Artificial neural network, Applied Statistics

Assignment Help:

Artificial neural network

The mathematical structure modeled on the human neural network and which is designed to attack number of statistical troubles, particularly in the areas of pattern recognition, learning multivariate analysis, and memory. The essential feature of such a structure is a network of the simple processing elements (arti?cial neurons) which are coupled together (either in the hardware or the software), so that they can cooperate with each other. From the set of 'inputs' and an associated set of parameters, the arti?cial neurons create an 'output' which provides a possible solution to the problem under analysis. In number of neural networks the relationship between the input received by the neuron and its output is determined by a general linear model. The most ordinary form is the feed-forward network which is basically an extension of idea of the perception. In this type of network the vertices can be numbered such that all the connections go from a vertex to one with the higher number; the vertices are set in layers, with connections only to the higher layers. This is explained in the figure drawn below. Each neuron sums its inputs to form a entire input and applies the function fj to xj to give the desired output yj. The links have weights wij which multiply signals travelling along with them by that factor. Number of ideas and activities familiar to statisticians can be expressed in a neural-network notation, consisting regression analysis, generalized additive models, and discriminate investigation. In any practical problem which occurs the statistical equivalent of specifying architecture of the suitable network is specifying a suitable model, and training the network to do well with reference to the training set is equivalent to estimating the parameters of the model provides a set of data.




 


Related Discussions:- Artificial neural network

Explain graph theory, For each of the following scenarios, explain how grap...

For each of the following scenarios, explain how graph theory could be used to model the problem described and what a solution to the problem corresponds to in your graph model.

Find the backward induction equilibrium, A rightist incumbent (player I) an...

A rightist incumbent (player I) and a leftist challenger (player C) run for senate. Each candidate chooses among two possible political platforms: Left or Right. The rules of the g

Define sampling unit , Define sampling unit and population for selecting a ...

Define sampling unit and population for selecting a random sample in every case. a) 100 voters from a constituency b) 20 stocks of National Stock Exchange c) 50 account ho

Lorenz curve , Lorenz Curve   It is a graphic method of measur...

Lorenz Curve   It is a graphic method of measuring dispersion. This curve was devised by Dr. Max o Lorenz a famous statistician.  He used this technique for wealth it i

Recitilinear motion, velocity of a particle which moves along the s-axis is...

velocity of a particle which moves along the s-axis is given by v=2-4t+5t then find position velocity,acceleration

Standard deviation for grouped data, Grouped data  For ...

Grouped data  For grouped data, the formula applied is  σ = Where f = frequency of the variable, μ= population mea

Explain the central tendency, Explain what central tendency and variability...

Explain what central tendency and variability are. In your answer define what the mean, median, mode, variance, and standard deviation are. What is the difference between the descr

Calculate the seasonal indexes , The total number of overtime hours (in 100...

The total number of overtime hours (in 1000s) worked in a large steel mill was recorded for 16 quarters, as shown below. Year Quarter Overtime hour

Regression analysis, Of the 6,325 kindergarten students who participated in...

Of the 6,325 kindergarten students who participated in the study, almost half or 3,052 were eligible for a free lunch program. The categorical variable sesk (1 == free lunch, 2 = n

Cluster sampling, Cluster Sampling This method is also known as multi s...

Cluster Sampling This method is also known as multi stage sampling .Under this method random selection is made of the ultimate or final units from a given stratum. The sampling

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd