Neural Networks - Glossary
Artificial neural networks: Computers whose architecture is modeled after the brain. They contain idealized neurons called nodes which are connected together in some network.
Neural network
An artificial neural network, more commonly known as a neural network or neural net for short, is a mathematical model for information processing based on a connectionist approach to computation.
Neural Networks
Tutorial Slides by Andrew Moore
We begin by talking about linear regression...the ancestor of neural nets. We look at how linear regression can use simple matrix operations to learn from data.
Neural Networks in 3 Minutes
A clear introduction to neural networks, concise and to the point. Covers biological neurons to mathematical models, applications and motivations as well as future research.
Neural Networks and Learning Machines:International Version
Seite senden!
Grosses Bild ...
Neural Networks
This page is under construction.
Discuss the use of internal delay lines, recurrent networks, and the Bayesian network related work by [Binder et al., 1995]. Back to Tutorial ...
Do Neural Networks Segregate Information By Frequency?
Can information be directed to different networks in the brain depending on the "transmission frequency", like the channels on a TV?
Artificial Intelligence Tutorials: Data Mining ▫ Neural Networks ▫ Fuzzy Logic ▫ Genetic Algorithms
Tutoriales de Inteligencia artificial: Redes Neuronales ▫ Lógica Fuzzy ▫ ...
I developed a grasp of most of the topics yet neural networks always seemed to elude me.
Neural Networks in Anaemia Classification
1.0 Introduction
The pioneering work of neural network in the modern era has started since 1943 by McCulloch and Pitts.
Neural networks: A requirement for intelligent systems
Throughout the years, the computational changes have brought growth to new technologies.
Neural Networks and the Computational Brain
or
Matters relating to Artificial Intelligence
by Stephen Jones ...
Neural Network Types:
Neural Network types can be classified based on following attributes:
Applications ...
Neural Networks (Brain-like computers)
As neurons in the nervous system interconnect, they form large clusters and ultimately form the brain. These large clusters inspired the development of neural networks.
Linear Neural Networks
Multiple regression
Our car example showed how we could discover an optimal linear function for predicting one variable (fuel consumption) from one other (weight).
[edit] Neural networks and neuroscience
Theoretical and computational neuroscience is the field concerned with the theoretical analysis and computational modeling of biological neural systems.
Neural networks have seen an explosion of interest over the last few years, and are being successfully applied across an extraordinary range of problem domains, in areas as diverse as finance, medicine, engineering, geology and physics.
Neural networks cannot do anything that cannot be done using traditional computing techniques, BUT they can do some things which would otherwise be very difficult.
Neural network predicted peak and trough Gentamicin concentrations.
31
Quantitative structure- pharmacokinetic relationship for drug distribution properties by using general regression neural network.
A neural network is composed of individual, locally-connected units termed neurons.
Artificial neural networks have proved useful in a variety of real-world applications that deal with complex, often incomplete data. The first of these were in visual pattern recognition and speech recognition.
Artificial Neural Networks
The branch of AI that modeled its work after the neural network of the human brain is called connectionism.
One of the two main supervised Neural Networks (the other one is the Multilayer Perceptron).
Neural Network (NN) A network of neurons that are connected through synapses or weights. In this book, the term is used almost exclusively to denote an artificial neural network and not the real thing.
Neural Networks
Interest in the brain paradigm revived in the 1980's after a new, ...
Neural Networks
Neural networks are structures that can be "trained" to recognize patterns in inputs. They are a way to implement function approximation: given y1 = f(x1), y2 = f(x2), ., yn = f(xn), construct a function f' that approximates f.
Neural Network
A system modeled after the neurons (nerve cells) in a biological nervous system. A neural network is designed as an interconnected system of processing elements, each with a limited number of inputs and outputs.
Neural Networks
Learning by Training a Network or Connectionist System
AITopics > Machine Learning > Neural Networks ...
Neural Network architecture(s)
Programmable or hardwired network(s)
On-chip learning or chip-in-the-loop training ...
Neural networks
Before going down to the statistical properties of the NN approach, in particular its link to the more usual regression approach, let's remind the reader some of the main properties of an artificial NN.
Neural Networks
Neural networks, as the term is commonly used, refers to the study of artificial systems of neuron-like processing elements.
