| １． |
Outline |
|
In this course, students learn the information theory that is a theory of digital communications and storage which supports the information society of nowadays.
Informaton theory is a theory that deals with the theoretical bounds of encoding and concrete encoding algorithm. In this theory, encodings are classified into source coding to increase the efficiency of communications, and into channel coding to increase the reliability of communications.
In this course, students aims at being possible to discuss theoretically the infimum of the average code length of source coding, and the supremum of the code rate of channel coding without errors giving the probabilistic model of a source or a channel. In addition, students aims at being able to decide which encoding algorithm is effective for a given purpose concretely.
Moreover, this course deals with analog source/channel, analog-to-digital or digital-to-analog conversion, the sampling theory, character encoding, the relation between information theory and cryptology.
Students acquire skills related to the diplomatic policy, DP4C.
<Comments>
In this course, students learn the information theory that is a theory of digital communications and storage which supports the information society of nowadays.
Information theory is a theory that deals with the theoretical bounds of encoding and concrete encoding algorithm. In this theory, encodings are classified into source coding to increase the efficiency of communications, and into channel coding to increase the reliability of communications.
In this course, students aim at being possible to discuss theoretically the infimum of the average code length of source coding, and the supremum of the code rate of channel coding without errors giving the probabilistic model of a source or a channel. In addition, students aim at being able to decide which encoding algorithm is effective for a given purpose concretely.
Moreover, this course deals with analog source/channel, analog-to-digital or digital-to-analog conversion, the sampling theory, character encoding, the relation between information theory and cryptology.
Students acquire skills related to the diplomatic policy, DP4C.
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| ２． |
Objectives |
|
The goal of this class is that students master the following abilities;
Students can explain the relation of system model of communication, noise source, source coding and channel coding.
Students can explain the purpose of source/channel coding, the meanings of Shannon's source coding theorem and Shannon's noisy-channel coding theorem.
Students can explain the model of the memoryless source, source with memory, the memoryless channel, the burst channel.
Students can explain features which source coding algorithms should have by using code tree.
Students can process basic source coding/encoding algorithm as for basic source coding algorithms.
Students can explain the amount of information, entropy, mutual information, and can compute those values
as for some basic sources.
Students can explain the meanings of channel capacity, and compute that as for some basic channels.
Students can process basic binary source coding algorithms as for some basic channel coding algorithms.
Students understand the sampling theorem and can obtain appropriate sampling frequency given maximum frequency of a signal.
Students can explain the necessity of character encoding and the features of representative character encoding.
<Comments>
訂正無し
|
| ３． |
Grading Policy |
|
Grading policy:
Midterm report(50%), Examination(50%).
The way of feedback;
Answers for questions or feedback for the contents of class, worksheets, and examination will be given in a class, through LMS or in office hours.
<Comments>
Grading policy:
Midterm report(50%), Examination(50%).
The way of feedback;
Answers for questions or feedback for the contents of class, worksheets, and examination will be given in a class, through LMS or during office hours.
|
| ４． |
Textbook and Reference |
|
Textbook：今井秀樹著、"情報理論 改訂2版"、オーム社、ISBN-13: 978-4274223259
Teaching materials: Published through LMS.
<Comments>
訂正無し
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| ５． |
Requirements (Assignments) |
|
Before a class, students are required to prepare the class by using materials, such as slides, handouts and
related materials which will be published on the LMS, which requires about 1.5 hours.
In a class, students should concentrate on, not to take notes, but to understand the contents of class,
to solve exercises in a class,
because most of the materials were published on the LMS before the class and students can bring them with
tablets or smart phones.
After a class, students are required to review the materials used in the class or quizzes on the LMS, which requires about 1.5 hours.
<Comments>
Before a class, students are required to prepare the class by using materials, such as slides, handouts and related materials which will be published on the LMS, which requires about 1.5 hours.
In a class, students should concentrate on, not to take notes, but to understand the contents of class, to solve exercises in a class, because most of the materials are published on the LMS before the class and students can bring them with tablets or smartphones.
After a class, students are required to review the materials used in the class or quizzes on the LMS, which requires about 1.5 hours.
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| ６． |
Note |
|
Students can hardly earn credits not submitting the mid-term report. Thus, it is expected students to observe the deadline.
As for the self-learning support students are expected to utilize materials, such as slides, handouts and quizzes on the LMS
Before taking this course, students should take the following courses;
Mathematical Logic, Linear Algebra, Discrete Mathematics, Applied Mathematics, Mathematical Statics, Digital Image Processing.
At the same semester with this course, students should take Multimedia Information Processing.
After taking this course, students should take the following courses;
Introduction to Stochastic Processes, Information Security, Communication, Communication Systems.
If a student has a question on quizzes or mid-term report or examinations, ask the question in the class or in office hours or through LMS.
This course is a required course, and relates to the mid term 4-1 of the attaining targets for learning and educating, in the JABEE program.
<Comments>
Students can hardly earn credits not submitting the mid-term report. Thus, it is expected students to observe the deadline.
As for the self-learning support students are expected to utilize materials, such as slides, handouts and quizzes on the LMS.
