The perceptron: A probabilistic model for information storage and organization in the brain.

A logical calculus of the ideas immanent in nervous activity

McCulloch, W. S., & Pitts, W. (1943) · The Bulletin of Mathematical Biophysics · doi:10.1007/bf02478259 · Cited by 18,566

The Organization of Behavior

Hebb, D. O. (2005) · doi:10.4324/9781410612403 · Cited by 9,825

Representation of Events in Nerve Nets and Finite Automata

Kleene, S. (1951) · Princeton University Press eBooks · doi:10.1515/9781400882618-002 · Cited by 1,927

Probabilistic Logic and the Synthesis of Reliable Organisms from Unreliable Components

von Neumann, J. (1956) · Cited by 1,652

Untitled work

(1952) · Medical Entomology and Zoology · Cited by 1,436

The Sensory Order.

Kneale, M., & von Hayek, F. A. (1954) · The Philosophical Quarterly · doi:10.2307/2216396 · Cited by 494

Human Nature in the Light of Psychopathology

Goldstein, K. (1940) · Harvard University Press eBooks · doi:10.4159/harvard.9780674492103 · Cited by 286

The cell assembly: Mark II.

Milner, P. M. (1957) · Psychological Review · doi:10.1037/h0042287 · Cited by 235

Human Nature in the Light of Psychopathology.

L., H. A., & Goldstein, K. (1941) · The Journal of Philosophy · doi:10.2307/2017294 · Cited by 126

Why the Mind is in the Head?

McCulloch, W. S. (1950) · dialectica · doi:10.1111/j.1746-8361.1950.tb01019.x · Cited by 73

Propostas de metodologias para controle inteligente de sistemas não lineares com incertezas parametricas e funcionais

Grinits, E. V. (2007) · doi:10.47749/t/unicamp.2007.401495

Specialized Cerebellum-Like Structures

Barlow, J. S. (2002) · Cambridge University Press eBooks · doi:10.1017/cbo9780511529771.013

Técnicas y herramientas en VA: Redes Neuronales

Quesada, F. J. G., Fernández‐Caballero, A., Díaz-Marta, M. D. L. L. A., & Graciani, M. Á. F. (1995) · Dialnet (Universidad de la Rioja)

Precision tests of the Standard Model using key observables of CP violation and rare decays

Schlupp, M. (2015) · CERN Document Server (European Organization for Nuclear Research) · doi:10.17877/de290r-16531

Orientación de un objeto 3D : implementación de redes neuronales artificiales utilizando lógica programable

Carnevale, F. (2010) · RICABIB - Repositorio Institucional del Centro Atómico Bariloche

Um estudo comparativo em memorias associativas com enfase em memorias associativas morfologicas

Mesquita, M. E. R. D. V. (2005) · doi:10.47749/t/unicamp.2005.359357

Feature Extraction Using an Information Theoretic Framework

Príncipe, J. C. (1999) · Defense Technical Information Center (DTIC) · doi:10.21236/ada397483

Skewing the Perceptron: Modeling the Importance of System-Level Manipulation When Investigating Long-Term Potentiation

Murray, A., & Matz, J. (2010) · Biochemistry and Molecular Biology Education

Thoughts and thinking

Ellman, R. (2011) · International Conference on Artificial Intelligence

Voted Kernel RegularizationPreprint

Cortes, C., Goyal, P., Kuznetsov, V., & Mohri, M. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1509.04340

Threshold Logic Units

Kruse, R., Borgelt, C., Klawonn, F., Moewes, C., Steinbrecher, M., & Held, P. (2013) · Texts in computer science · doi:10.1007/978-1-4471-5013-8_3

Online Cost Sensitive Domain Knowledge Adaption

Dhanashree, M., & Phursule, R. N. (2015) · International Journal of Computer Applications · doi:10.5120/ijca2015905639

Developmental model of sensorimotor map acquisition for a humanoid robot

Majure, L. (2013) · Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign)

On String Prioritization in Web-Based User Interface Localization

Leiva, L. A., & Alabau, V. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-11746-1_34

