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WorksheetsВопросы по теории кодирования
Total questions: 58
Worksheet time: 32mins
... является мерой неопределенности
Кодирование
Энтропия
Информация
Избыточность
Избыточность кода S = ...
1 - lavr/Imax
lavr/Imax
1 + lavr/Imax
Imax/lavr
Средняя длина кодовых слов qavr = ...
∑ (pi*qi)
∑ (pi/qi)
∑pi / n
∑qi / n
6. Эффективность кода E = ...
lavr/Imax
Imax/lavr
lavr*Imax
Imax-lavr
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) = ...
H(X|Y) - H(X) + H(Y)
[P(A)] /P(B)
H(X|Y) - H(X)
H(X|Y)+ H(Y)
By the Bayes' theorem ...
P(B|A) = P(A and B)/P(A)
P(A|B) = [P(B|A)][P(A)] /P(B)
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 = ...
(a)
By the Hartley's formula the entropy H = ...
H = - Σ(pi*log pi)
H = - Σ (log pi)
H = log m
H = - Σ (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 * Σ(pi*log pi)
H = - n * Σ (log pi)
H = - n * Σ pi
H = - n * Σ (pi/log pi)
By the Shannon's formula the entropy H = ...
H = - Σ(pi*log pi)
H = - Σ (log pi)
Choose an example of block code
Shannon-Fano code
Huffman code
Hamming code
None of the given
Choose conditions of an optimal coding (p – probability, l – length of a code word)
pi < pj and li<=lj
pi > pj and li<=lj
pi > pj and li>=lj
none of the given
Choose the formula to create the Hamming code
(n, k) = (2r - 1, 2r - 1 - r)
(n, k) = (2r, 2r - 1 - r)
(n, k) = (2r - 1, 2r - r)
(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.
N = mn
N = mn
N = m*n
N = log m
Code rate R (k information bits and n total bits) is defined as
k = n/R
R = k * n
R = k/n
R = n/k
Conditional entropy H(Y|X) lies between
- H(Y) and 0
0 and H(Y)
- H(Y) and H(Y)
0 and 1
Convert the message into a signal suitable for transmission over the channel of communication, referred to as ...
Encoding
Decoding
Entropy
Redundancy
For Hamming distance dmin and r errors in the received word, the condition to be able to detect the errors is
dmin>= r+1
dmin>= 2r+1
dmin>= 2r+2
dmin>= r+2
For Hamming distance dmin and s errors in the received word, the condition to be able to correct the errors is
dmin>= s+1
dmin>= 2s+1
dmin>= 2s+2
dmin>= s+2
Hamming distance can easily be found with ...
XNOR operation
XOR operation
OR operation
Как шум влияет на данные?
изменяет только 0 на 1
изменяет только 1 на 0
изменяет 0 на 1 и 1 на 0
ни одно из вышеуказанных
Какая буква получит самый короткий код после кодирования Хаффмана слова «bbaacccabaac»?
a
b
c
ни одна
Если k — количество бит до кодирования Хэмминга, а n — количество бит после кодирования Хэмминга, то
k > n
k < n
k = n
k = 1/2 n
В цифровой системе связи, чем меньше скорость кода, тем ... избыточных бит.
меньше
равно
больше
непредсказуемо
Основная идея кодов управления ошибками:
добавить некоторую избыточность
удалить некоторую избыточность
удвоить все биты
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 formula to find the amount of information if events have different probabilities.
Hartley's formula
Shannon's formula
Fano's formula
Bayes' formula
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
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
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
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
What is the first step of Shannon-Fano algorithm?
Каково расстояние Хэмминга между двумя строками одинаковой длины?
количество позиций, в которых соответствующие символы различаются
количество позиций, в которых соответствующие символы совпадают
количество одинаковых символов в первой строке
количество одинаковых символов во второй строке
Каково значение числа "2" в формуле I = n*log2m?