Before taking this course, students should take the following courses;
Mathematical Logic, Linear Algebra, Discrete Mathematics, Applied Mathematics, Mathematical Statics, Digital Image Processing.
At the same semester with this course, students should take Multimedia Information Processing.
After taking this course, students should take the following courses;
Introduction to Stochastic Processes, Information Security, Communication, Communication Systems.
If a student has a question on quizzes or mid-term report or examinations, ask the question in the class or in office hours or through LMS.
This course is a required course, and relates to the mid term 4-1 of the attaining targets for learning and educating, in the JABEE program.
|
| ７． |
Schedule |
|
１. Introduction
Problems in the Information Theory
<Comments>
訂正無し |
２. Review of Probability Theory
Modeling digital information sources
<Comments>
訂正無し
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３. Modeling digital channels
<Comments>
訂正無し
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４. Analog information sources, channels
Fourier seriese expansion, Sampling Theory, Analog to Digital Conversion, Character codes
<Comments>
Analog information sources, channels
Fourier series expansion, Sampling Theory, Analog to Digital Conversion, Character codes
|
５. Source coding and its bound
Basic concepts in source coding, the bound of average code length
<Comments>
訂正無し
|
６. Source coding and its bound
Huffman coding, extended information source, block coding, Shannon's source coding theorem
<Comments>
訂正無し |
７. Entropy of basic information source/Source coding1
Entropy of independently, identically distributed(i.i.d.) information source, Entropy of Markov information source, Huffman Block Coding, Run-length Huffman Coding
<Comments>
訂正無し |
８. Source coding 2/Entropy and Mutual Information, Arithmetic coding
<Comments>
訂正無し
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９. Entropy, distortion
<Comments>
訂正無し
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10. Channel coding and its bound
Channel Capacity, Basic concepts in channel coding, noisy channel coding theorem
<Comments>
訂正無し |
11. Channel Coding 1
Single error detection/correction
<Comments>
訂正無し |
12. Channel Coding 2
Ciclic codes
<Comments>
Channel Coding 2
Cyclic codes
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13. Channel Coding 3
Decoding of ciclic codes, Ciclic Redundancy Code(CRC), Ciclic Hamming Codes
<Comments>
Channel Coding 3
Decoding of cyclic codes, Cyclic Redundancy Code(CRC), Cyclic Hamming Codes |
14. Analog information source and analog channel, Information Theory and Cryptology
<Comments>
訂正無し
|
15. Summary and examination
<Comments>
訂正無し
|
|
| １． |
Outline |
|
In this course, students learn the information theory that is a theory of digital communications and storage which supports the information society of nowadays.
Informaton theory is a theory that deals with the theoretical bounds of encoding and concrete encoding algorithm. In this theory, encodings are classified into source coding to increase the efficiency of communications, and into channel coding to increase the reliability of communications.
In this course, students aims at being possible to discuss theoretically the infimum of the average code length of source coding, and the supremum of the code rate of channel coding without errors giving the probabilistic model of a source or a channel. In addition, students aims at being able to decide which encoding algorithm is effective for a given purpose concretely.
Moreover, this course deals with analog source/channel, analog-to-digital or digital-to-analog conversion, the sampling theory, character encoding, the relation between information theory and cryptology.
Students acquire skills related to the diplomatic policy, DP4C.
<Comments>
In this course, students learn the information theory that is a theory of digital communications and storage which supports the information society of nowadays.
Information theory is a theory that deals with the theoretical bounds of encoding and concrete encoding algorithm. In this theory, encodings are classified into source coding to increase the efficiency of communications, and into channel coding to increase the reliability of communications.
In this course, students aim at being possible to discuss theoretically the infimum of the average code length of source coding, and the supremum of the code rate of channel coding without errors giving the probabilistic model of a source or a channel. In addition, students aim at being able to decide which encoding algorithm is effective for a given purpose concretely.
Moreover, this course deals with analog source/channel, analog-to-digital or digital-to-analog conversion, the sampling theory, character encoding, the relation between information theory and cryptology.
Students acquire skills related to the diplomatic policy, DP4C.
|
| ２． |
Objectives |
|
The goal of this class is that students master the following abilities;
Students can explain the relation of system model of communication, noise source, source coding and channel coding.
Students can explain the purpose of source/channel coding, the meanings of Shannon's source coding theorem and Shannon's noisy-channel coding theorem.
Students can explain the model of the memoryless source, source with memory, the memoryless channel, the burst channel.
Students can explain features which source coding algorithms should have by using code tree.
Students can process basic source coding/encoding algorithm as for basic source coding algorithms.
Students can explain the amount of information, entropy, mutual information, and can compute those values
as for some basic sources.
Students can explain the meanings of channel capacity, and compute that as for some basic channels.
Students can process basic binary source coding algorithms as for some basic channel coding algorithms.
Students understand the sampling theorem and can obtain appropriate sampling frequency given maximum frequency of a signal.
Students can explain the necessity of character encoding and the features of representative character encoding.
