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WorksheetsFinal Theory Information(2024)
Total questions: 152
Worksheet time: 1hrs 16mins
______ indicate(s) an error in a received combination.
Parity bits
Error syndrome
Data bits
None of the given
... is a measure of uncertainty
Entropy
Encoding
Information
Redundancy
A code has two allowable combinations 101 and 010. What is the allowable combination for the error combination 001?
010
100
101
None
A code has two allowable combinations 101 and 010. What is the allowable combination for the error combination 100?
101
010
100
None
A code has two allowable combinations 101 and 010. What is the allowable combination for the error combination 000?
100
010
101
None
A code has two allowable combinations 101 and 010. What is the allowable combination for the error combination 111?
111
101
010
None
A code has two allowable combinations 101 and 010. What is the allowable combination for the error combination 011?
111
101
010
None
A code has two allowable combinations 101 and 010. What is the allowable combination for the error combination 110?
110
010
101
None
A codeword of the Hamming code consists of ________ and ________ bits.
data; parity
allowable; not allowable
with errors; without errors
none of the given
A Huffman code is a = 1, b = 000, c = 001, d = 01. Probabilities are p(a) = 0.4, p(b) = 0.1, p(c) = 0.2, p(d) = 0.3. The average length of codewords q is
2.1 bit
1.9 bit
2.0 bit
8.0 bit
A redundancy of a code S = ...
1 - Iavr/Imax
Iavr/Imax
1 + Iavr/Imax
Imax/Iavr
An average length of codewords qavr = ...
∑ (pi/qi)
∑pi / n
∑ (pi*qi)
∑qi / n
An efficiency of a code E = ...
Imax/Iavr
Iavr/100
Iavr/Imax
Imax - Iavr
ASCII code is a
Variable length code
Fixed length code
Error-correction code
None of the given
By the Bayes' rule for conditional entropy H(Y|X) = ...
[P(A)] /P(B)
H(X|Y) - H(X) + H(Y)
H(X|Y) - H(X)
H(X|Y)+ H(Y)
By the Bayes' theorem ...
P(A|B) = [P(B|A)][P(A)] /P(B)
P(B|A) = P(A and B)/P(A)
P(B|A) = P(A and B)*P(A)
P(A|B) = [P(B|A)][P(A)] * P(B)
By the Chain rule H(X,Y) = H(Y|X) + ...
H(X)
H(Y)
H(Y|X)
H(X|Y)
By the Hartley's formula the amount of information I = ...
I = m*n
I = log (m/n)
I = n*log m
I = log (m*n)
By the Hartley's formula the entropy H = ...
H = - ∑(pi*log pi)
H = - ∑ (log pi)
H = log m
H = - ∑ (pi/log pi)
By the property of joint entropy H(X,Y) <= ...
H(X)
H(Y)
H(X) + H(Y)
None of the given
By the property of joint entropy H(X,Y) ...
H(X,Y) >= H(X) and H(X,Y) <= H(Y)
H(X,Y) <= H(X) and H(X,Y) >= H(Y)
H(X,Y) >= H(X) and H(X,Y) >= H(Y)
H(X,Y) >= H(X) + H(Y)
By the Shannon's formula the amount of information I = ...
H = - n *∑(pi*log pi)
H = - n * ∑ (log pi)
H = - n * ∑ pi
H = - n * ∑ (pi/log pi)
By the Shannon's formula the entropy H = ...
H = - ∑(pi*log pi)
H = - ∑ (log pi)
H = - ∑ pi
H = - ∑ (pi/log pi)
Calculate the code rate for Hamming (15,11) code
1
0,733
0,571
0,839
Calculate the code rate for Hamming (31,26) code
1
0,733
0,839
0,571
Calculate the code rate for Hamming (7,4) code
1
0,571
0,733
0,839
70. Encode a string "1100" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
A)1100110
B) 1100000
C) 1100010
D) 1100011
71. Encode a string "1101" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
A) 1101101
B) 1101011
C) 1101001
D) 1101000
72. Encode a string "1110" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
A) 1110000
B) 1110101
C) 1110100
D) 1110110
73. Encode a string "1111" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
A) 1111110
B) 1111011
C) 1111111
D) 1111101
74. The length of the message is 16 symbols and the message’salphabet consists of 4 symbols. Find the amount of informationin this message.
