Cognitive Techniques MCQs

Welcome to our comprehensive collection of Multiple Choice Questions (MCQs) on Cognitive Techniques, a fundamental topic in the field of Cognitive Radio. Whether you're preparing for competitive exams, honing your problem-solving skills, or simply looking to enhance your abilities in this field, our Cognitive Techniques MCQs are designed to help you grasp the core concepts and excel in solving problems.

In this section, you'll find a wide range of Cognitive Techniques mcq questions that explore various aspects of Cognitive Techniques problems. Each MCQ is crafted to challenge your understanding of Cognitive Techniques principles, enabling you to refine your problem-solving techniques. Whether you're a student aiming to ace Cognitive Radio tests, a job seeker preparing for interviews, or someone simply interested in sharpening their skills, our Cognitive Techniques MCQs are your pathway to success in mastering this essential Cognitive Radio topic.

Note: Each of the following question comes with multiple answer choices. Select the most appropriate option and test your understanding of Cognitive Techniques. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

So, are you ready to put your Cognitive Techniques knowledge to the test? Let's get started with our carefully curated MCQs!

Cognitive Techniques MCQs | Page 4 of 7

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Q31.
In ____ approach, the ____ members are saved after each process or test.

a.

multiple single objective Pareto sampling, dominant

b.

repeated single objective, dominant

c.

multiple single objective Pareto sampling, recessive

d.

repeated single objective, recessive

Discuss
Answer: (b).repeated single objective, dominant Explanation:Repeated single objective involves operating on the same set of members multiple times using single, different objective each time. The dominant members from each test are recorded for final analysis of Pareto set.
Q32.
Which among the following is a monitor parameter for power consumption?

a.

Throughput

b.

Modulation type

c.

SINR

d.

Interference

Discuss
Answer: (b).Modulation type Explanation:Modulation type and symbol rate are monitor parameters for power consumption. Each waveform utilizes certain amount of power based on the processes used at the transmitter and the receiver for proper operation.
Q33.
Effective isotropic radiated power is given by ____

a.

product of input power to the antenna and gain of the antenna

b.

sum of input power to the antenna and gain of the antenna

c.

difference of input power to the antenna and gain of the antenna

d.

ratio of product of input power to the antenna and gain of the antenna

Discuss
Answer: (a).product of input power to the antenna and gain of the antenna Explanation:Effective isotropic radiated power measures the combination of the power emitted by the transmitter and the capability of the antenna to wield that power in a particular direction. It is given by the product of product of input power to the antenna and gain of the antenna.
Q34.
Non coherent receivers require more power than coherent receivers.

a.

True

b.

False

c.

May be True or False

d.

Can't say

Discuss
Answer: (b).False Explanation:Non coherent receivers require less power than coherent receivers. This is because coherent receivers involve frequency and phase correction in their reception process. Since additional processes are carried out, more power is consumed. Similarly, higher symbol rate requires more processing speed, and consequently more power.
Q35.
Bayesian networks uses ____

a.

directed cyclic graph

b.

directed acyclic graph

c.

undirected cyclic graph

d.

undirected acyclic graph

Discuss
Answer: (b).directed acyclic graph Explanation:A Bayesian network is a probabilistic graphical model where a group of variables and their conditional dependencies are represented using directed acyclic graph. Directed acyclic graph is a directed graph and does not have directed cycles.
Q36.
Bayesian network can match ____ with ____

a.

an incident, probable cause

b.

a definite cause, probable consequence

c.

a incident, similar incident

d.

a cause, similar cause

Discuss
Answer: (a).an incident, probable cause Explanation:A Bayesian network examines an event and determines the probability of a known cause activating that event. For example, a Bayesian network can be used to examine the symptoms of a person and match it with a probable disease.
Q37.
Bayesian network that models speech signals are called ____

a.

signal Bayesian network

b.

sequential Bayesian network

c.

series Bayesian network

d.

dynamic Bayesian network

Discuss
Answer: (d).dynamic Bayesian network Explanation:Bayesian network that replicate sequence of variables such as speech signals are called as dynamic Bayesian network. It has been applied in robotics, bioinformatics, and digital forensics. It is a generalisation of Hidden Markov Model and Kalman filter.
Q38.
Which among the following is not represented by node in Bayesian network?

a.

Latent variables

b.

Observable variables

c.

Hypotheses

d.

Conditions

Discuss
Answer: (d).Conditions Explanation:The nodes in a Bayesian network represent latent variables, observable variables, unknown parameters, and hypotheses. The conditions are represented using edges. The nodes which are not connected by edges are conditionally independent.
Q39.
The process of computing the ____ of variables when provided with supporting conditions is called ____

a.

prior distribution, probabilistic inference

b.

posterior distribution, probabilistic inference

c.

prior distribution, probabilistic query

d.

posterior distribution, probabilistic query

Discuss
Answer: (b).posterior distribution, probabilistic inference Explanation:The process of computing the posterior distribution of variables when provided with supporting conditions is called probabilistic inference. It is probability of one or more variable taking a particular set of values.
Q40.
Expert system is a computer system capable of resolving _____ problems.

a.

recognition

b.

decision making

c.

transfer

d.

storage

Discuss
Answer: (b).decision making Explanation:An expert system is a computer system that performs decision making based on facts and heuristic approach. It can solve difficult issues occurring within a specific domain.
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