Artificial neural network, Advanced Statistics

Artificial neural network: A mathematical arrangement modelled on the human neural network and designed to attack various statistical problems, particularly in the region of pattern recognition, multivariate analysis, memory and learning. The significant feature of such a structure is a network of the simple processing elements (such as arti?cial neurons) coupled together (the hardware or software), such that they cooperate. From the set of 'inputs' and an associated set of the parameters, the arti?cial neurons produce an 'output' which provides a possible solution to the problem under the investigation. In number of neural networks the relationship between the input received by the neuron and its output.

 The most is determined by the generalized linear model ordinary form is the feed-forward network which is fundamentally an extension of the idea of the perception. In this type of network the vertices can be numbered so that all the connections go from a vertex to one with the one possessing the higher number; the vertices are organised in the form of layers, with connections only to the higher layers. This is illustrated in the figure draw below each neuron sums its inputs to form a whole input

xj and applies the function fj to xj to give the result yj. The links have weights wij which multiply the signals travelling along them by the factor. Number of ideas and activities familiar to statisticians can be expressed in the neural-network notation, consisting regression analysis, generalized additive models, and the discriminant examination. In any practical problem the statistical equivalent of specifying architecture of the suitable network is specifying a appropriate model, and training the network to perform well with the reference to a training set is equivalent to estimating the parameters of the model given as the set of data.

 

Posted Date: 7/26/2012 4:32:26 AM | Location : United States







Related Discussions:- Artificial neural network, Assignment Help, Ask Question on Artificial neural network, Get Answer, Expert's Help, Artificial neural network Discussions

Write discussion on Artificial neural network
Your posts are moderated
Related Questions
I need a statistics project done. How much will it cost?

The type of longitudinal study in which the subjects receive different treatments on the various occasions. Random allocation is required to determine the order in which the treatm

Nearest-neighbour methods are the methods of discriminant analysis are based on studying the training set subjects much similar to the subject to be classified. Classification mig

Collective risk models : The models applied to insurance portfolios which do not create direct reference to the risk characteristics of individual members of the portfolio when des

Suppose we estimate the following model: Passengersi = 1 + 2Populationi + ui a) Generate a scatter plot with passengers on the vertical axis and population on the horizonta

Response feature analysis is the approach to the analysis of longitudinal data including the calculation of the suitable summary measures from the set of repeated measures on each

The Null Hypothesis - H0:  There is autocorrelation The Alternative Hypothesis - H1: There is no autocorrelation Rejection Criteria: Reject H0 (n-s)R 2 > = (1515 - 4) x (0.

when there is tie in sequencing then what we do

Quittingill effect is a  problem which occurs most frequently in studies of the smoker cessation where smokers frequently quit smoking following the onset of the disease symptoms

Kaiser's rule is the  rule frequently used in the principal components analysis for selecting the suitable the number of components. When the components are derived from correlati