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From Natural to Artificial Neural Computation

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Cover of 'From Natural to Artificial Neural Computation'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 149 Are there universal principles of brain computation?
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    Chapter 150 Modeling cortical networks
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    Chapter 151 Cooperative organization of connectivity patterns and receptive fields in the visual pathway: application to adaptive tresholding
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    Chapter 152 Neurobiological inspiration for the architecture and functioning of cooperating neural networks
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    Chapter 153 Synaptic modulation based artificial neural networks
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    Chapter 154 Self-organization of cortical receptive fields and columnar structures in a Hebb-trained neural network
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    Chapter 155 An analytical solution of the compartmental model for use in local learning in artificial neural networks
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    Chapter 156 Should ANN be ANGN?
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    Chapter 157 Modeling retinal high and low contrast sensitivity filters
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    Chapter 158 Neural micro-structures three simple models
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    Chapter 159 Adaptive hierarchical structures
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    Chapter 160 Optimal range of input resistance in the oscillatory behavior of the pancreatic β-cell
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    Chapter 161 A computational model of periodic-pattern-selective cells
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    Chapter 162 Modeling and analysis of some neural mechanisms for the genesis and control of respiratory pattern
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    Chapter 163 A neural network model for plasticity in adult striate cortex
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    Chapter 164 Regenerative-type neural interface
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    Chapter 165 New perspectives in auditory coding: Bases for a new cochlear behavioural model
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    Chapter 166 Nervous system as a closed neuronal network: behavioral and cognitive consequences
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    Chapter 167 Local accumulation of persistent activity at synaptic level: Application to motion analysis
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    Chapter 168 High Order Boltzmann Machines with continuous units: Some experimental results
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    Chapter 169 An adaptive control model of a locomotion by the central pattern generator
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    Chapter 170 Self-consistent neural receptive fields
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    Chapter 171 A simple probabilistic neural model producing multimodal ISHs
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    Chapter 172 An associative neural network to model the developing mammalian hippocampus
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    Chapter 173 The implementation of propositional logic in random neural networks
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    Chapter 174 From Natural to Artificial Neural Computation
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    Chapter 175 The influence of the sigmoid function parameters on the speed of backpropagation learning
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    Chapter 176 General transient length upper bound for recurrent neural networks
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    Chapter 177 On some methods in neuromathematics (or the development of mathematical methods for the description of structure and function in neurons)
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    Chapter 178 Logistic networks with DNA-like encoding and interactions
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    Chapter 179 A review on the stochastic firing behaviour of real neurons and how it can be modelled
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    Chapter 180 The BP-λL1 algorithm: Non-chaotic and accelerated learning in a MLP network
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    Chapter 181 Analysis of pruning in backpropagation networks for artificial and real world mapping problems
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    Chapter 182 Oscillatory networks with Hebbian matrix of connections
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    Chapter 183 A new algorithm for implementing a recursive neural network
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    Chapter 184 Visual information processing from the viewpoint of symbolic operations
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    Chapter 185 Dentritic computation in the brain
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    Chapter 186 Stochastic neuronal models with realistic synaptic inputs and oscillatory inputs
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    Chapter 187 A neural paradigm for controlling autonomous systems with reflex behaviour and learning capability
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    Chapter 188 Fast automatic architecture selection in RBF networks
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    Chapter 189 Collective behaviour of a chain of Hopfield subnetworks interconnected unidirectionally
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    Chapter 190 A comparative study of three neural networks that use soft competition
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    Chapter 191 Neural networks and genetic algorithms for the attitude control problem
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    Chapter 192 Self-organising Artifical Neural Networks
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    Chapter 193 A distributed classifier based on Yprel networks cooperation
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    Chapter 194 A fractal, selforganizing map with partially chaotic neurons
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    Chapter 195 Multiple self-organizing maps for supervised learning
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    Chapter 196 An application of the saturated attractor analysis to three typical models
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    Chapter 197 Learning in evolutive neural architectures: An ill-posed problem?
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    Chapter 198 Automatic scaling using gamma learning for feedforward neural networks
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    Chapter 199 Determining the significance of input parameters using sensitivity analysis
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    Chapter 200 Multi-valued neurons: Learning, networks, application to image recognition and extrapolation of temporal series
