neural network wikipedia neural network contents overview edit history edit artificial intelligence edit application edit neuroscience edit type model edit connectivity edit criticism edit recent improvement edit edit reference edit external link edit navigation menu personal tool namespaces variant view search navigation contribute tool print export language wikipedia free encyclopedia jump navigation jump search use neural network disambiguation structure biology artificial intelligence simplified view feedforward artificial neural network neural network network circuit neuron modern sense artificial neural network compose artificial neuron node neural network biological neural network real biological neuron artificial neural network solve artificial intelligence ai problem connection biological neuron model weight positive weight reflect excitatory connection negative value mean inhibitory connection input modify weight sum activity refer linear combination finally activation function control amplitude output example acceptable range output usually artificial network predictive modeling adaptive control application train dataset self learn result experience occur network derive conclusion complex seemingly unrelated set information overview history artificial intelligence application neuroscience type model connectivity criticism recent improvement reference external link overview edit biological neural network compose group chemically connect functionally associate neuron single neuron connect neuron total number neuron connection network extensive connection call synapsis usually form axon dendrite dendrodendritic synapsis connection possible apart electrical signaling form signal arise neurotransmitter diffusion artificial intelligence cognitive modeling neural network information process paradigm inspire way biological neural system process datum artificial intelligence cognitive modeling try simulate property biological neural network artificial intelligence field artificial neural network apply successfully speech recognition image analysis adaptive control order construct software agent computer video game autonomous robot historically digital computer evolve von neumann model operate execution explicit instruction access memory number processor hand origin neural network base effort model information processing biological system unlike von neumann model neural network computing separate memory processing neural network theory serve well identify neuron brain function provide basis effort create artificial intelligence history edit preliminary theoretical base contemporary neural network independently propose alexander bain william james work thought body activity result interaction neuron brain computer simulation branch architecture dendrite pyramidal neuron bain activity lead firing certain set neuron activity repeat connection neuron strengthen accord theory repetition lead formation memory general scientific community time skeptical bain theory require appear inordinate number neural connection brain apparent brain exceedingly complex brain wiring handle multiple problem input james theory similar bain suggest memory action result electrical current flow neuron brain model focus flow electrical current require individual neural connection memory action sherrington conduct experiment test james theory run electrical current spinal cord rat instead demonstrate increase electrical current project james sherrington find electrical current strength decrease testing continue time importantly work lead discovery concept habituation mcculloch pitts create computational model neural network base mathematic algorithm call model threshold logic model pave way neural network research split distinct approach approach focus biological process brain focus application neural network artificial intelligence late 1940 psychologist donald hebb create hypothesis learn base mechanism neural plasticity know hebbian learning hebbian learning consider typical unsupervised learning rule later variant early model long term potentiation idea start apply computational model turing b type machine farley clark computational machine call calculator simulate hebbian network mit neural network computational machine create rochester holland habit duda rosenblatt create perceptron algorithm pattern recognition base layer learning computer network simple addition subtraction mathematical notation rosenblatt describe circuitry basic perceptron exclusive circuit circuit mathematical computation process backpropagation algorithm create werbos neural network research stagnate publication machine learning research marvin minsky seymour papert discover key issue computational machine process neural network issue single layer neural network incapable process exclusive circuit second significant issue computer sophisticated effectively handle long run time require large neural network neural network research slow computer achieve great processing power key later advance backpropagation algorithm effectively solve exclusive problem werbos parallel distribute processing popular connectionism text rumelhart mcclelland provide exposition use connectionism computer simulate neural process neural network artificial intelligence traditionally view simplify model neural processing brain relation model brain biological architecture debate clear degree artificial neural network mirror brain function artificial intelligence edit main article artificial neural network neural network nn case artificial neuron call artificial neural network ann simulate neural network snn interconnected group natural artificial neuron use mathematical computational model information processing base connectionistic approach computation case ann adaptive system change structure base external internal information flow network practical term neural network non linear statistical datum modeling decision make tool model complex relationship input output find pattern datum artificial neural network involve network simple processing element artificial neuron exhibit complex global behavior determine connection processing element element parameter artificial neuron propose warren mcculloch neurophysiologist walter pitts logician collaborate university chicago classical type artificial neural network recurrent hopfield network concept neural network appear propose alan turing paper intelligent machinery call b type unorganised machine utility artificial neural network model lie fact infer function observation use unsupervise neural network learn representation input capture salient characteristic input