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Real-Time Multi-Chip Neural Network for Cognitive Systems

Neural Network for Cognitive Systems presents novel real-time, reconfigurable, multi-chip SNN system architecture based on localized;

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Multi model Jumping Systems Robust Filtering and Fault Detection

well as higher order moment and neural network-based fault detection methods for multi-model jumping systems, allowing them to grasp the;

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Cellular Neural Networks, Multi-scroll Chaos And Synchronization

. Cellular neural networks and their universal machine implementations offer a well-established platform for processing spatial-temporal patterns and;

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Convergence of Communications, Navigation, Sensing and Services

Networks * Brain Computer Interfacing * Quality Improvement of Generic Services * Machine to Machine communications * Chip to Chip;

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Neural Fuzzy Control Systems With Structure And Parameter Learning

A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed in this book for the realization of a;

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Neural Networks Modeling and Control

Neural Networks Modelling and Control: Applications for Unknown Nonlinear Delayed Systems in Discrete Time focuses on modeling and;

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Congress on Intelligent Systems

transportation, artificial intelligence for machine vision, imaging sensors technology, image segmentation, convolutional neural network, image/video;

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Congress on Intelligent Systems

transportation, artificial intelligence for machine vision, imaging sensors technology, image segmentation, convolutional neural network, image/video;

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New Developments in Computer Networks

cluster; fuzzy-based controller for improvement of network performance; multi-layer perceptron artificial neural network; fault detection and;

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Neural Network Control of Nonlinear Discrete-Time Systems

methods in more complex systems. Borrowing from Biology Examining neurocontroller design in discrete-time for the first time, Neural Network;

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Fuzzy Logic Based Power-Efficient Real-Time Multi-Core System

Multi-Processor Systems on Chip (MPSoCs) in both simulation and real-time environments, it is divided into two major parts. The first part deals;

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Neural Information Processing

processing research. The 3 volumes represent topical sections containing articles on cognitive science, neural networks and learning systems, theory;

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Neural Information Processing

processing research. The 3 volumes represent topical sections containing articles on cognitive science, neural networks and learning systems, theory;

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Reconfigurable and Adaptive Computing

access, end-to-end quality-of-service metrics modeling based on a multi-application environment in network-on-chip, and a 3D ant colony routing;

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Reconfigurable and Adaptive Computing

access, end-to-end quality-of-service metrics modeling based on a multi-application environment in network-on-chip, and a 3D ant colony routing;

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Neural Network Modeling and Identification of Dynamical Systems

Neural Network Modeling and Identification of Dynamical Systems presents a new approach on how to obtain the adaptive neural network;

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Distributed Real-Time Architecture for Mixed-Criticality Systems

criticality coexist and interact on networked multi-core chips. The architecture leverages multi-core platforms for a hierarchical system perspective;

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Multi-Agent Systems

control and non-fragile quantized consensus for multi-agent systems. The main feature of this book is that distributed adaptive sliding mode;

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Multi-Agent Systems

control and non-fragile quantized consensus for multi-agent systems. The main feature of this book is that distributed adaptive sliding mode;

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Architecture Of Network Systems

network-on-chip, network processors, algorithms for lookup and classification, and network systems for the next-generation Internet.

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Complex-Valued Neural Networks with Multi-Valued Neurons

who develop theoretical fundamentals of neural networks and use neural networks for solving various real-world problems. It should also be;

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Neuromorphic Computing Principles and Organization

is dedicated to the circuits and architectures used for communication in neuromorphic systems. In particular, the Network-on-Chip fabric is introduced;

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Stevens' Handbook of Experimental Psychology

; network models for clinical psychology; response time modeling; analyzing neural time series data; models and methods for reinforcement learning;

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Multi-Processor System-on-Chip 2 - Applications

A Multi-Processor System-on-Chip (MPSoC) is the key component for complex applications. These applications put huge pressure on memory;

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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to;

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Neuro-fuzzy Control of Industrial Systems with Actuator Nonlinearities

build intelligent controllers for real-time applications. Neural networks capture the parallel processing and learning capabilities;

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Einde inhoud

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