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New Trends in Neural Computation

Overview of attention for book
Cover of 'New Trends in Neural Computation'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 116 Biophysics of neural computation
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    Chapter 117 Integrated learning in rana computatrix
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    Chapter 118 A model for centering visual stimuli through adaptive value learning
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    Chapter 119 A model for the development of neurons selective to visual stimulus size
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    Chapter 120 An invariant representation mechanism after presynaptic inhibition
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    Chapter 121 The pancreatic B-cell as a voltage-controlled oscillator
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    Chapter 122 Approximation of the solution of the dendritic cable equation by a small series of coupled differential equations
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    Chapter 123 A neural network model inspired in global appreciations about the thalamic reticular nucleus and cerebral cortex connectivity
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    Chapter 124 Towards more realistic self contained models of neurons: High-order, recurrence and local learning
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    Chapter 125 McCulloch's neurons revisited
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    Chapter 126 Biologically motivated approach to face recognition
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    Chapter 127 Learning by reinforcement: A psychobiological model
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    Chapter 128 A neural state machine for iconic language representation
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    Chapter 129 Variable binding using serial order in recurrent neural networks
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    Chapter 130 Region of influence (ROI) networks. Model and implementation
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    Chapter 131 A node splitting algorithm that reduces the number of connections in a Hamming distance classifying network
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    Chapter 132 A high order neural model
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    Chapter 133 Higher-order networks for the optimization of block designs
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    Chapter 134 Neural Bayesian classifier
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    Chapter 135 Constructive methods for a new classifier based on a radial-basis-function neural network accelerated by a tree
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    Chapter 136 Practical realization of a radial basis function network for handwritten digit recognition
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    Chapter 137 Design of fully and partially connected random neural networks for pattern completion
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    Chapter 138 Representation and recognition of regular grammars by means of second-order recurrent neural networks
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    Chapter 139 Connectionist models for syllabic recognition in the time domain
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    Chapter 140 Sparsely interconnected artificial neural networks for associative memories
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    Chapter 141 Dynamic analysis of networks of neural oscillators
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    Chapter 142 Optimised attractor neural networks with external inputs
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    Chapter 143 Non-orthogonal bases and metric tensors: An application to artificial neural networks
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    Chapter 144 Genetic synthesis of discrete-time recurrent neural network
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    Chapter 145 Optimization of a competitive learning neural network by genetic algorithms
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    Chapter 146 Adaptive models in neural networks
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    Chapter 147 Self-organizing grammar induction using a neural network model
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    Chapter 148 The role of forgetting in efficient learning strategies for self-organising discriminator-based systems
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    Chapter 149 Simulation of stochastic regular grammars through simple recurrent networks
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    Chapter 150 Local stochastic competition and vector quantization
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    Chapter 151 MHC — An evolutive connectionist model for hybrid training
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    Chapter 152 Fast-convergence learning algorithms for multi-level and binary neurons and solution of some image processing problems
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    Chapter 153 Invariant object recognition using fahlman and Lebiere's learning algorithm
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    Chapter 154 Realization of subjective correspondence in artificial neural network trained by Fahlman and Lebiere's learning algorithm
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    Chapter 155 Bimodal distribution removal
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    Chapter 156 A simplified ARTMAP architecture for real-time learning
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    Chapter 157 B-Learning: A reinforcement learning algorithm, comparison with dynamic programming
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    Chapter 158 Increased complexity training
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    Chapter 159 Optimized learning for improving the evolution of piecewise linear separation incremental algorithms
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    Chapter 160 A method of pruning layered feed-forward neural networks
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    Chapter 161 Tests of different regularization terms in small networks
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    Chapter 162 On the distribution of feature space in Self-Organising mapping and convergence accelerating by a Kalman algorithm
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    Chapter 163 A learning algorithm to obtain self-organizing maps using fixed neighbourhood Kohonen networks
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    Chapter 164 Analysing a contingency table with Kohonen maps: A factorial correspondence analysis
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    Chapter 165 Dynamics of self-organized feature mapping
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    Chapter 166 Comparative study of self-organizing neural networks
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    Chapter 167 GANNet: A genetic algorithm for optimizing topology and weights in neural network design
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    Chapter 168 Vector quantization and projection neural network
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    Chapter 169 Constructive design of LVQ and DSM classifiers
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    Chapter 170 Linear vector classification: An improvement on LVQ algorithms to create classes of patterns
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    Chapter 171 Non-greedy adaptive vector quantizers
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    Chapter 172 Hybrid programming environments
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    Chapter 173 Automatic generation of C++ code for neural network simulation
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    Chapter 174 Urano: An object-oriented artificial neural network simulation tool
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    Chapter 175 Realistic simulation tool for early visual processing including space, time and colour data
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    Chapter 176 Language supported storage and reuse of persistent neural network objects
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    Chapter 177 Flexible operating environment for matrix based neurocomputers
