Which of the following equation represent perceptron learning law?a) ∆wij= µ(si) ajb) ∆wij= µ(bi – si) ajc) ∆wij= µ(bi – si) aj Á(xi),wher Á(xi) is derivative of xid) ∆wij= µ(bi – (wi

∆wij= µ(bi – si) aj Á(xi),wher Á(xi) is derivative of xi

State which of the following statements hold foe perceptron learning law?

it is supervised type of learning law

it requires desired output for each input

Hebb’s law can be represented by equation?a) ∆wij= µf(wi

∆wij= µ(si) aj, where (si) is output signal of ith input

State whether Hebb’s law is supervised learning or of unsupervised type?

either supervised or unsupervised

can be both supervised & unsupervised

If the change in weight vector is represented by ∆wij, what does it mean?

describes the change in weight vector for jth processing unit, taking input vector ith into account

describes the change in weight vector for ith processing unit, taking input vector jth into account

describes the change in weight vector for jth processing unit, taking input vector ith into account

describes the change in weight vector for jth & ith processing unit.

Explore topic-wise MCQs in Neural Networks.

This section includes 10 Mcqs, each offering curated multiple-choice questions to sharpen your Neural Networks knowledge and support exam preparation. Choose a topic below to get started.

1.	Which of the following equation represent perceptron learning law?a) ∆wij= µ(si) ajb) ∆wij= µ(bi – si) ajc) ∆wij= µ(bi – si) aj Á(xi),wher Á(xi) is derivative of xid) ∆wij= µ(bi – (wi
A.	∆wij= µ(si) aj
B.	∆wij= µ(bi – si) aj
C.	∆wij= µ(bi – si) aj Á(xi),wher Á(xi) is derivative of xi
D.	∆wij= µ(bi – (wi a)) aj
Answer» C. ∆wij= µ(bi – si) aj Á(xi),wher Á(xi) is derivative of xi

Discussion

2.	What’s the other name of widrow & hoff learning law?
A.	Hebb
B.	LMS
C.	MMS
D.	None of the mentioned
Answer» C. MMS

Discussion

3.	widrow & hoff learning law is special case of?
A.	hebb learning law
B.	perceptron learning law
C.	delta learning law
D.	none of the mentioned
Answer» D. none of the mentioned

Discussion

4.	Delta learning is of unsupervised type?
A.	yes
B.	no
Answer» C.

Discussion

5.	State which of the following statements hold foe perceptron learning law?
A.	it is supervised type of learning law
B.	it requires desired output for each input
C.	∆wij= µ(bi – si) aj
D.	all of the mentioned
Answer» E.

Discussion

6.	Hebb’s law can be represented by equation?a) ∆wij= µf(wi
A.	∆wij= µf(wi a)aj
B.	∆wij= µ(si) aj, where (si) is output signal of ith input
C.	both way
D.	none of the mentioned
Answer» D. none of the mentioned

Discussion

7.	State whether Hebb’s law is supervised learning or of unsupervised type?
A.	supervised
B.	unsupervised
C.	either supervised or unsupervised
D.	can be both supervised & unsupervised
Answer» C. either supervised or unsupervised

Discussion

8.	What is learning signal in this equation ∆wij= µf(wi a)aj?a) µb) wi ac) ajd) f(wi
A.	µ
B.	wi a
C.	aj
D.	f(wi a)
Answer» E.

Discussion

9.	If the change in weight vector is represented by ∆wij, what does it mean?
A.	describes the change in weight vector for ith processing unit, taking input vector jth into account
B.	describes the change in weight vector for jth processing unit, taking input vector ith into account
C.	describes the change in weight vector for jth & ith processing unit.
D.	none of the mentioned
Answer» B. describes the change in weight vector for jth processing unit, taking input vector ith into account

Discussion

10.	On what parameters can change in weight vector depend?
A.	learning parameters
B.	input vector
C.	learning signal
D.	all of the mentioned
Answer» E.

Discussion

Explore topic-wise MCQs in Neural Networks.

Which of the following equation represent perceptron learning law?a) ∆wij= µ(si) ajb) ∆wij= µ(bi – si) ajc) ∆wij= µ(bi – si) aj Á(xi),wher Á(xi) is derivative of xid) ∆wij= µ(bi – (wi

What’s the other name of widrow & hoff learning law?

widrow & hoff learning law is special case of?

Delta learning is of unsupervised type?

State which of the following statements hold foe perceptron learning law?

Hebb’s law can be represented by equation?a) ∆wij= µf(wi

State whether Hebb’s law is supervised learning or of unsupervised type?

What is learning signal in this equation ∆wij= µf(wi a)aj?a) µb) wi ac) ajd) f(wi

If the change in weight vector is represented by ∆wij, what does it mean?

On what parameters can change in weight vector depend?