distribution boltzmann machine recently deep learning algorithm implicitly learn distribution function observe datum learn neural network particularly useful application complexity datum task make design function hand impractical application edit neural network different field task artificial neural network apply tend fall following broad category function approximation regression analysis include time series prediction modeling classification include pattern sequence recognition novelty detection sequential decision making datum processing include filtering clustering blind signal separation compression application area ann include nonlinear system identification control vehicle control process control game playing decision making backgammon chess racing pattern recognition radar system face identification object recognition sequence recognition gesture speech handwritten text recognition medical diagnosis financial application datum mining knowledge discovery database kdd visualization e mail spam filtering example possible create semantic profile user interest emerge picture train object recognition neuroscience edit theoretical computational neuroscience field concern analysis computational modeling biological neural system neural system intimately related cognitive process behaviour field closely relate cognitive behavioural modeling aim field create model biological neural system order understand biological system work gain understanding neuroscientist strive link observed biological process datum biologically plausible mechanism neural processing learn biological neural network model theory statistical learning theory information theory type model edit model define different level abstraction model different aspect neural system range model short term behaviour individual neuron model dynamic neural circuitry arise interaction individual neuron model behaviour arise abstract neural module represent complete subsystem include model long term short term plasticity neural system relation learning memory individual neuron system level connectivity edit brain connectivity estimator august scientist report bi directional connection add appropriate feedback connection accelerate improve communication modular neural network brain cerebral cortex lower threshold successful communication show add feedback connection resonance pair support successful propagation single pulse packet entire network criticism edit common criticism neural network particularly robotic require large diversity training real world operation surprising learning machine need sufficient representative example order capture underlying structure allow generalize new case dean pomerleau research present paper knowledge base training artificial neural networks autonomous robot driving use neural network train robotic vehicle drive multiple type road single lane multi lane dirt etc large research devoted extrapolate multiple training scenario single training experience preserve past training diversity system overtrained example present series right turn learn turn right issue common neural network decide wide variety response deal way example randomly shuffle training example numerical optimization algorithm large step change network connection follow example group example call mini batch dewdney scientific american columnist write neural net solve toy problem power computation limited surprised take seriously general problem solve tool dewdney argument dewdney position implement large effective software neural network processing storage resource need commit brain hardware tailor task processing signal graph neuron simulate simplified form von neumann technology compel neural network designer fill million database row connection consume vast amount computer memory hard disk space furthermore designer neural network system need simulate transmission signal connection associate neuron match incredible amount cpu processing power time neural network yield effective program cost efficiency tend consume considerable amount time money argument dewdney position neural net successfully solve complex diverse task autonomously fly aircraft technology writer roger bridgman comment dewdney statement neural net neural network instance dock hype high heaven create successful net understand work bunch number capture behaviour probability opaque unreadable table valueless scientific resource spite emphatic declaration science technology dewdney pillory neural net bad science devise try good engineer unreadable table useful machine read worth have true analyze learn artificial neural network difficult easy analyze learn biological neural network recent emphasis explainability ai contribute development method notably base attention mechanism visualize explain learn neural network furthermore researcher involve explore learning algorithm neural network gradually uncover generic principle allow learn machine successful example bengio lecun write article local vs non local learning shallow vs deep architecture criticism come believer hybrid model combine neural network symbolic approach advocate intermix approach believe hybrid model well capture mechanism human mind sun bookman citation need recent improvement edit initially research concern electrical characteristic neuron particularly important investigation recent year exploration role neuromodulator dopamine acetylcholine serotonin behaviour learning biophysical model bcm theory important understand mechanism synaptic plasticity application computer science neuroscience research ongoing understand computational algorithm brain recent biological evidence radial basis network neural backpropagation mechanism processing datum computational device create cmos biophysical simulation neuromorphic computing recent effort promise create nanodevice large scale principal component analysis convolution successful effort usher new era neural computing step digital computing depend learn programming fundamentally analog digital instantiation fact cmo digital device recurrent neural network deep feedforward neural network develop research group jürgen schmidhuber swiss ai lab idsia win international competition pattern recognition machine learning example multi dimensional long short term memory lstm win competition connected handwriting recognition international conference document analysis recognition icdar prior knowledge different language learn variant propagation algorithm unsupervise method geoff hinton colleague university toronto train deep highly nonlinear neural architecture similar neocognitron kunihiko fukushima standard architecture vision