A) 16
B) 80
C) 64
D) 32
75. The efficiency of the language is 0,5 and its I average isequal to 1 bit. Calculate the number of letters in this language’salphabet?
A) 64
B) 32
C) 4
D) 16
76. Elements of alphabets X and Y are statistically related. It isknown that H(X)=4 bits and H(Y)=10 bits. What are a range ofvariation for a conditional entropy H(Y|X) when H(X|Y) changes from its min to max?
A) (from 7 to 11)
B) (from 4 to 12)
C) (from 6 to 10)
D) (from 6 to 11)
77. For Hamming distance dmin and r errors in the receivedword, the condition to be able to detect the errors is
A) dmin>= r+1
B) dmin>= 2r+1
C) dmin>= 2r+2
D) dmin>= r+2
78. For Hamming distance dmin and s errors in the receivedword, the condition to be able to correct the errors is
A) dmin>= s+1
B) dmin>= 2s+1
C) dmin>= 2s+2
D) dmin>= s+2
79. Hamming (7,4) code can correct ___ error(s)
A) 2
B) 3
C) 1
D) 0
80. Hamming distance can easily be found with ...
A) XNOR operation
B) XOR operation
C) OR operation
D) AND operation
81. How does a noise affect the data?
A) change only the 0 to 1
B) change only the 1 to 0
C) change the 0 to 1 and the 1 to 0
D) None of the above
82. How many data bits are in the (15, 11) Hamming code?
A) 11
B) 4
C) 15
D) 5
83. How many data bits are in the (31, 26) Hamming code?
A) 26
B) 31
C) 5
D) 4
84. How many data bits are in the (7, 4) Hamming code?
A) 4
B) 3
C) 7
D) 10
85. How many parity bits are in the (15, 11) Hamming code?
A) 4
B) 15
C) 11
D) 5
86. How many parity bits are in the (31, 26) Hamming code?
A) 26
B) 31
C) 5
D) 4
87. How many parity bits are in the (7, 4) Hamming code?
A) 3
B) 4
C) 7
D) 11
88. A Huffman code is a = 0, b = 10, c = 110, d = 1110, e = 1111. Probabilities are p(a) = 0.50, p(b) = 0.30, p(c) = 0.15, p(d) = 0.03, p(e) = 0.02. The average length of a code words is
A) 1.75 bit
B) 2.0 bit
C) 1.3 bit
D) 1.7 bit
89. Which letter will get the shortest codeword after Huffmancoding of the word «bbaacccabaac»?
A) a
B) b
C) c
D) none
90. An alphabet consist of the letters a, b, c, d, e and f. The probability of occurrence is p(a) = 0.06, p(b) = 0.15, p(c) = 0.4 and p(d) = 0.18, p(e)=0.17, p(f)=0.04. The Huffman code is
A) c=1,d=000,e=001,b=010,a=0110,f=0111
B) c=0,d=111,e=110,b=101,a=1001,f=1000
C) c=1,d=01,e=001,b=0000,a=00010,f=00011
D) c=1,d=01,e=001,b=000,a=0010,f=00011
E) c=0,d=101,e=110,b=101,a=1000,f=1001
91. If k - number of bits before Hamming encoding and n - number of bits after Hamming encoding then
A) k > n
B) k < n
C) k = n
D) k = 1/2 n
Calculate the efficiency of the language if it has 32 letters and its I average is 1 bit.
0.8
0.2
5
11
28. Calculate the redundancy of the language if it has 32 letters and its I average is 1 bit.
0.8
0.2
5
1
29. Choose an example of block code
Shannon-Fano code
Huffman code
Hamming code
None of the given
30. Choose conditions of an optimal coding (p – probability, l – length of a code word)
A) pi < pj and li<=lj
B) pi > pj and li<=lj
C) pi > pj and li>=lj
D) none of the given
31. Choose the formula to create the Hamming code
A) (n, k) = (2r - 1, 2r - 1 - r)
B) (n, k) = (2r, 2r - 1 - r)
C) (n, k) = (2r - 1, 2r - r)
D) (n, k) = (2r - 1, 2r - 1 + r)
Choose the formula to determine the number N of possible messages with length n if the message source alphabet consists of m characters, each of which can be an element of the message.
