If a(l) gives output b(l) & a’=a(l)+m,where m is small quantity & if a’ gives ouput b(l) then?(a) network exhibits accretive behaviour(b) network exhibits interpolative behaviour(c) exhibits both accretive & interpolative behaviour(d) none of the mentionedI had been asked this question in final exam.My doubt is from Pattern Recognition topic in section Feedforward Neural Networks of Neural Networks

If a(l) gives output b(l) & a’=a(l)+m,where m is small quantity & if

1.	If a(l) gives output b(l) & a’=a(l)+m,where m is small quantity & if a’ gives ouput b(l) then?(a) network exhibits accretive behaviour(b) network exhibits interpolative behaviour(c) exhibits both accretive & interpolative behaviour(d) none of the mentionedI had been asked this question in final exam.My doubt is from Pattern Recognition topic in section Feedforward Neural Networks of Neural Networks
Answer» Correct option is (a) NETWORK EXHIBITS accretive behaviour Explanation: This FOLLOWS from basic definition of accretive behaviour in NEURAL.

Discussion

No Comment Found

Related InterviewSolutions

How hard problem can be solved?(a) by providing additional units in a feedback network(b) nothing can be done(c) by removing units in hidden layer(d) none of the mentionedThe question was asked during an internship interview.The query is from Analysis of Pattern Storage in portion Feedforward Neural Networks of Neural Networks
Why there is error in recall, when number of energy minima is more the required number of patterns to be stored?(a) due to noise(b) due to additional false maxima(c) due to additional false minima(d) none of the mentionedThis question was addressed to me in semester exam.This key question is from Analysis of Pattern Storage topic in portion Feedforward Neural Networks of Neural Networks
What happens when number of available energy minima be more than number of patterns to be stored?(a) no effect(b) pattern storage is not possible in that case(c) error in recall(d) none of the mentionedThe question was posed to me in an interview for job.My doubt is from Analysis of Pattern Storage topic in chapter Feedforward Neural Networks of Neural Networks
What happens when number of available energy minima be less than number of patterns to be stored?(a) pattern storage is not possible in that case(b) pattern storage can be easily done(c) pattern storage problem becomes hard problem for the network(d) none of the mentionedThe question was posed to me at a job interview.I need to ask this question from Analysis of Pattern Storage topic in portion Feedforward Neural Networks of Neural Networks
The number of patterns that can be stored in a given network depends on?(a) number of units(b) strength of connecting links(c) both number of units and strength of connecting links(d) none of the mentionedThe question was posed to me in an online quiz.My question is based upon Analysis of Pattern Storage in division Feedforward Neural Networks of Neural Networks
When are stable states reached in energy landscapes, that can be used to store input patterns?(a) mean of peaks and valleys(b) maxima(c) minima(d) none of the mentionedI had been asked this question during an online interview.This interesting question is from Analysis of Pattern Storage topic in chapter Feedforward Neural Networks of Neural Networks
What can be done by using non – linear output function for each processing unit in a feedback network?(a) pattern classification(b) recall(c) pattern storage(d) all of the mentionedI have been asked this question in homework.This intriguing question originated from Analysis of Pattern Storage topic in chapter Feedforward Neural Networks of Neural Networks
Does linear autoassociative network have any practical use?(a) yes(b) noThe question was asked in a job interview.The above asked question is from Analysis of Pattern Storage in chapter Feedforward Neural Networks of Neural Networks
In a linear autoassociative network, if input is noisy than output will be noisy?(a) yes(b) noThis question was addressed to me at a job interview.My question comes from Analysis of Pattern Storage topic in chapter Feedforward Neural Networks of Neural Networks
Which is a simplest pattern recognition task in a feedback network?(a) heteroassociation(b) autoassociation(c) can be hetero or autoassociation, depends on situation(d) none of the mentionedThe question was asked in an internship interview.My question is from Analysis of Pattern Storage topic in section Feedforward Neural Networks of Neural Networks

Discussion

No Comment Found

Related InterviewSolutions

Reply to Comment