inspire simple complex cell identify david hubel torsten wiesel primary visual cortex radial basis function wavelet network introduce show offer good approximation property apply nonlinear system identification classification application deep learning feedforward network alternate convolutional layer max pooling layer top pure classification layer fast gpu implementation approach win pattern recognition contest include ijcnn traffic sign recognition competition isbi segmentation neuronal structures electron microscopy stacks challenge neural network artificial pattern recognizer achieve human competitive superhuman performance benchmark traffic sign recognition ijcnn mnist handwritten digit problem yann lecun colleague nyu edit adaline adaptive resonance theory biological cybernetic biologically inspire compute cerebellar model articulation controller cognitive architecture cognitive science connectomics cultured neuronal network deep learn deep image prior digital morphogenesis efficiently updatable neural network exclusive evolutionary algorithm genetic algorithm gene expression programming generative adversarial network group method datum handle habituation situ adaptive tabulation memristor multilinear subspace learn neural network software nonlinear system identification parallel constraint satisfaction process parallel distribute process predictive analytic radial basis function network self organize map simulate reality support vector machine tensor product network time delay neural network reference edit hopfield neural network physical system emergent collective computational ability proc natl acad sci bibcode 1982pnas doi pmc pmid neural net neural network gartner glossary arbib b c d bain mind body theory relation new york appleton company b james principles psychology new york holt company cuntz hermann plos computational biology issue image vol august plos computational biology doi sherrington experiment examination peripheral distribution fibers posterior root spinal nerves proceeding royal society london doi mcculloch warren walter pitts logical calculus ideas immanent nervous activity bulletin mathematical biophysics doi bf02478259 hebb donald organization behavior new york wiley farley clark simulation self organizing systems digital computer ire transactions information theory doi rochester holland habit duda test cell assembly theory action brain large digital computer ire transactions information theory doi rosenblatt perceptron probalistic model information storage organization brain psychological review citeseerx doi h0042519 pmid b werbos regression new tools prediction analysis behavioral sciences minsky papert introduction computational geometry mit press isbn rumelhart james mcclelland parallel distribute processing exploration microstructure cognition cambridge mit press russell ingrid neural networks module archive original retrieve check date value help mcculloch warren pitts walter logical calculus ideas immanent nervous activity bulletin mathematical biophysics doi bf02478259 copeland jack ed essential turing oxford university press isbn b billings nonlinear system identification narmax methods time frequency spatio temporal domains wiley isbn wieczorek szymon filipiak dominik filipowska agata semantic image base profiling users interest neural networks study semantic web emerge topics semantic technologies doi neuroscientist demonstrate improve communication different region brain retrieved september rezaei hedyeh aertsen ad kumar arvind valizadeh alireza august facilitate propagation spike activity feedforward network include feedback plos computational biology e1008033 doi issn pmid s2cid text image available creative commons attribution international license administrator nasa june dryden flight research center news room news release nasa neural network project pass milestone nasa roger bridgman defence neural network archive original march retrieved august scale learning algorithms ai lisa publications aigaion yang et al memristive switching mechanism metal oxide metal nanodevice nat nanotechnol doi pmid strukov et al miss memristor find nature bibcode 80s doi nature06932 pmid kurzweil ai interview jürgen schmidhuber competition win deep learning team archive original august retrieved december graves alex schmidhuber jürgen offline handwriting recognition multidimensional recurrent neural networks bengio yoshua schuurmans dale lafferty john williams chris culotta aron eds advance neural information processing systems neural information processing systems nips foundation pp graves liwicki fernandez bertolami bunke schmidhuber novel connectionist system improved unconstrained handwriting recognition ieee transaction pattern analysis machine intelligence citeseerx doi pmid hinton osindero teh fast learning algorithm deep belief net pdf neural computation citeseerx doi pmid fukushima neocognitron self organize neural network model mechanism pattern recognition unaffected shift position biological cybernetics doi bf00344251 pmid riesenhuber poggio hierarchical model object recognition cortex nature neuroscience doi pmid ciresan meier masci schmidhuber multi column deep neural network traffic sign classification neural networks ciresan giusti gambardella schmidhuber deep neural networks segment neuronal membranes electron microscopy images advance neural information processing systems nips lake tahoe ciresan meier schmidhuber multi column deep neural networks image classification ieee conf computer vision pattern recognition cvpr external link edit listen article megabyte audio file create revision article date november reflect subsequent edit audio help speak article brief introduction neural networks kriesel illustrate bilingual manuscript artificial neural network topic far perceptron backpropagation radial basis functions recurrent neural networks self organizing maps hopfield networks review neural networks materials science artificial neural networks tutorial language univ politécnica de madrid introduction ann generation neural networks google tech talks performance neural networks neural networks information sanderson grant october neural network 3blue1brown youtube retrieve category computational neuroscience neural network network architecture networks econometrics information knowledge uncertainty artificial intelligence emerging technology hide category cs1 error date article short description short description match wikidata use mdy date january article incomplete citation article incomplete citation april articles haudio microformat spoken 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