Advances in Neural Computation, Machine Learning, and Cognitive Research II

1. Front Matter

   Pages i-xvii

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2. Invited Papers

   1. Front Matter

      Pages 1-1

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   2. Quantumness and Irrationality

      • Alexandr A. Ezhov, Andrei G. Khromov, Svetlana S. Terentyeva

      Pages 3-13

   3. Planar Ising-Spin Models in Probabilistic Machine Learning

      • Iakov M. Karandashev

      Pages 14-38

   4. Intellectual Agents Based on a Cognitive Architecture Supporting Humanlike Social Emotionality and Creativity

      • Alexei V. Samsonovich

      Pages 39-50

   5. A Novel Methodology for Simulation of EEG Traveling Waves on the Folding Surface of the Human Cerebral Cortex

      • Vitaly M. Verkhlyutov, Vladislav V. Balaev, Vadim L. Ushakov, Boris M. Velichkovsky

      Pages 51-63

3. Neural Network Theory

   1. Front Matter

      Pages 65-65

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   2. Comparative Test of Evolutionary Algorithms to Build an Approximate Neural Network Solution of the Model Boundary Value Problem

      • A. R. Galyautdinova, J. S. Sedova, D. A. Tarkhov, E. A. Varshavchik, A. N. Vasilyev

      Pages 67-76

   3. Spectral Density of 1D Ising Model in n-Vicinity Method

      • Leonid Litinskii, Inna Kaganowa

      Pages 77-83

   4. Match-Mismatch Detection Neural Circuit Based on Multistable Neurons

      • Yury S. Prostov, Yury V. Tiumentsev

      Pages 84-90

   5. Hopfield Associative Memory with Quantized Weights

      • Mikhail S. Tarkov

      Pages 91-97

4. Applications of Neural Networks

   1. Front Matter

      Pages 99-99

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   2. Linear Filtering Based on a Pulsed Neuron Model with an Orthogonal Filter Bank

      • Vladimir Bondarev

      Pages 101-108

   3. Comparative Testing of the Neural Network and Semi-empirical Method on the Stabilization Problem of Inverted Pendulum

      • Egor A. Degilevich, Aleksandra M. Kobicheva, Valery A. Kozhin, Anastasia D. Subbota, Ilya Y. Surikov, Dmitry A. Tarkhov et al.

      Pages 109-114

   4. Homotopy Continuation Training Method for Semi-Empirical Continuous-Time State-Space Neural Network Models

      • Mikhail Egorchev, Yury Tiumentsev

      Pages 115-120

   5. Temperature Forecasting Based on the Multi-agent Adaptive Fuzzy Neuronet

      • E. A. Engel, N. E. Engel

      Pages 121-128

   6. The Neural Network with Automatic Feature Selection for Solving Problems with Categorical Variables

      • Yuriy S. Fedorenko, Yuriy E. Gapanyuk

      Pages 129-135

   7. Object Detection on Docking Images with Deep Convolutional Network

      • Ivan S. Fomin, Svetlana R. Orlova, Dmitrii A. Gromoshinskii, Aleksandr V. Bakhshiev

      Pages 136-143

   8. On Comparative Evaluation of Effectiveness of Neural Network and Fuzzy Logic Based Adjusters of Speed Controller for Rolling Mill Drive

      • Anton I. Glushchenko, Vladislav A. Petrov

      Pages 144-150

   9. Disease Detection on the Plant Leaves by Deep Learning

      • P. Goncharov, G. Ososkov, A. Nechaevskiy, A. Uzhinskiy, I. Nestsiarenia

      Pages 151-159

This book describes new theories and applications of artificial neural networks, with a special focus on addressing problems in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large-scale neural models, brain–computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XX International Conference on Neuroinformatics, held in Moscow, Russia on October 8–12, 2018.

• Deep neural networks
• Modeling inverse problems
• Additive noise
• Multilayer neural networks
• Boolean neural network
• Context dependent recognition
• Applications of adaptive neural networks
• Digital neural-network control system
• Traffic control methods
• Synchronous information environment
• Adaptive control systems
• Conference Proceedings

• Scientific Research Institute for System Analysis, Russian Academy of Sciences, Moscow, Russia

  Boris Kryzhanovsky, Witali Dunin-Barkowski, Vladimir Redko

• Moscow Aviation Institute (National Research University), Moscow, Russia

  Yury Tiumentsev

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