This HTML5 document contains 127 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Namespace Prefixes

PrefixIRI
dbpedia-dehttp://de.dbpedia.org/resource/
dctermshttp://purl.org/dc/terms/
n7https://arxiv.org/abs/quant-ph/
yago-reshttp://yago-knowledge.org/resource/
n16https://web.archive.org/web/20131113014007/http:/www.dwavesys.com/en/
dbohttp://dbpedia.org/ontology/
foafhttp://xmlns.com/foaf/0.1/
n17http://dbpedia.org/resource/File:
dbpedia-cahttp://ca.dbpedia.org/resource/
dbpedia-eshttp://es.dbpedia.org/resource/
n29https://global.dbpedia.org/id/
yagohttp://dbpedia.org/class/yago/
dbthttp://dbpedia.org/resource/Template:
dbpedia-ukhttp://uk.dbpedia.org/resource/
rdfshttp://www.w3.org/2000/01/rdf-schema#
freebasehttp://rdf.freebase.com/ns/
dbpedia-srhttp://sr.dbpedia.org/resource/
n22http://bn.dbpedia.org/resource/
n15http://commons.wikimedia.org/wiki/Special:FilePath/
dbpedia-fahttp://fa.dbpedia.org/resource/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
n20http://www.cic.unb.br/~weigang/qc/
dbpedia-arhttp://ar.dbpedia.org/resource/
n31https://arxiv.org/abs/
owlhttp://www.w3.org/2002/07/owl#
wikipedia-enhttp://en.wikipedia.org/wiki/
dbphttp://dbpedia.org/property/
provhttp://www.w3.org/ns/prov#
dbchttp://dbpedia.org/resource/Category:
xsdhhttp://www.w3.org/2001/XMLSchema#
wikidatahttp://www.wikidata.org/entity/
goldhttp://purl.org/linguistics/gold/
dbrhttp://dbpedia.org/resource/

Statements

Subject Item
dbr:Quantum_mind
dbo:wikiPageWikiLink
dbr:Quantum_neural_network
Subject Item
dbr:Electromagnetic_theories_of_consciousness
dbo:wikiPageWikiLink
dbr:Quantum_neural_network
Subject Item
dbr:Quantum_Neural_Network
dbo:wikiPageWikiLink
dbr:Quantum_neural_network
dbo:wikiPageRedirects
dbr:Quantum_neural_network
Subject Item
dbr:Quantum_associative_memory
dbo:wikiPageWikiLink
dbr:Quantum_neural_network
dbo:wikiPageRedirects
dbr:Quantum_neural_network
Subject Item
dbr:Quantum_cognition
dbo:wikiPageWikiLink
dbr:Quantum_neural_network
Subject Item
dbr:Optical_neural_network
dbo:wikiPageWikiLink
dbr:Quantum_neural_network
Subject Item
dbr:Machine_learning_in_physics
dbo:wikiPageWikiLink
dbr:Quantum_neural_network
Subject Item
dbr:QNN
dbo:wikiPageWikiLink
dbr:Quantum_neural_network
dbo:wikiPageDisambiguates
dbr:Quantum_neural_network
Subject Item
dbr:Quantum_machine_learning
dbo:wikiPageWikiLink
dbr:Quantum_neural_network
Subject Item
dbr:Quantum_neural_network
rdf:type
yago:WikicatArtificialNeuralNetworks yago:ComputerArchitecture106725249 yago:Description106724763 yago:NeuralNetwork106725467 yago:Communication100033020 yago:Specification106725067 yago:Message106598915 yago:Abstraction100002137 yago:WikicatNeuralNetworks dbo:Person yago:Statement106722453
rdfs:label
Xarxa neuronal quàntica Quantum neural network Red neuronal cuántica Neuronaler Schaltkreis شبكة عصبية كمية Квантова нейронна мережа
rdfs:comment
الشبكات العصبية الكمية نماذج شبكة عصبية حسابية تعتمد على مبادئ الميكانيكا الكمية. وتجمع الشبكات العصبية الكمية بين نماذج الشبكة العصبية الاصطناعية الأصلية ومزايا المعلومات الكمية من أجل تطوير خوارزميات أحسن. Quantum neural networks are computational neural network models which are based on the principles of quantum mechanics. The first ideas on quantum neural computation were published independently in 1995 by Subhash Kak and Ron Chrisley, engaging with the theory of quantum mind, which posits that quantum effects play a role in cognitive function. However, typical research in quantum neural networks involves combining classical artificial neural network models (which are widely used in machine learning for the important task of pattern recognition) with the advantages of quantum information in order to develop more efficient algorithms. One important motivation for these investigations is the difficulty to train