<Comments>
訂正無し
|
| ３． |
Grading Policy |
|
Grading policy:
Midterm report(50%), Examination(50%).
The way of feedback;
Answers for questions or feedback for the contents of class, worksheets, and examination will be given in a class, through LMS or in office hours.
<Comments>
Grading policy:
Midterm report(50%), Examination(50%).
The way of feedback;
Answers for questions or feedback for the contents of class, worksheets, and examination will be given in a class, through LMS or during office hours.
|
| ４． |
Textbook and Reference |
|
Textbook：今井秀樹著、"情報理論 改訂2版"、オーム社、ISBN-13: 978-4274223259
Teaching materials: Published through LMS.
<Comments>
訂正無し
|
| ５． |
Requirements (Assignments) |
|
Before a class, students are required to prepare the class by using materials, such as slides, handouts and
related materials which will be published on the LMS, which requires about 1.5 hours.
In a class, students should concentrate on, not to take notes, but to understand the contents of class,
to solve exercises in a class,
because most of the materials were published on the LMS before the class and students can bring them with
tablets or smart phones.
After a class, students are required to review the materials used in the class or quizzes on the LMS, which requires about 1.5 hours.
<Comments>
Before a class, students are required to prepare the class by using materials, such as slides, handouts and related materials which will be published on the LMS, which requires about 1.5 hours.
In a class, students should concentrate on, not to take notes, but to understand the contents of class, to solve exercises in a class, because most of the materials are published on the LMS before the class and students can bring them with tablets or smartphones.
After a class, students are required to review the materials used in the class or quizzes on the LMS, which requires about 1.5 hours.
|
| ６． |
Note |
|
Students can hardly earn credits not submitting the mid-term report. Thus, it is expected students to observe the deadline.
As for the self-learning support students are expected to utilize materials, such as slides, handouts and quizzes on the LMS
Before taking this course, students should take the following courses;
Mathematical Logic, Linear Algebra, Discrete Mathematics, Applied Mathematics, Mathematical Statics, Digital Image Processing.
At the same semester with this course, students should take Multimedia Information Processing.
After taking this course, students should take the following courses;
Introduction to Stochastic Processes, Information Security, Communication, Communication Systems.
If a student has a question on quizzes or mid-term report or examinations, ask the question in the class or in office hours or through LMS.
This course is a required course, and relates to the mid term 4-1 of the attaining targets for learning and educating, in the JABEE program.
<Comments>
Students can hardly earn credits not submitting the mid-term report. Thus, it is expected students to observe the deadline.
As for the self-learning support students are expected to utilize materials, such as slides, handouts and quizzes on the LMS.
Before taking this course, students should take the following courses;
Mathematical Logic, Linear Algebra, Discrete Mathematics, Applied Mathematics, Mathematical Statics, Digital Image Processing.
At the same semester with this course, students should take Multimedia Information Processing.
After taking this course, students should take the following courses;
Introduction to Stochastic Processes, Information Security, Communication, Communication Systems.
If a student has a question on quizzes or mid-term report or examinations, ask the question in the class or in office hours or through LMS.
This course is a required course, and relates to the mid term 4-1 of the attaining targets for learning and educating, in the JABEE program.
|
| ７． |
Schedule |
|
１. Introduction
Problems in the Information Theory
<Comments>
訂正無し |
２. Review of Probability Theory
Modeling digital information sources
<Comments>
訂正無し
|
３. Modeling digital channels
<Comments>
訂正無し
|
４. Analog information sources, channels
Fourier seriese expansion, Sampling Theory, Analog to Digital Conversion, Character codes
<Comments>
Analog information sources, channels
Fourier series expansion, Sampling Theory, Analog to Digital Conversion, Character codes
|
５. Source coding and its bound
Basic concepts in source coding, the bound of average code length
<Comments>
訂正無し
|
６. Source coding and its bound
Huffman coding, extended information source, block coding, Shannon's source coding theorem
<Comments>
訂正無し |
７. Entropy of basic information source/Source coding1
Entropy of independently, identically distributed(i.i.d.) information source, Entropy of Markov information source, Huffman Block Coding, Run-length Huffman Coding
<Comments>
訂正無し |
８. Source coding 2/Entropy and Mutual Information, Arithmetic coding
<Comments>
訂正無し
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９. Entropy, distortion
<Comments>
訂正無し
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10. Channel coding and its bound
Channel Capacity, Basic concepts in channel coding, noisy channel coding theorem
<Comments>
訂正無し |
11. Channel Coding 1
Single error detection/correction
<Comments>
訂正無し |
12. Channel Coding 2
Ciclic codes
<Comments>
Channel Coding 2
Cyclic codes
|
13. Channel Coding 3
Decoding of ciclic codes, Ciclic Redundancy Code(CRC), Ciclic Hamming Codes
<Comments>
Channel Coding 3
Decoding of cyclic codes, Cyclic Redundancy Code(CRC), Cyclic Hamming Codes |
14. Analog information source and analog channel, Information Theory and Cryptology
<Comments>
訂正無し
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15. Summary and examination
<Comments>
訂正無し
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