Emergent neural computational architectures based on neuroscience : towards neuroscience-inspired computing

It is generally understood that the present approachs to computing do not have the performance, flexibility, and reliability of biological information processing systems. Although there is a comprehensive body of knowledge regarding how information processing occurs in the brain and central nervous...

সম্পূর্ণ বিবরণ

সংরক্ষণ করুন:
গ্রন্থ-পঞ্জীর বিবরন
প্রধান লেখক: Wermter, Stefan, 1961-
অন্যান্য লেখক: Austin, Jim (Publishing director), Willshaw, David J. (Publishing director)
বিন্যাস: Livre numérique
ভাষা:Anglais
প্রকাশিত: Berlin [etc.] : Springer [20..].
Cham : Springer Nature
মালা:Lecture notes in computer science. Lecture notes in artificial intelligence 2036
বিষয়গুলি:
অনলাইন ব্যবহার করুন:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
টীকা: Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Autres localisations: Voir dans le Sudoc
Edition sous un autre format:• Emergent neural computational architectures based on neuroscience, towards neuroscience-inspired computing, Stefan Wermter, Jim Austin, David J. Willshaw, New York, Springer-Verlag, 2001, 1 vol. (x-576 p.), Lecture notes in computer science, 3-540-42363-X
• Emergent Neural Computational Architectures Based on Neuroscience, Texte imprimé, 9783662186749
সূচিপত্রের সারণি:
  • Towards Novel Neuroscience-Inspired Computing
  • Towards Novel Neuroscience-Inspired Computing
  • Modular Organisation and Robustness
  • Images of the Mind: Brain Images and Neural Networks
  • Stimulus-Independent Data Analysis for fMRI
  • Emergence of Modularity within One Sheet of Neurons: A Model Comparison
  • Computational Investigation of Hemispheric Specialization and Interactions
  • Explorations of the Interaction between Split Processing and Stimulus Types
  • Modularity and Specialized Learning: Mapping between Agent Architectures and Brain Organization
  • Biased Competition Mechanisms for Visual Attention in a Multimodular Neurodynamical System
  • Recurrent Long-Range Interactions in Early Vision
  • Neural Mechanisms for Representing Surface and Contour Features
  • Representations of Neuronal Models Using Minimal and Bilinear Realisations
  • Collaborative Cell Assemblies: Building Blocks of Cortical Computation
  • On the Influence of Threshold Variability in a Mean-Field Model of the Visual Cortex
  • Towards Computational Neural Systems through Developmental Evolution
  • The Complexity of the Brain: Structural, Functional, and Dynamic Modules
  • Timing and Synchronisation
  • Synchronisation, Binding, and the Role of Correlated Firing in Fast Information Transmission
  • Segmenting State into Entities and Its Implication for Learning
  • Temporal Structure of Neural Activity and Modelling of Information Processing in the Brain
  • Role of the Cerebellum in Time-Critical Goal-Oriented Behaviour: Anatomical Basis and Control Principle
  • Locust Olfaction
  • Temporal Coding in Neuronal Populations in the Presence of Axonal and Dendritic Conduction Time Delays
  • The Role of Brain Chaos
  • Neural Network Classification of Word Evoked Neuromagnetic Brain Activity
  • Simulation Studies of the Speed of Recurrent Processing
  • Learning and Memory Storage
  • The Dynamics of Learning and Memory: Lessons from Neuroscience
  • Biological Grounding of Recruitment Learning and Vicinal Algorithms in Long-Term Potentiation
  • Plasticity and Nativism: Towards a Resolution of an Apparent Paradox
  • Cell Assemblies as an Intermediate Level Model of Cognition
  • Modelling Higher Cognitive Functions with Hebbian Cell Assemblies
  • Spiking Associative Memory and Scene Segmentation by Synchronization of Cortical Activity
  • A Familiarity Discrimination Algorithm Inspired by Computations of the Perirhinal Cortex
  • Linguistic Computation with State Space Trajectories
  • Robust Stimulus Encoding in Olfactory Processing: Hyperacuity and Efficient Signal Transmission
  • Finite-State Computation in Analog Neural Networks: Steps towards Biologically Plausible Models?
  • An Investigation into the Role of Cortical Synaptic Depression in Auditory Processing
  • The Role of Memory, Anxiety, and Hebbian Learning in Hippocampal Function: Novel Explorations in Computational Neuroscience and Robotics
  • Using a Time-Delay Actor-Critic Neural Architecture with Dopamine-Like Reinforcement Signal for Learning in Autonomous Robots
  • Connectionist Propositional Logic A Simple Correlation Matrix Memory Based Reasoning System
  • Analysis and Synthesis of Agents That Learn from Distributed Dynamic Data Sources
  • Connectionist Neuroimaging.