Modelagem hibrido neuronal de um processo de fermentação alcoolica

Mantovaneli, I. C. C. (2005) · doi:10.47749/t/unicamp.2005.376272

High-performance simulation of neural networks

Rademacher, T. J., & Lumpp, J. E. (1997) · IEEE Aerospace Conference (AERO) · doi:10.1109/aero.1997.574894

A hebbian based rule reduction approach to neuro-fuzzy modeling

Liu, F. (2008) · doi:10.32657/10356/13601

Einstein–Cartan, Bianchi I and the Hubble diagram

Zouzou, S. R., Tilquin, A., & Schücker, T. (2016) · General Relativity and Gravitation · doi:10.1007/s10714-016-2050-5

Improving the distance reduction step in the von Neumann algorithmPreprint

Pang, C. H. J. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1408.3214

Modelo predictivo de mortalidad a largo plazo en el trasplante hepático del adulto

Esteban, M. B. (2015) · Dialnet (Universidad de la Rioja)

Previsão de series de vazões com redes neurais artificiais e modelos lineares ajustados por algoritmos bio-inspirados

Siqueira, H. V. (2009) · doi:10.47749/t/unicamp.2009.468427

Protein Secondary Structure Prediction Using a Vector Valued Classifier

Korff, M. G. (2016) · Universitätsbibliothek der FU Berlin Hochschulschriftenstelle u. Dokumentenserver · doi:10.17169/refubium-8667

Herding as a Learning System with Edge-of-Chaos Dynamics

Chen, Y., & Welling, M. (2016) · The MIT Press eBooks · doi:10.7551/mitpress/10761.003.0005

Estudo da estrutura-atividade das Esterilquinolinas e Tetraciclinas através de descritores quânticos

Sato, F. (2003) · doi:10.47749/t/unicamp.2003.281889

A Domotic Ecosystem Driven by a Networked Intelligence

Ferrari, L., Gioia, M., Galliani, G. L., & Apolloni, B. (2014) · International Conference on Web Information Systems and Technologies · doi:10.5220/0004977603590366

Learning to learn: An Automated and Continuous Approach to Learning in Imperfect Environments

Mujtaba, H. (2010)

Statistical Learning Theoretical Foundations Overview for Big Data Predictive Analytic

Tigani, S., Saadane, R., & Ouzzif, M. (2016)

Approches neuromimétiques pour l'identification et la commande

Wira, P. (2009) · HAL

State representation for agent-based reinforcement learning.

Mao, T. (2012) · doi:10.1349/ddlp.3529

A characterization of hard-threshold boolean functions

Botelho, F. (1998) · University of Minnesota Digital Conservancy (University of Minnesota)

Modelling equity returns in South Africa: a data mining approach to the variable selection problem in asset pricing

Mhlanga, W. (2015)

Optimization and machine learning applications to protein sequence and structure

Karypis, G., & DeRonne, K. W. (2013) · University of Minnesota Digital Conservancy (University of Minnesota)

Comparison of explicit and implicit keywords to categorize geographic information system procedures

Viger, R. J. (2011)

Topological Classification of Behavioural Financial Patterns in Spanish FirmsPreprint

Acín, J. A. M., Estévez, P. G., & Ferrari, S. R. (2007) · SSRN Electronic Journal · doi:10.2139/ssrn.967993

Specific Features of Adaptive Controllers and Adaptive Signal Processors

Barlow, J. S. (2002) · Cambridge University Press eBooks · doi:10.1017/cbo9780511529771.016

Cerebellar Pathology in Humans and Animals: Genetic Alterations

Barlow, J. S. (2002) · Cambridge University Press eBooks · doi:10.1017/cbo9780511529771.012

Solução de problemas de otimização linear por redes neurais associadas a metodos de pontos interiores

Fontova, M. I. V. (2003) · doi:10.47749/t/unicamp.2003.303638

Training of spiking neural networks based on information theoretic costsPreprint

Sinyavskiy, O. Y. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1602.04742

Latent structure discriminative learning for natural language processing

Clifton, A. (2015) · Summit (Simon Fraser University)

COMPUTERIZED TOOLS: A SUBSTITUTE OR A SUPPLEMENT WHEN DIAGNOSING ALZHEIMER'S DISEASE?

