A New Approach to Adaptive Filters
Springer series in information sciencesPublished 1 January 1989
Teuvo Kohonen
Citations3
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
A critical analysis is aiming at a critical analysis, mainly with an objective to find amendments to the early ideas of artificial intelligence using formal models of neurons and Perceptron networks.
Abstract
The early works around 1960 on learning machines may be characterized as attempts to implement artificial intelligence using formal models of neurons and Perceptron networks, obviously in the hope that more and more complex functions would gradually evolve from such structures. There is no doubt about the biological organisms having that fundamental organization. Why was the success in artificial constructs not straightforward as expected? Below I am aiming at a critical analysis, mainly with an objective to find amendments to the early ideas.
Keywords
Computer ScienceEngineering
The Journal of PhysiologyA quantitative description of membrane current and its application to conduction and excitation in nerve
23,234 Citations1952A. L. Hodgkin, A. F. Huxley
This article concludes a series of papers concerned with the flow of electric current through the surface membrane of a giant nerve fibre by putting them into mathematical form and showing that they will account for conduction and excitation in quantitative terms.
Biological CyberneticsSelf-organized formation of topologically correct feature maps
9,519 Citations1982Teuvo Kohonen
In a simple network of adaptive physical elements which receives signals from a primary event space, the signal representations are automatically mapped onto a set of output responses in such a way that the responses acquire the same topological order as that of the primary events.
Journal of Mathematical BiologySimplified neuron model as a principal component analyzer
2,343 Citations1982Erkki Oja
A simple linear neuron model with constrained Hebbian-type synaptic modification is analyzed and a new class of unconstrained learning rules is derived.
IEEE Transactions on ComputersCorrelation Matrix Memories
878 Citations1972Teuvo Kohonen
A new model for associative memory, based on a correlation matrix, is suggested, in which any part of the memorized information can be used as a key and the memories are selective with respect to accumulated data.
Psychological ReviewDistinctive features, categorical perception, and probability learning: Some applications of a neural model.
860 Citations1977James A. Anderson, Jack W. Silverstein +2 more
The model can predict overshooting, recency data, and probabilities occurring in systems with more than two events with reasonably good accuracy and applies the model to "categorical perception" and probability learning.
Biological CyberneticsFigure-ground discrimination by relative movement in the visual system of the fly
212 Citations1983W. Reichardt, Tomaso Poggio +1 more
The basic structure of a neuronal circuitry possibly underlying the detection of discontinuities in the optical flow by the visual system of the houseflyMusca is proposed and detailed predictions of the model circuitry are compared with old and new behavioural experiments on Musca.
KybernetikNeural expectation: cerebellar and retinal analogs of cells fired by learnable or unlearned pattern classes
169 Citations1972Stephen Grossberg
Neural networks are introduced which can be taught by classical or instrumental conditioning to fire in response to arbitrary learned classes of patterns, and some adaptation mechanisms, and arousal mechanisms for crispening the pattern weights that can fire a given cell, are noted.
Biological CyberneticsFast adaptive formation of orthogonalizing filters and associative memory in recurrent networks of neuron-like elements
124 Citations1976Teuvo Kohonen, Erkki Oja
The system then acts as a filter, which optimally extracts the amount that is “new” in an input pattern with respect to all “old” patterns, and has features that are directly attributable to a distributed associative memory that is optimally selective.
SIAM Journal on Applied MathematicsSome Averaging and Stability Results for Random Differential Equations
70 Citations1979Stuart Geman
KybernetikA model for repetitive firing in neurons
63 Citations1974Ronald J. MacGregor, Richard Oliver
The model is shown to produce strength-duration curves for accomodation which are compatible with available data from real neurons and to be used as a module in large-scale network simulation studies.
Computers and Biomedical ResearchA computer program for simulating a network of interacting neurons I. Organization and physiological assumptions
54 Citations1976Donald H. Perkel
PABLO is the most recent version of a series of digital-computer programs designed to simulate interacting neurons, programmed in FORTRAN, that is organized to jump from event to event; the state variables are updated only when necessary as, for example, when an impulse arrives at a synapse.
Computer Simulation in Brain Science
38 Citations2008R. M. J. Cotterill
This book will not make you feel bored when reading, and computer simulation in brain science really offers what everybody wants.
IEEE Transactions on Microwave Theory and TechniquesSlot-Coupled Tee Junction in Rectangular-Guide E Plane
13 Citations1979V.M. Pandharipande, B.N. Das
International Journal of Systems ScienceAsymptotic solutions of a class of matrix differential equations arising in neutral network modelling
5 Citations1977Erkki Oja