Already have an account? Get multiple benefits of using own account!
Login in your account..!
Remember me
Don't have an account? Create your account in less than a minutes,
Forgot password? how can I recover my password now!
Enter right registered email to receive password!
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.
Analysis of variance allows us to test whether the differences among more than two sample means are significant or not. This technique overcomes the drawback of the method used in
Multivariate analysis involves a set of techniques to analyse data sets on more than one variable. Many of these techniques are modern and often involve quite sophisticated use of
data:59,59,65,70,74 176,179,195,210,200
#question what is the statistical process to reduce hardness of water
Lifts usually have signs indicating their maximum capacity. Consider a sign in a lift that reads "maximum capacity 1400kg or 20 persons". Suppose that the weights of lift-users are
what is non linear modl
Mathematical Properties The sum of deviations of the items from the arithmetic mean (taking signs into account) is always zero, i.e. = 0. The sum of
Analytical Approach We will illustrate this through an example. Example 1 A firm sells a product in a market with a few competitors. The average price charged by the
how to analyzePractice-Based Evidence Back to the Future
Scenario : Mrs dick's year 1s and 2s carried out a level-one science investigation to explain the changes in a particular plant over a period of time. As part of the investigation
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!
whatsapp: +91-977-207-8620
Phone: +91-977-207-8620
Email: [email protected]
All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd