Q#01: Multiple Choice Question.
01: Feed-forward networks have ______________ connections from input to output layers.
(A) Two-way
(B) One-Way
(C)None
02: LVQ is a powerful method for classifying patterns that are not __________separable.
(A) Linearly
(B) Non Linearly (C)None
03: _________________ recognize and group similar input vectors and using these groups the network
automatically sorts the inputs into categories.
(A) Self-organizing maps (B) Recurrent networks (C) Radial basis networks (D) Competitive layers
04: Early stopping is a technique that uses ______ different data sets
(A) 4
(B) 3
(C) 2
(D) None
05: Activation function is a ____________function which takes the argument u and produces the output y
(A) Linear
(B) Non-Linear
(C) Both A & B
(D)None
06: Most commonly used activation function in feed forward neural networks is:
(A) Log-sigmoid transfer function (B) Tangent hyperbolic function
(C) Positive linear function
(D) Symmetrical hardlimiter
07: x=radbas(u) command used to generate response of ______________ Function
(A) Triangular basis (B) Max Transfer (C) Positive linear (D) Gaussian Function
08: In MATLAB Neural Network toolbox has the function satlin to generate_________function.
(A) Symmetric saturating linear transfer (B) Saturating linear transfer
(C) Soft Max Transfer
(D) Log-sigmoid transfer
09: In MATLAB trainbfg function is used to run__________________ back propagation training
algorithm.
(A) Quasi-Newton (B) Baysian regulation (C) Levenberg-Marquardt (D) RPROP
10: In MATLAB to train MLP Network using Gradient Descent back-propagation with momentum
which matlab function is used:
(A) trainlm
(B) traingdm (C) traingda (D) traingd
Q#02 Fill in the blanks:
1: A Perceptron can be created with the function__________ (Ans: newp)
2: __________ command is used to bring up the neural network toolbox block set (Ans: neural)
3: Training and learning functions are mathematical procedures used to automatically adjust the
network’s _________ and _________
(Ans: weights and Biases)
4: LVQ stand for _______________________________________ (Ans: Learning vector quantization)
5: Recurrent networks use feedback to recognize________ and __________ patterns.
(Ans:Spatial,temporal)
6: y=satlins(u) command is used to generate the response of ____________________________________
function (Ans: Symmetric saturating linear transfer)
7: trainlm MTLAB function is used to train a MLP network using _________________________
Back-propagation algorithm (Ans: Levenberg-Marquardt)
8: Radial Basis Function Networks can be designed with the function__________
(Ans:newrbe.m)
9: The drawback of newrbe is that it produces a network with as many _________ neurons as
there are input vectors. (Ans: Hidden)
10: The weight vector of the associator is computed as_________________ (Ans: W=dX)
Q#03: True and False
1: Pseudoinverse Rule is used with the Hebbian learning when the patterns are not orthogonal (T)
2: In Neural Network toolbox of MATLAB there are four distinct ways to calculate
distances from a particular neurons to its neighbors. (T)
3: The hextop function creates a dissimilar set of neurons but they are in a hexadecimal
pattern. (F)
4: The dist function calculates the Euclidean distance from a home neuron to any other
neuron. (T)
5: newsop function is used to create self organizing map neural network. (F)
6: The Elman network commonly is a three layer network with feedback from the first layer output to the
first layer input. (F)
7: Tangent hyperbolic function is a very famous activation function which is widely used in multilayer
perceptron networks. (T)
8: Self-organizing maps learn to classify input vectors according to dissimilarity. (F)
9: Radial basis networks provide an alternative fast method for designing linear feed-forward
Networks (F)
10: Soft Max Transfer Function usually used with committee machines (T)