classical neural networks, especially in big data applications. The hope is that Una red neuronal cuántica (QNN) es un modelo de red neuronal que está basado en los principios de la mecánica cuántica. Hay dos aproximaciones diferentes en la investigación de las QNN: de un lado, explotando el procesamiento de información cuántica para mejorar los modelos de redes neuronales actuales (en ocasiones, también viceversa), y, de otro, buscando efectos cuánticos potenciales en el cerebro. Квантові нейронні мережі (QNNs) — модель нейронної мережі, яка базуються на принципах квантової механіки. Існує два різних підходи до дослідження QNN: одна експлуатаційна обробка квантової інформації для вдосконалення існуючих моделей нейронних мереж (іноді також і навпаки), а інша — пошук потенційних квантових ефектів у мозку. Neuronale Schaltkreise sind in ihrer Arbeitsweise dem biologischen Nervensystem nachempfunden (siehe Neuronaler Erregungskreis). Neuronale Schaltkreise beruhen auf der Technik künstlicher neuronaler Netze. Die Arbeitsweise Neuronaler Schaltkreise ist in der Regel Parallel Distributed Processing oder eine alternative davon abgeleitete Technik. Der wichtigste Vertreter der neuronalen Schaltkreise sind die neuromorphen Schaltkreise, welche die Nachbildung biologischer Neuronen zum Ziel haben.
foaf:depiction
n15:Neural_Network_-_basic_scheme_with_legends.png
dcterms:subject
dbc:Artificial_neural_networks dbc:Quantum_information_science dbc:Quantum_programming dbc:Neural_circuits
dbo:wikiPageID
3737445
dbo:wikiPageRevisionID
1122138297
dbo:wikiPageWikiLink
dbr:Feedforward_neural_network dbr:Big_data dbr:Reservoir_computing dbr:Quantum_reservoir_processor dbr:Integrated_quantum_photonics dbr:Qubits dbr:Quantum_superposition dbr:Qubit dbr:Quantum_cognition dbr:Quantum_mind dbr:Unitary_operator dbr:Associative_memory_(psychology) dbr:Quantum_circuit dbr:Grover_search_algorithm dbr:No-cloning_theorem dbr:Perceptron dbr:Unitary_matrix dbr:Quantum_information dbr:Quantum_phase_estimation_algorithm dbr:Quantum_logic_gate dbr:Artificial_neural_network dbr:Quantum_parallelism dbr:Quantum_mechanics dbr:Fuzzy_logic n17:Neural_Network_-_basic_scheme_with_legends.png dbr:McCulloch-Pitts_neuron dbr:Quantum_computing dbr:Training_set dbr:Reversible_computing dbr:Holographic_associative_memory dbr:Optical_neural_network dbr:Hopfield_neural_network dbr:Subhash_Kak dbr:Neural_network_models dbc:Artificial_neural_networks dbr:Measurement_in_quantum_mechanics dbr:Differentiable_programming dbc:Quantum_information_science dbr:Backpropagation dbc:Quantum_programming dbr:Quantum_machine_learning dbc:Neural_circuits dbr:Ancilla_bit dbr:Fan-out_(software) dbr:Quantum_interference dbr:Quantum_entanglement
dbo:wikiPageExternalLink
n7:0401127 n16:dev-tutorial-neural.html n20:aci.html n31:1408.7005
owl:sameAs
dbpedia-sr:Kvantne_neuronske_mreže wikidata:Q1981341 dbpedia-uk:Квантова_нейронна_мережа dbpedia-de:Neuronaler_Schaltkreis dbpedia-fa:شبکه_عصبی_کوانتومی n22:কোয়ান্টাম_নিউরাল_নেটওয়ার্ক freebase:m.09y5xz dbpedia-es:Red_neuronal_cuántica yago-res:Quantum_neural_network dbpedia-ar:شبكة_عصبية_كمية n29:tXBw dbpedia-ca:Xarxa_neuronal_quàntica
dbp:wikiPageUsesTemplate
dbt:Reflist dbt:Emerging_technologies dbt:Quantum_computing dbt:Differentiable_computing dbt:Short_description
dbo:thumbnail
n15:Neural_Network_-_basic_scheme_with_legends.png?width=300
dbp:other
yes
dbo:abstract