A) N = mn
N = m^n
C) N = m*n
D) N = log m
33. Code has dmin = 1. How many errors can be corrected by this code?
2
3
0
1
34. Code has dmin = 1. How many errors can be detected by this code?
2
3
0
1
35. Code has dmin = 10. How many errors can be detected by this code?
4
8
9
10
37. Code has dmin = 11. How many errors can be detected by this code?
A) 5
B) 9
C) 10
D) 11
36. Code has dmin = 11. How many errors can be corrected by this code?
A) 11
B) 7
C) 5
D) 10
39. Code has dmin = 2. How many errors can be corrected by this code?
2
3
1
0
38. Code has dmin = 12. How many errors can be detected by this code?
11
5
10
12
40. Code has dmin = 2. How many errors can be detected by this code?
2
3
1
0
41. Code has dmin = 3. How many errors can be corrected by this code?
2
3
1
4
43. Code has dmin = 4. How many errors can be detected by this code?
3
5
1
4
42. Code has dmin = 3. How many errors can be detected by this code?
1
3
2
4
44. Code has dmin = 5. How many errors can be corrected by this code?
5
3
2
4
45. Code has dmin = 5. How many errors can be detected by this code?
6
2
4
5
46. Code has dmin = 6. How many errors can be detected by this code?
6
2
5
4
47. Code has dmin = 7. How many errors can be corrected by this code?
5
6
3
4
48. Code has dmin = 7. How many errors can be detected by this code?
7
3
6
5
114.The first code combination is 0000 and the Hamming distance of this code equals 4. Choose the second combination. 1
1111
1011
0011
0000
115. The Hamming code is a method of _______.
B) Optimal coding
A) Error control coding
C) None of the above
116. The Hamming distance between "client" and "server" is
0
1
6
impossible to detect
117. The Hamming distance between "make" and "made" is
4
3
1
D) impossible to detect
118. The Hamming distance between "push" and "pull" is
2
4
0
D) impossible to detect
119. The Hamming distance between "starting" and "finishing" is
4
3
impossible to detect
5
120. The Hamming distance between 001111 and 010011 is
1
2
3
4
121. The Hamming distance between 010111 and 010011 is
2
3
4
1
122. The Hamming distance between 011111 and 010011 is
1
2
3
4
123. The Hamming distance between 101001 and 010011 is
4
2
1
3
124. The length of the message is 16 symbols and the message's alphabet consists of 32 symbols. Find the amount of information in this message.
80
16
64
32
125. The length of the message is 6 symbols and the message's alphabet consists of 32 symbols. Find the amount of information in this message.
6
30
32
24
126. The redundancy of the language is 0,75 and its I average is 1 bit. Calculate the number of letters in this language's alphabet?
16
32
8
64
127. The string was encoded with Hamming (7,4) code using the structure (i1, i2, i3, i4, r1, r2, r3). After a channel the error syndrome is 000. Specify the position of the error.
i1
r1
no error
r3
128. The string was encoded with Hamming (7,4) code using the structure (i1, i2, i3, i4, r1, r2, r3). After a channel the error syndrome is 001. Specify the position of the error.
r3
r1
i1
no error
129. The string was encoded with Hamming (7,4) code using the structure (i1, i2, i3, i4, r1, r2, r3). After a channel the error syndrome is 010. Specify the position of the error.
r2
r3
i2
r1
130. The string was encoded with Hamming (7,4) code using the structure (i1, i2, i3, i4, r1, r2, r3). After a channel the error syndrome is 011. Specify the position of the error.
i4
i1
r4
r1
131. The string was encoded with Hamming (7,4) code using the structure (i1, i2, i3, i4, r1, r2, r3). After a channel the error syndrome is 100. Specify the position of the error.
i1
r1
r3
r2
132. The string was encoded with Hamming (7,4) code using the structure (i1, i2, i3, i4, r1, r2, r3). After a channel the error syndrome is 101. Specify the position of the error.
no error
r1
i1
i2
133. The string was encoded with Hamming (7,4) code using the structure (i1, i2, i3, i4, r1, r2, r3). After a channel the error syndrome is 110. Specify the position of the error.
i3
r3
i4
i1
134. The string was encoded with Hamming (7,4) code using the structure (i1, i2, i3, i4, r1, r2, r3). After a channel the error syndrome is 111. Specify the position of the error.