Двоичная система счисления
Длина сообщения равна 2
Не имеет значения
Информация измеряется в нитах
Когда основание логарифма равно 10, то единицей измерения информации является
байты
диты
ниты
биты
Когда основание логарифма равно 2, то единицей измерения информации является
байты
биты
ниты
диты
When the base of the logarithm is e, then the unit of measure of information is
bytes
nits
dits
bits
Which letter will get the shortest codeword after Huffman coding of the word "abracadabra"?
c
r
d
a
Which of the following codes is uniform?
ASCII
Shannon-Fano
Huffman
None of the given
According to Kerckhoffs’ Principle, which part of a cryptographic system must remain secret to ensure security?
The communication protocol
The encryption algorithm
The key
The coding scheme
In cryptography terminology, the original text is known as ...
Key
Encrypt
Plaintext
Cipher
Ciphertext
The basic idea behind Shannon–Fano coding is to
compress data by using fewer bits to encode fewer frequently occurring characters
expand data by using fewer bits to encode more frequently occurring characters
compress data by using fewer bits to encode more frequently occurring characters
compress data by using more bits to encode more frequently occurring characters
What is the primary focus of steganography compared to general security by obscurity?
Making the ciphertext look like gibberish to the attacker
Sharing the concealment method with the public
Concealing the very presence of a message
Increasing the mathematical complexity of the encryption
What is another name for Kerckhoffs’s Principle?
Advanced Persistent Threat
Information Asymmetry
Shannon’s Maxim
The Interaction Routine
According to Kerckhoffs’ Principle, which part of a cryptographic system must remain secret to ensure security?
The coding scheme
The encryption algorithm
The key
The communication protocol
A shorthand way of saying when set A does not occur
A—
Complement
Intersection
Union
−A
Which of the following is typically known by an attacker under Kerckhoffs’ Principle?
The key length and how the key is used
The plaintext message before encryption
The password to Bob’s private computer
The specific value of the secret key
Which of the following is NOT allowed when using AI tools, regardless of the use level?
Using AI to summarize a long research paper to better understand the core arguments
Using AI to brainstorm initial topics or create a rough outline for a project
Employing AI to check for grammatical errors or to improve the clarity of your original writing
Entering another person’s personal details
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
c=1,d=000,e=001,b=010,a=0110,f=0111
c=0,d=111,e=110,b=101,a=1001,f=1000
c=1,d=01,e=001,b=0000,a=00010,f=00011
c=1,d=01,e=001,b=000,a=0010,f=00011
c=0,d=101,e=110,b=101,a=1000,f=1001
If a directed edge is drawn from vertex u to vertex v, how are the roles of u and v formally described?
u is the tail and v is the head
u is the origin and v is the incident
u and v are both considered heads of the edge
u is the head and v is the tail
The Hamming distance between “make” and “made” is
(a)
В контексте ориентированных графов, каково основное различие между использованием фигурных скобок {u, v} и круглых скобок (u, v) для обозначения ребра?
Разницы нет; обе нотации могут использоваться взаимозаменяемо в ориентированных графах.
Фигурные скобки обозначают множество, в котором порядок не важен, в то время как круглые скобки указывают на конкретное направление от u к v.
Круглые скобки используются для социальных сетей, а фигурные скобки — для физических карт.
Фигурные скобки обозначают, что вершины должны быть соединены сами с собой, а круглые скобки — нет.
Пусть буквы a, b, c, d, e, f имеют вероятности 1/2, 1/4, 1/8, 1/16, 1/32, 1/32 соответственно. Какой из следующих вариантов является кодом Хаффмана для букв a, b, c, d, e, f?
a: 1, b: 01, c: 001, d: 0001, e: 00001, f: 00000
a: 0, b: 10, c: 110, d: 1110, e: 11110, f: 11111
a: 00, b: 01, c: 10, d: 110, e: 1110, f: 1111
a: 1, b: 00, c: 010, d: 0110, e: 01110, f: 01111