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    Chapter 201 Individual evolutionary algorithm and its application to learning of nearest neighbor based MLP
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    Chapter 202 A practical view of suboptimal Bayesian classification with radial Gaussian kernels
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    Chapter 203 Schema based learning & learning to Detour
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    Chapter 204 Neurons with continuous varying activation in self-organizing maps
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    Chapter 205 Improving back-propagation: Epsilon-back-propagation
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    Chapter 206 Finite State Automata and Connectionist Machines: A survey
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    Chapter 207 Learning transformed prototypes (LTP) — A statistical pattern classification technique of neural networks
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    Chapter 208 Fuzzy function estimators as basis on learning from experience
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    Chapter 209 Connectionists and statisticians, friends or foes?
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    Chapter 210 Unsupervised neural networks for speech perception with Cochlear Implant systems for the profoundly deaf
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    Chapter 211 Obstacle avoidance by means of an operant conditioning model
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    Chapter 212 Qualitative approach to gradient based learning algorithms
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    Chapter 213 Character recognition with neural assemblies
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    Chapter 214 Learning by attentional scanning
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    Chapter 215 The synthesis of the ranked neural networks applying genetic algorithm with the dynamic probability of mutation
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    Chapter 216 Global versus local Heuristic Terminal Attractor
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    Chapter 217 Dynamic learning of radial bases functions for fuzzy clustering
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    Chapter 218 Incremental learning with a stopping criterion experimental results
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    Chapter 219 Learning algorithm with gaussian membership function for Fuzzy RBF Neural Networks
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    Chapter 220 Neural network initialization
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    Chapter 221 Bidirectional Neural Networks reduce generalisation error
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    Chapter 222 Balancing bias and variance: Network topology and pattern set reduction techniques
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    Chapter 223 Priming an artificial neural classifier
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    Chapter 224 Artificial neuroconsciousness an update
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    Chapter 225 Physical and linguistic problems in the modelling of consciousness by neural networks
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    Chapter 226 A neural network model for the velocity vector of an object and its consistency with psychological phenomena
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    Chapter 227 Implementation and evaluation of a Relevance Feedback device based on Neural Networks
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    Chapter 228 Second-order recurrent neural networks can learn regular grammars from noisy strings
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    Chapter 229 Extracting DNF rules from artificial neural networks
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    Chapter 230 Dynamic symbol grounding, state construction and the problem of teleology
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    Chapter 231 Analysis of industrial economics by means of neural nets
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    Chapter 232 Effects of spatial frequency and stimulus size on the orientation sensitivity of humans
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    Chapter 233 Object oriented design of a simulator for large BP Neural Networks
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    Chapter 234 Introducing XSim: A neural network simulator that incorporates biological parameters
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    Chapter 235 NETTOOL: A hybrid connectionist-symbolic development environment
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    Chapter 236 EL-SIM: a development environment for neuro-fuzzy intelligent controllers
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    Chapter 237 Packlib, an interactive environment to develop modular software for data processing
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    Chapter 238 NSL — Neural Simulation Language
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    Chapter 239 Low-cost accelerator for the simulation of Cellular Neural Networks
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    Chapter 240 A VLSI system for neural Bayesian and LVQ classification
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    Chapter 241 An associative processor dedicated to classification by neural methods
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    Chapter 242 Hardware-Oriented models for VLSI implementation of Self-Organizing Maps
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    Chapter 243 Hardware requirements for spike-processing neural networks
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    Chapter 244 A VLSI approach to the implementation of additive and shunting neural networks
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    Chapter 245 A low-power analog implementation of Cellular Neural Networks
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    Chapter 246 Asynchonously parallel Boltzmann Machines mapped onto distributed-memory multiprocessors
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    Chapter 247 A coprocessor card for fast neural network emulation
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    Chapter 248 Digital hardware implementation of ROI incremental algorithms
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    Chapter 249 Comparing implementations of Radial Basis Function Neural Networks on three parallel machines
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    Chapter 250 Implementing Radial Basis Functions Neural Networks on the systolic MANTRA machine
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    Chapter 251 A mixed parallel-sequential SHNN for large networks
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    Chapter 252 A modular VLSI architecture for neural networks implementation
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    Chapter 253 A massively parallel neurocomputer with a reconfigurable arithmetical unit
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    Chapter 254 An all-optical forward propagation multilayer neural network