Palomeque, A., & Alberto, C. (2015) · Figshare

SVM imbalance correction by conformal kernel transformations

Jiménez, Á. B. (2008) · Biblos-e Archivo (Universidad Autónoma de Madrid)

An integrated adaptive fuzzy clustering model for pattern recognition

Kim, Y. S. (1993) · ThinkTech (Texas Tech University)

NESSR : Un système neuro-expert pour la reconnaissance de la parole

Abidet-Bahi, H. (2005)

entre l'Analyse Discriminante et l'Approche Neuronale

Boujelb, Y., & Khemakhem, S. (2013)

Influence of Different Concepts of Voltage Control on the Transient Performance of

Generators, S. T. (2006)

UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL INSTITUTO DE PESQUISAS HIDRÁULICAS PROGRAMA DE PÓS-GRADUAÇÃO EM RECURSOS HÍDRICOS E SANEAMENTO AMBIENTAL EFEITO DO CONTROLE DE MONTANTE NA PREVISÃO HIDROLÓGICA DE CURTO PRAZO COM REDES NEURAIS: APLICAÇÃO À

Ijuí, B. D. (2012)

Plattformabhängige Eliminierung gemeinsamer Teilausdrücke auf Quellcode-Ebene

Vogt, M. (2004) · Technische Universität Dortmund Eldorado (Technische Universität Dortmund) · doi:10.17877/de290r-14379

UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL FACULDADE DE VETERINÁRIA PROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIAS VETERINÁRIAS USO DE REDES NEURAIS ARTIFICIAIS NO GERENCIAMENTO DE MATADOUROS-FRIGORÍFICOS DE AVES E SUÍNOS NO SUL DO BRASIL.

Pinto, P. R. (2006)

Dynamic configuration and approximation capabilities of extreme learning machines

Zhang, R. (2012) · doi:10.32657/10356/50729

Pulse stream VLSI circuits and techniques for the implementation of neural networks

Hamilton, A. (1993) · ERA

Neuro-Fuzzy Data Mining Mexico’s Economic Data

Becerra-Gaviño, G., & Barbosa-Santillán, L. I. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-12568-8_79

Modeling and characterizing novel pulsed neural networks for real-time applications

Zhuang, H. (2011) · doi:10.32657/10356/46323

Study of Computational and Experimental Methodologies for Cracks Recognition of Vibrating Systems using Modal Parameters

Khan, I. A. (2015)

UNIVERSIDADE ESTADUAL PAULISTA Instituto de Geociências e Ciências Exatas Campus de Rio Claro

Ferro, L. (2013)

CLASSIFIERS BASED ON A NEW APPROACH TO ESTIMATE THE FISHER SUBSPACE AND THEIR APPLICATIONS

Rozza, A. (2011) · Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) · doi:10.13130/rozza-alessandro_phd2011-03-24

Learning from images by integrating different perspectives

Goldman, S. A., & Cholleti, S. R. (2008)

The role of chemical cues in the predatory and anti-predatory behaviour of jumping spiders (Araneae, Salticidae).

Clark, R. J. (2000) · UC Research Repository (University of Canterbury) · doi:10.26021/8161

SUMMARY LEARNING EXPERT KNOWLEDGE AND THEOREM PROVING

KodratotT, Y. (1986)

A VIEW OF REMOTE SENSING IN NEAR FUTURE

HOSHI, T. (1990) · Doboku Gakkai Ronbunshu · doi:10.2208/jscej.1990.419_21

Differenzierung zwischen dem Churg-Strauss Syndrom und dem Hypereosinophilen Syndrom anhand eines künstlichen neuronalen Netzwerkes

der Doktorwürde, E. (2008)