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    Chapter 178 A parallel implementation of kohonen's self-organizing maps on the smart neurocomputer
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    Chapter 179 Simulation of neural networks in a distributed computing environment using Neurograph
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    Chapter 180 Full automatic ann design: A genetic approach
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    Chapter 181 Hardware implementations of artificial neural networks
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    Chapter 182 A neural network chip using CPWM modulation
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    Chapter 183 Hardware implementation of a neural network for high energy physics application
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    Chapter 184 MapA: An array processor architecture for neural networks
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    Chapter 185 Limitation of connectionism in MLP
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    Chapter 186 High level synthesis of neural network chips
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    Chapter 187 Neural network simulations on massively parallel computers: Applications in chemical physics
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    Chapter 188 A model based approach to the performance analysis of multi-layer networks realised in linear systolic arrays
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    Chapter 189 The temporal noisy-leaky integrator neuron with additional inhibitory inputs
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    Chapter 190 Architectures for self-learning neural network modules
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    Chapter 191 The generic neuron architectural framework for the automatic generation of ASICs
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    Chapter 192 A risc architecture to support neural net simulation
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    Chapter 193 Hardware design for self organizing feature maps with binary input vectors
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    Chapter 194 The Kolmogorov signal processor
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    Chapter 195 Projectivity invariant pattern recognition with high-order neural networks
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    Chapter 196 Rejection of incorrect answers from a neural net classifier
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    Chapter 197 Nonlinear time series modeling by competitive segmentation of state space
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    Chapter 198 Identification and prediction of non-linear models with recurrent neural network
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    Chapter 199 Use of unsupervised neural networks for classification of blood pressure time series
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    Chapter 200 Application of artificial neural networks to chest image classification
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    Chapter 201 Combination of self-organizing maps and multilayer perceptrons for speaker independent isolated word recognition
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    Chapter 202 An industrial application of neural networks to natural textures classification
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    Chapter 203 Use of a layered neural nets as a display method for n-dimensional distributions
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    Chapter 204 MLP modular versus yprel classifiers
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    Chapter 205 How many hidden neurons are needed to recognize a symmetrical pattern ?
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    Chapter 206 Hopfield neural network for routing
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    Chapter 207 Neural network routing controller for communication parallel multistage interconnection networks
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    Chapter 208 Adaptive routing using cellular automata
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    Chapter 209 Optimal blind equalization of Gaussian channels
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    Chapter 210 Noise prediction in urban traffic by a neural approach
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    Chapter 211 A connectionist approach to the correspondence problem in computer vision
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    Chapter 212 Self-organizing feature maps for image segmentation
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    Chapter 213 Recognition of fractal images using a neural network
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    Chapter 214 Feed forward network for vehicle license character recognition
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    Chapter 215 Interpretation of optical flow through complex neural network
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    Chapter 216 CT image segmentation by self-organizing learning
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    Chapter 217 Texture image segmentation using a modified Hopfield network
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    Chapter 218 Image compression with self-organizing networks
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    Chapter 219 Neural networks as direct adaptive controllers
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    Chapter 220 A neural adaptive controller for a turbofan exhaust nozzle
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    Chapter 221 Feed-forward neural networks for bioreactor control
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    Chapter 222 Learning networks for process identification and associative action
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    Chapter 223 On-line performance enhancement of a behavioral neural network controller
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    Chapter 224 An architecture for implementing control and signal processing neural networks
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    Chapter 225 Planlite: Adaptive planning using weightless systems
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    Chapter 226 Stock prices and volume in an artificial adaptive stock market
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    Chapter 227 Application of the Fuzzy ARTMAP neural network architecture to bank failure predictions
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    Chapter 228 Combination of neural network and statistical methods for sensory evalution of biological products: On-line beauty selection of flowers
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    Chapter 229 An adaptive information retrieval system based on Neural Networks
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    Chapter 230 Software pattern EEG recognition after a wavelet transform by a neural network
Overall attention for this book and its chapters
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About this Attention Score

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Mentioned by

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3 X users

Citations

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Title
New Trends in Neural Computation
Published by
Lecture notes in computer science, January 1993
DOI 10.1007/3-540-56798-4
ISBNs
978-3-54-056798-1, 978-3-54-047741-9
Authors

José Mira, Joan Cabestany, Alberto Prieto

Editors

Mira, José, Cabestany, Joan, Prieto, Alberto

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 1 13%
Student > Bachelor 1 13%
Student > Master 1 13%
Unknown 5 63%
Readers by discipline Count As %
Mathematics 1 13%
Business, Management and Accounting 1 13%
Computer Science 1 13%
Unknown 5 63%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 26 February 2019.
All research outputs
#14,670,014
of 24,601,689 outputs
Outputs from Lecture notes in computer science
#4,082
of 8,157 outputs
Outputs of similar age
#54,737
of 68,054 outputs
Outputs of similar age from Lecture notes in computer science
#10
of 16 outputs
Altmetric has tracked 24,601,689 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,157 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
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 68,054 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.