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    Chapter 255 A VLSI current mode synapse chip
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    Chapter 256 Optimal mapping of neural networks onto FPGAs
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    Chapter 257 A CPWM synapsis for Weighted Radial Basis Functions
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    Chapter 258 Test pattern generation for analog circuits using neural networks and evolutive algorithms
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    Chapter 259 About some perception problems in neural networks
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    Chapter 260 Optimization neural networks for image segmentation
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    Chapter 261 Segmentation of range images: A neural network approach
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    Chapter 262 A neural architecture for preattentive segmentation of sewage pipes video images
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    Chapter 263 A CNN model for grey scale image processing
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    Chapter 264 Kohonen's self-organizing maps for contour segmentation of gray level and color images
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    Chapter 265 A geometrical based procedure for source separation mapped to a neural network
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    Chapter 266 Quasi-optimum combination of multilayer perceptrons for adaptive multiclass pattern recognition
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    Chapter 267 A text recognition system based on a Neural Network and on a Deformed System
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    Chapter 268 Simultaneous recognition of multiple objects using the MEM model
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    Chapter 269 On-line handwritten character recognition by a hybrid method based on neural networks and pattern matching
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    Chapter 270 Analysis and application of the store neural model in recognizing handwritted symbols
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    Chapter 271 An adaptative orthogonal asociative memory and its application to character recognition
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    Chapter 272 Texture classification on real time using semi-cover vector and an orthogonal neural network
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    Chapter 273 An architecture for texture segmentation: from energy features to region detection
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    Chapter 274 A lattice-based Time-Delay Neural Network for speech processing
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    Chapter 275 Acquisition of internal representation by learning of identity-mapping using overload learning
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    Chapter 276 A multiacuity connectionist model for local speed estimation
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    Chapter 277 Using Artificial Neural Networks for ultrasonic signals processing from simple geometric shapes
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    Chapter 278 A hierarchical neural network for mobile visual tracking with a robot head
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    Chapter 279 Short-term load forecasting using neural nets
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    Chapter 280 Image compression using feedforward neural networks — Hierarchical approach
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    Chapter 281 Neural approaches to robot control: Four representative applications
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    Chapter 282 On line identification of causal relationships between variables in the feed water system of a nuclear power plant
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    Chapter 283 Dynamic neural units for nonlinear dynamic systems identification
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    Chapter 284 Optimal identification using feed-forward neural networks
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    Chapter 285 Recurrent neural networks for identification of friction
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    Chapter 286 Solving an end-effector positioning problem by Hopfield neural network
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    Chapter 287 Visuomotor control using an artificial neural network
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    Chapter 288 Learning the visuomotor coordination of a mobile robot by using the invertible Kohonen Map
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    Chapter 289 Neural networks for automatic fuzzy control system design
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    Chapter 290 Supervised classification with variable kernel estimators
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    Chapter 291 Daily electrical power curves: Classification and forecasting using a Kohonen map
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    Chapter 292 CMAC real-time adaptive control implementation on a D.S.P. based card
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    Chapter 293 Neural networks in digital data transmission
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    Chapter 294 A new neural network approach to the floorplanning of hierarchical VLSI designs
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    Chapter 295 A neural network approach to Quality Control Charts
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    Chapter 296 Bankruptcy prediction with Artificial Neural Networks
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
2 news outlets
patent
7 patents
wikipedia
11 Wikipedia pages

Citations

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33 Dimensions

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11 Mendeley
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Title
From Natural to Artificial Neural Computation
Published by
Lecture notes in computer science, January 1995
DOI 10.1007/3-540-59497-3
ISBNs
978-3-54-059497-0, 978-3-54-049288-7
Authors

José Mira, Francisco Sandoval

Editors

Mira, José, Sandoval, Francisco

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 36%
Student > Ph. D. Student 2 18%
Researcher 2 18%
Professor > Associate Professor 1 9%
Unknown 2 18%
Readers by discipline Count As %
Engineering 5 45%
Mathematics 1 9%
Environmental Science 1 9%
Neuroscience 1 9%
Computer Science 1 9%
Other 0 0%
Unknown 2 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 23. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 February 2024.
All research outputs
#1,400,253
of 23,114,117 outputs
Outputs from Lecture notes in computer science
#220
of 8,146 outputs
Outputs of similar age
#867
of 76,854 outputs
Outputs of similar age from Lecture notes in computer science
#1
of 24 outputs
Altmetric has tracked 23,114,117 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,146 research outputs from this source. They receive a mean Attention Score of 5.0. This one has done particularly well, scoring higher than 97% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 76,854 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.