EMPIRICAL EVIDENCE AND THEORETICAL ANALYSIS OF FEATURE CREATION DURING CATEGORY ACQUISITION

FINK, M., Ben‐Shakhar, G., & Horn, D. (2004) · Neural Computation and Psychology Workshop (NCPW) · doi:10.1142/9789812702784_0013

HCKP: An Effective Hybrid Classification for Chinese News

Gu, W. (2014) · Journal of Information and Computational Science · doi:10.12733/jics20103814

Connectionist Taxonomy Learning

Friedrich-Wilhelms-Universität, R. (2007)

Classification of the EMG's Recruitment Pattern Using Neural Networks

Papadopoulou, F., Michou, A. A., Panas, S. M., & I.B. Mavromatis (1998) · Journal of Intelligent Systems · doi:10.1515/jisys.1998.8.1-2.145

Co-evolutionary Approach to Improve Robustness of Routing Algorithms against Disruptive Events on the Airport Surface

Kicinger, R., Ganji, M., Chen, J.-T., Reddy, R., & Ellejmi, M. (2014) · AIAA Guidance, Navigation, and Control Conference and Exhibit · doi:10.2514/6.2014-1466

What can and what cannot be adjusted in the movement patterns of cerebellar patients?

Haggard, P. (1996) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00081668

In defense of PTC

Smolensky, P. (1990) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00079486

How and where does nitric oxide affect cerebellar synaptic plasticity? New methods for investigating its action

Bindman, L. J. (1996) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00081541

Comparative Analysis of the CAP Reform Impacts in Diversified Agricultural Systems

Prosperi, M. (2004) · Journal of Rural Problems · doi:10.7310/arfe1965.40.315

The High Precise Optimization Algorithm and rational construct study of multi-layered feed-forward neural network

Xiang-lin, H., Liu, Y., & Li, Q. (2014) · Chinese Control and Decision Conference (CCDC) · doi:10.1109/ccdc.2014.6852566

Understanding the Genetic Etiology of Complex Phenotypes using Bayesian Neural Networks

Beam, A. L. (2014) · NCSU Libraries Repository (North Carolina State University Libraries)

Metoda ekstrakcji modeli wyceny składki ubezpieczeniowej ze źródeł

Ekonomicznej, K. I. (2015)

Artificial neural networks applied to the resolution of regression and classification multivariate analysis problems in the agricultural and the industrial fields

Martínez-Martínez, V. (2016) · doi:10.35376/10324/16709

Applications of machine learning in sensorimotor control

Bradley, S. (2016) · cIRcle (University of British Columbia) · doi:10.14288/1.0166596

Neural networks for legal quantum prediction

Terrett, A. J. (2009) · bepress Legal Repository · doi:10.14288/1.0077428

Extra»~o Automtica de Conhecimento por M¶ ultiplos Indutores

Monard, M. C. (2001)

Kernel Online Multi-task Learning

Sumitra, S., & Aravindh, A. (2015) · Advances in intelligent systems and computing · doi:10.1007/978-981-10-0251-9_7

Surveillance Data Analytics

Yan, W. Q. (2016) · Springer eBooks · doi:10.1007/978-3-319-28515-3_4

Layered Neural Networks

Domany, E., & Meir, R. (1995) · Physics of neural networks · doi:10.1007/978-3-642-79814-6_9

Estimating and M odeling M onthly M ean D aily G lobal S olar R adiation on H or i- zontal S urfaces U sing A rtificial N eural N e tworks in S outh E ast of Iran

Ameri, M. (2015)

Computational intelligence approach for prediction of hardness performance in coating process

Mohamad, M. A. (2014)

METODOLOGÍA BAYESANA APLICADA AL ESTUDIO DE CONFIGURACIONES ESPACIALES EN BIOINFORMÁTICA.