Neural Networks
The model for the artificial neural network is made when the records from the data base are processed one at a time and the computed value of their output is then compared with the actual value.
Neural Networks - Trying to emulate the way neurons in our brain work.
Evolutionary Algorithms - Emulating the process of evolution in order to "evolve" a better solution to a given problem. The most known subfield of EA is Genetic Algorithms.
Neural Networks. An artificial intelligence technique that mimics the operation of the human brain. It consists of a network of individual neurons that are triggered according to the intensity of various inputs and their relative 'weights'.
Neural Networks
Neural networks are an approach to machine learning which developed out of attempts to model the processing that occurs within the neurons of the brain.
neural network An artificial neural network is a collection of simple artificial neurons connected by directed weighted connections. When the system is set running, the activation levels of the input units is clamped to desired values.
Neural Networks for clustering
Neural networks of various kinds can be used for clustering and prototype creation.
neural network a computational network, often for pattern recognition, composed of mathematically defined elements that are thought to approximate the working of biological neurons; often composed of a layer that receives and organizes inputs, ...
Neural networks
Main articles: neural networks and connectionism
A neural network is an interconnected group of nodes, akin to the vast network of neurons in the human brain.
neural networks
Humans, through neurons in their brains, learn how to read human writing, recognize a bad apple from a good one or identify their child from a group of children.
Neural networking theory shows that backprop networks can represent most reasonable functions as close as you like with linear output units and a single layer of non-polynomial hidden layer units, for instance see the article by Leshno, Lin, ...
Neural Networks
Artificial neural networks are information processing systems composed of a large number of highly interconnected processing elements (modelled on neurons in the brain) linked by weighted connections (mirroring synapses).
Ontology ...
Neural Networks and Neuro-computation
An Artificial Neural Network (ANN) is an information-processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information.
[14] "Neural Networks and Fuzzy Systems--A Dynamic Systems Approach to Machine Intelligence" by B. Kosko (Prentice-Hall, Englewood Cliffs, N.J., 1992).
[15] "Putting Fuzzy Logic into Focus" by Janet J. Barron (Byte, Vol. 18, Apr. 1993, pp. 11).
Artificial Neural Networks
This technique has been applied to many of the difficult problems in AI with some success.
Feed-forward neural network regression Basis function regression with adaptive basis functions. Given a measurement vector, each layer of the network makes a linear transformation and then applies a nonlinearity to each vector component.
Prediction with Neural Networks
Tutoriály v češtině (in Czech)
Předpovídání pomocí neuronové sítě ...
CNN 96 - a cellular neural network conference
Neural Net Study Group (Denmark)
Compression and encryption ...
The currently popular form of this, the connectionist neural network approach, developed more sporadically than did heuristic programming.
Even with these inhibiting factors, artificial neural networks have presented some impressive results.
However, an area of AI that shows some promise is that of neural networks, systems of circuitry that reproduce the patterns of neurons found in the brain. Current neural nets are limited, however.
This tutorial will introduce you to the heart of Pattern Recognition, unsupervised learning of Neural network called k-means clutering.
A multilayer network is a kind of neural network which consists of one or more layers of nodes between the input and the output nodes. The input nodes pass values to the hidden layer, which in turn passes to the output layer.
neural networks
Definition: Classification is a data mining (machine learning) technique used to predict group membership for data instances.
Wang tiles
Recurrent neural network (finite-precision inputs/outputs/weights, infinite-precision signals initialized to zero)
Cellular automaton, including: ...
We'll look at the fundamental technologies of Neural Networks, Artificial Intelligence, and Artificial Life. Then we'll see how these technologies are used in T2, as evidenced by the film's dialog and action.
perceptron
Model of neuron behavior. Perceptrons are used as a fundamental component of many neural networks.
[close the glossary]
prolog (programming in logic)
The most famous and widely used logic programming language.
AGM Theory for Belief Revision
AI-complete
artificial intelligence
Artificial Life
artificial neural network ...
Sole, R. V., and O. Miramontes. 1995. Information at the edge of chaos in fluid neural networks. Physica D 80:171- 180.
Neural network A form of artificial intelligence in which a computer simulates the way a human brain processes information. Paradigm an example, model, pattern or standard. Taxonomy A system of categorising information ...
 See also: Artificial intelligence, Knowledge, Percept, Classification, Data mining
  
|
RSS
