{
Quantum computers, i.e. information processing by using quantum superposition, coherence, decoherence, entanglement, nonlocality, teleportation
}
G06N 99/005
.
{
Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run (neural networks G06N 3/02; knowledge based models G06N5; fuzzy logic systems G06N 7/02; adaptive control systems G05B 13/00)
}
G06N 99/007
.
{
Molecular computers, i.e. using inorganic molecules (using biomolecules G06N 3/002)
}
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Last Modified: 04/16/2013 4:31:16 PM