A) i4
i4
r2
i2
no error
135. This is the method for data processing for reducing errors during transmission via channel with noise.
Error Correction code
Uniform code
Non-uniform code
Optimal code
49. Code has dmin = 8. How many errors can be detected bythis code?
8
6
7
3
50. Code has dmin = 9. How many errors can be corrected bythis code?
5
7
4
8
51. Code has dmin = 9. How many errors can be detected bythis code?7
7
9
8
4
52. Code rate R (k information bits and n total bits) is defined as
k = n/R
R = k * n
R = k/n
n = R * k
53. Conditional entropy H(Y|X) lies between
- H(Y) and 0
0 and H(Y)
- H(Y) and H(Y)
0 and 1
54. Convert the message into a signal suitable for transmissionover the channel of communication, referred to as …
Encoding
Decoding
Entropy
Redundancy
55.Determine the Hamming distance for code that can detect 3 errors and correct 2 errors.
6
5
7
9
56.Determine the Hamming distance for code that can detect 3 errors and correct 1 errors.
5
4
6
8
57. Determine the Hamming distance for code that can detect 5 errors and correct 3 errors.
9
8
10
14
58. Encode a string "0000" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
0000001
0000111
0000000
0000101
59. Encode a string "0001" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
0001010
0001001
0001011
0001111
60. Encode a string "0010" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
0010010
0010111
0010110
0010100
61. Encode a string "0011" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
0011100
0011001
0011101
0011111
62. Encode a string "0100" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
0100011
0100110
0100111
0100101
63. Encode a string "0101" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
0101101
0101000
0101100
0101110
64. Encode a string "0110" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
0110101
0110011
0110001
0110000
65. Encode a string "0111" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
0111110
0111000
0111010
0111011
66. Encode a string "1000" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
1000111
1000100
1000101
1000001
67. Encode a string "1001" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
1001111
1001010
1001110
1001100
68. Encode a string "1010" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
1010111
1010001
1010011
1010010
69. Encode a string "1011" with Hamming (7,4) code using thefollowing structure (i1, i2, i3, i4, r1, r2, r3)
1011100
1011010
1011000
1011001
In digital communication system, smaller the code rate, ... are the redundant bits.
less
equal
more
unpredictable
Main idea of error control codes is
To add some redundancy
To delete some redundancy
To double all bits
None of the given
Noise affects ...
information source
receiver
channel
transmitter
Shannon-Fano and Huffman codes are an encoding algorithms used for
lossy data compression
lossless data compression
error correction
error detection
Specify the case when entropy is maximum
p1=0,5 and p2=0,5
p1=1 and p2=0
p1=0 and p2=1
p1=0,9 and p2=0,1
Specify the error position in the string "0001110", if the initial string was encoded with Hamming (7,4) code using the following structure (i1, i2, i3, i4, r1, r2, r3)
i4
i1
i2
r2
98. Specify the error position in the string "1000110", if the initial string was encoded with Hamming (7,4) code using the following structure (i1, i2, i3, i4, r1, r2, r3)
i1
i4
i2
i3
99. Specify the error position in the string "1001010", if the initial string was encoded with Hamming (7,4) code using the following structure (i1, i2, i3, i4, r1, r2, r3)
r2
r1
r3
i3
100. Specify the error position in the string "1001100", if the initial string was encoded with Hamming (7,4) code using the following structure (i1, i2, i3, i4, r1, r2, r3)
r3
r2
r1
no error
101. Specify the error position in the string "1001110", if the initial string was encoded with Hamming (7,4) code using the following structure (i1, i2, i3, i4, r1, r2, r3)
r1
no error
r2
i4
102. Specify the error position in the string "1001111", if the initial string was encoded with Hamming (7,4) code using the following structure (i1, i2, i3, i4, r1, r2, r3)
r1
r3
r2
i4
103. Specify the error position in the string "1011110", if the initial string was encoded with Hamming (7,4) code using the following structure (i1, i2, i3, i4, r1, r2, r3)
i1
i3
i2
i4
104. Specify the error position in the string "1101110", if the initial string was encoded with Hamming (7,4) code using the following structure (i1, i2, i3, i4, r1, r2, r3)
i1
i2
i3
i4
Specify the formula to find the amount of information if events have different probabilities.
Hartley's formula
Shannon's formula
Fano's formula
Bayes' formula
106. Specify the formula to find the amount of information if events have the same probabilities.
Shannon's formula
Hartley's formula
Fano's formula
Bayes' formula
107. Specify the right formula if dmin is Hamming distance, s - number of correctable errors and r - number of detecteable errors.
dmin>= s+r+1
dmin>= 2s+r+1
dmin>= s+2r+1
dmin>= s+r+2
108. Suppose the letters a, b, c, d, e, f have probabilities 1/2, 1/4, 1/8, 1/16, 1/32, 1/32 respectively. Which of the following is the Huffman code for the letter a, b, c, d, e, f?