Квантові нейронні мережі (QNNs) — модель нейронної мережі, яка базуються на принципах квантової механіки. Існує два різних підходи до дослідження QNN: одна експлуатаційна обробка квантової інформації для вдосконалення існуючих моделей нейронних мереж (іноді також і навпаки), а інша — пошук потенційних квантових ефектів у мозку. الشبكات العصبية الكمية نماذج شبكة عصبية حسابية تعتمد على مبادئ الميكانيكا الكمية. وتجمع الشبكات العصبية الكمية بين نماذج الشبكة العصبية الاصطناعية الأصلية ومزايا المعلومات الكمية من أجل تطوير خوارزميات أحسن. Quantum neural networks are computational neural network models which are based on the principles of quantum mechanics. The first ideas on quantum neural computation were published independently in 1995 by Subhash Kak and Ron Chrisley, engaging with the theory of quantum mind, which posits that quantum effects play a role in cognitive function. However, typical research in quantum neural networks involves combining classical artificial neural network models (which are widely used in machine learning for the important task of pattern recognition) with the advantages of quantum information in order to develop more efficient algorithms. One important motivation for these investigations is the difficulty to train classical neural networks, especially in big data applications. The hope is that features of quantum computing such as quantum parallelism or the effects of interference and entanglement can be used as resources. Since the technological implementation of a quantum computer is still in a premature stage, such quantum neural network models are mostly theoretical proposals that await their full implementation in physical experiments. Most Quantum neural networks are developed as feed-forward networks. Similar to their classical counterparts, this structure intakes input from one layer of qubits, and passes that input onto another layer of qubits. This layer of qubits evaluates this information and passes on the output to the next layer. Eventually the path leads to the final layer of qubits. The layers do not have to be of the same width, meaning they don't have to have the same number of qubits as the layer before or after it. This structure is trained on which path to take similar to classical artificial neural networks. This is discussed in a lower section. Quantum neural networks refer to three different categories: Quantum computer with classical data, classical computer with quantum data, and quantum computer with quantum data. Una red neuronal cuántica (QNN) es un modelo de red neuronal que está basado en los principios de la mecánica cuántica. Hay dos aproximaciones diferentes en la investigación de las QNN: de un lado, explotando el procesamiento de información cuántica para mejorar los modelos de redes neuronales actuales (en ocasiones, también viceversa), y, de otro, buscando efectos cuánticos potenciales en el cerebro. Neuronale Schaltkreise sind in ihrer Arbeitsweise dem biologischen Nervensystem nachempfunden (siehe Neuronaler Erregungskreis). Neuronale Schaltkreise beruhen auf der Technik künstlicher neuronaler Netze. Die Arbeitsweise Neuronaler Schaltkreise ist in der Regel Parallel Distributed Processing oder eine alternative davon abgeleitete Technik. Der wichtigste Vertreter der neuronalen Schaltkreise sind die neuromorphen Schaltkreise, welche die Nachbildung biologischer Neuronen zum Ziel haben.
dbp:quantum
yes
gold:hypernym
dbr:Models
prov:wasDerivedFrom
wikipedia-en:Quantum_neural_network?oldid=1122138297&ns=0
dbo:wikiPageLength
17925
foaf:isPrimaryTopicOf
wikipedia-en:Quantum_neural_network
Subject Item
dbr:AND_Corporation
dbo:wikiPageWikiLink
dbr:Quantum_neural_network
Subject Item
dbr:Physical_neural_network
dbo:wikiPageWikiLink
dbr:Quantum_neural_network
Subject Item
dbr:Sergio_Boixo
dbo:wikiPageWikiLink
dbr:Quantum_neural_network
Subject Item
dbr:Outline_of_black_holes
dbo:wikiPageWikiLink
dbr:Quantum_neural_network
Subject Item
dbr:Quantum_neural_networks
dbo:wikiPageWikiLink
dbr:Quantum_neural_network
dbo:wikiPageRedirects
dbr:Quantum_neural_network
Subject Item
wikipedia-en:Quantum_neural_network
foaf:primaryTopic
dbr:Quantum_neural_network