Matemáticas, F. D. C. (2010)

Formation of structure in cortical networks through spike timing-dependent plasticity

Ocker, G. K. (2015) · D-Scholarship@Pitt (University of Pittsburgh)

Metodología de clasificación de señales electromiográficas

Vásquez, J. R. C., Oria, J. I. C., & Yáñez-Márquéz, C. (2015) · Research in Computing Science · doi:10.13053/rcs-105-1-13

Image retrieval by statistical features and artificial neural networks

Melnyk, R. A., & Zawyalow, A. (2016) · International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science · doi:10.1109/tcset.2016.7452159

Hardware spiking neural network and remote FPGA lab

Cawley, S. (2013) · Arrow@dit (Dublin Institute of Technology) · doi:10.13025/16058

Étude du potentiel de création de formes du quantron

Hackenbeck-Lambert, J. (2011) · PolyPublie (École Polytechnique de Montréal)

Theory and algorithm of state minimization of linear separation automata

Numai, Y. (2011) · Institutional Repositories DataBase (IRDB)

Clustering approach to protein folding problem and dynamics of the tropical atmosphere

Mikhail, F. (2016) · doi:10.32657/10356/66991

Statistical Methods in Applied Computer Science Lecture Notes Preliminary for course 2D5342, Data Mining, Jan-April 2006.

Arnborg, S., & Nada, K. (2006)

Architectures for communication between processes and software layers for a simulator for biological neural networks.

Eppler, J. M. (2010) · FreiDok plus (Universitätsbibliothek Freiburg)

Modeling Movement Disorders in Parkinson's Disease using Computational Intelligence

Lacy, S. (2015) · White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York)

實證探究多種鑑別式語言模型於語音辨識之研究 (Empirical Comparisons of Various Discriminative Language Models for Speech Recognition) [In Chinese].

Lai, M.-H., Huang, B.-X., Chen, K., & Chen, B. (2011) · International Conference on Computational Linguistics

A Pseudoregression Formulation of Emphasized Soft Target Procedures for Classification Problems

Jelali, S. E., Lyhyaoui, A., & Figueiras-Vidal, A. R. (2010)

Experience-Based Control and Coordination of Autonomous Mobile Systems in Dynamic Environments

Buck, S. (2003) · mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich)

鑑別式語言模型於語音辨識結果重新排序之研究 (Exploiting Discriminative Language Models for Reranking Speech Recognition Hypotheses) [In Chinese]

Liu, C.-W., Lin, S.-H., & Chen, B. (2010) · International Conference on Computational Linguistics

MODELACIÓN DE LA ESTRUCTURA JERÁRQUICA DE MACROINVERTEBRADOS BENTÓNICOS A TRAVÉS DE REDES NEURONALES ARTIFICIALES Modeling of the Hierarchical Structure of Freshwater Macroinvertebrates Using Artificial Neural Networks

Rico, C. L. V., Fernández, N., & Marino, B. M. (2009)

Machine learning with Lipschitz classifiers

Stuhlsatz, A. (2010) · Digitalen Hochschulbibliothek Sachsen-Anhalt (Universitäts- und Landesbibliothek Sachsen-Anhalt) · doi:10.25673/5050

Step Function Approximation for Support Vector Reduction

Allahyar, A., & Yazdi, H. S. (2014)

Data : Report from the JSRT Sectional Committee on Medical imaging "Recommended References on Radiological Imaging Research"

Shiraishi, J. (2004) · Japanese Journal of Radiological Technology · doi:10.6009/jjrt.kj00000922568

THE PERCEPTRON: A PROBABILISTIC MODEL FOR INFORMATION STORAGE AND ORGANIZATION

Brain, I. T., & Rosenblatt, F. F. (2013)

The perception: a probabilistic model for information storage and organization in the brain

Rosenblatt, F. F. (1988) · The MIT Press eBooks · Cited by 78

(1958) F. Rosenblatt, "The perceptron: a probabilistic model for information storage and organization in the brain," Psychological Review 65: 386-408

Rosenblatt, F. F. (1988) · The MIT Press eBooks · doi:10.7551/mitpress/4943.003.0010 · Cited by 13

Perception, memory and providing information

Upton, D. (2013) · doi:10.4324/9781315846972-11

Brain mechanisms of perception and memory from neuron to behavior

Ono, T., & Toyama, I. S. O. B. M. O. P. A. M. F. N. T. B. 1. (1993)