11, 10, 011, 010, 001, 000
0, 10, 110, 1110, 11110, 11111
11, 10, 01, 001, 0001, 0000
110, 100, 010, 000, 001, 111
109. Suppose the letters a, b, c, d, e, f have probabilities 1/2, 1/4, 1/8, 1/16, 1/32, 1/32 respectively. What is the average length q of the Huffman code?
3,0
1,9
2,7
4,3
110. The amount of information in the message is 120 bits. Calculate the length of this message, which is written by characters of 16-character alphabet.
30
480
120
130
111. The amount of information in the message is 60 bits. Calculate the length of this message, which is written by characters of 4-character alphabet.
30
60
15
510
112. The basic idea behind Shannon-Fano coding is to
compress data by using more bits to encode more frequently occuring characters
compress data by using fewer bits to encode more frequently occuring characters
compress data by using fewer bits to encode fewer frequently occuring characters
expand data by using fewer bits to encode more frequently occuring characters
113. The efficiency of the language is 0,25 and its I average is 1 bit. Calculate the number of letters in this language's alphabet?
32
16
8
64
We can divide coding schemes into two broad categories: ________ and ______coding
A) block; linear
B) linear; nonlinear
C) block; convolution
D) none of the given
What is the first step of Shannon-Fano algorithm?
A) Characters of the original alphabet are setted in descending order of probability
B) Letters divided to the two subsets so that the overall probability of these subsets were about equal.
C) For all characters (letters) of the top subset assign a code element 1, and for characters of the lower subset the 0 code.
D) For all characters (letters) of the top subset assign a code element 0, and for characters of the lower subset the 1 code.
What is the Hamming distance between two strings of equal length?
A) the number of positions at which the corresponding symbols are different
B) the number of positions at which the corresponding symbols are equal
C) the number of identical symbols in the first string
D) the number of identical symbols in the second string
. What is the meaning of number “2” in the formula I = n*log2m?
A) Binary number system
B) Message length equals to 2
C) It hasn’t any meaning
D) Information is measured in nits
What is the sample space of one dice roll?
A) {1,2,3,4,5,6}
B) {1,3,5}
C) {2,4,6}
D) {1,2,3,4,5,6,7,8,9,10,11,12}
When the base of the logarithm is 10, then the unit of measure of information is
A) bytes
B) dits
C) nits
D) bits
When the base of the logarithm is 2, then the unit of measure of information is
A) bytes
B) bits
C) nits
D) dits
When the base of the logarithm is e, then the unit of measure of information is
A) bytes
B) nits
C) dits
D) bits
Which letter will get the shortest codeword after Huffman coding of the word "abracadabra"?
A) c
B) r
C) d
D) a
Which of the following codes can be the Huffman code for the letters a,b,c,d,e?
A) 10,011,11,001,010
B) 0,10,110,1110,1111
C) 10,01,0001,100,1010
D) 100,110,001,000,010
Which of the following codes has the highest code rate?
A) code rate is constant for all of the Hamming codes
B) Hamming (31,26)
C) Hamming (15,11)
D) Hamming (7,4)
Which of the following codes has the highest redundancy?
A) redundancy is constant for all of the Hamming codes
B) Hamming (7,4)
C) Hamming (15,11)
D) Hamming (31,26)
Which of the following codes is prefix?
A) 0, 111, 11
B) 0, 111, 10
C) 0, 101, 10
D) 00, 10, 101
Which of the following codes is prefix?
A) 0, 01, 11
B) 0, 10, 11
C) 0, 10, 1
D) 0, 01, 001
Which of the following codes is uniform?
A) ASCII
B) Shannon-Fano
C) Huffman
D) None of the given
Which of the following codes is uniform?
A) 10,011,11,001,010
B) 0,10,110,1110,1111
C) 10,01,0001,100,1010
D) 100,110,001,000,010
Which of the following symbols will get the shortest codeword after Shannon-Fano coding if probabilities are p(a) = 0.05, p(b) = 0.6, p(c) = 0.2 and p(d) = 0.15?
A) c
B) a
C) d
D) b
