Advanced Lecture on Intellectual Signal Processing

Course Information

College	Toyama College	Year	2022
Course Title	Advanced Lecture on Intellectual Signal Processing
Course Code	0037	Course Category	Specialized / Elective
Class Format	Lecture	Credits	Academic Credit: 2
Department	ECOdesign Engineering Course	Student Grade	Adv. 1st
Term	First Semester	Classes per Week	2
Textbook and/or Teaching Materials
Instructor	Ishida Fumihiko

Course Objectives

Through this course, understanding of the following will be facilitated
(1) Basic technology about pattern processing
(2) Basic technology about information analysis
(3) Basic technology about multivariate analysis
(4) Basic technology about statistical modeling
(5) Basic technology about pattern recognition
(6) Basic technology about artificial intelligence

Rubric

	Ideal Level of Achievement (Very Good)	Standard Level of Achievement (Good)	Unacceptable Level of Achievement (Fail)
Evaluation 1	Clearly understands the pattern processing technology and has the ability to explain in detail	Understands the pattern processing technology and has the ability to explain in general	Unable to explain the pattern processing technology in general
Evaluation 2	Clearly understands the information analysis technology and has the ability to calculate the information amount in detail	Understands the information analysis technology and has the ability to explain in general	Unable to explain the information analysis technology in general
Evaluation 3	Clearly understands the multivariate analysis technology and has the ability to explain in detail	Understands the multivariate analysis technology and has the ability to explain in general	Unable to explain the multivariate analysis technology in general
Evaluation 4	Clearly understands the statistical modeling technology and has the ability to calculate the process in detail	Understands he statistical modeling technology and has the ability to explain in general	Unable to explain he statistical modeling technology in general
Evaluation 5	Clearly understands the pattern recognition technology and has the ability to explain in detail	Understands the pattern recognition technology and has the ability to explain in general	Unable to explain the pattern recognition technology in general
Evaluation 6	Clearly understands the artificial intelligence technology and has the ability to explain in detail	Understands the artificial intelligence technology and has the ability to explain in general	Unable to explain the artificial intelligence technology in general

Assigned Department Objectives

学習・教育到達度目標 A-6 （核となる専門分野の既存技術を説明でき，社会から要求されている問題や実務上の問題を見出し設定することができる。）

JABEE 1(2)(d)(1) （専門工学（工学（融合複合・新領域）における専門工学の内容は申請高等教育機関が規定するものとする）の知識と能力）

JABEE 1(2)(e) （種々の科学、技術及び情報を活用して社会の要求を解決するためのデザイン能力）

Teaching Method

Outline:

In order to acquire necessary information from multivariate signals recorded by experiment etc., analysis and processing methods corresponding to the purpose are required. This course aims to understand representative analytical methods and the basic technology.

Style:

Lecture

Notice:

Characteristics of Class / Division in Learning

Aided by ICT

Applicable to Remote Class

Course Plan

			Theme	Goals
1st Semester
	1st Quarter
		1st	Pattern processing	Learn the pattern processing technology
		2nd	Information analysis	Learn the information analysis technology
		3rd	Multivariate analysis(1)	Learn the principle component analysis technology
		4th	Multivariate analysis(2)	Learn the independent component anaysis and non-negative factorization analysis technology
		5th	Statistical modeling (1)	Learn general filters
		6th	Statistical modeling (2)	Learn the Gaussian mixture model and EM algorithm technology
		7th	Statistical modeling (3)	Learn the Kalman filter and particle filter technology
		8th	Experimental plan and statistical analysis (1)	Learn statistical analysis
	2nd Quarter
		9th	Experimental plan and statistical analysis (2)	Learn methods about experimental plans
		10th	Examination
		11th	Explanation of the examination
		12th	Pattern recognition	Learn the pattern recognition technology
		13th	Artificial intelligence (1)	Learn the artificial intelligence technology
		14th	Artificial intelligence (2)	Learn relationships between the artificial intelligence and the society
		15th	Report	Write reports and check the contents about the pattern recogition and artificial intelligence technology
		16th	Summary	Summarize the study content and confirm grades

Evaluation Method and Weight (%)

	Examination	Presentation	Mutual Evaluations between students	Behavior	Portfolio	Other	Total
Subtotal	60	40	0	0	0	0	100
Basic Ability	0	0	0	0	0	0	0
Technical Ability	60	40	0	0	0	0	100
Interdisciplinary Ability	0	0	0	0	0	0	0