Line 110: Line 110:
 
|-
 
|-
 
|22.11.
 
|22.11.
|The basics of linear algebra: The basic problem of linear algebra (Matrix and Vector)  
+
|The basics of linear algebra: The basic problem of linear algebra (matrix and vector)  
  
 
|-
 
|-
Line 126: Line 126:
 
|-
 
|-
 
|06.12.
 
|06.12.
|The basics of linear algebra: Matrices (Advanced operations)
+
|The basics of linear algebra: Matrices (advanced operations)
  
 
|-
 
|-
Line 154: Line 154:
 
!References
 
!References
 
|-
 
|-
|05.10.
+
|03.10.
 
|1. Choose 1 Exercise from the Exercise 2.1 (page 54).
 
|1. Choose 1 Exercise from the Exercise 2.1 (page 54).
 
2. Is 0/0 = 0 statement or not? Why?
 
2. Is 0/0 = 0 statement or not? Why?
Line 161: Line 161:
 
|Discrete and combinatorial mathematics: An applied introduction / Ralph P. Grimaldi.
 
|Discrete and combinatorial mathematics: An applied introduction / Ralph P. Grimaldi.
 
Rose-Hulman Institute of Technology: Pearson, 2004; [http://ceiucaweb.com.ar/documentos/6-informatica/3er-anio-2do-cuatri/estructura-de-datos/apunte/Discrete_and_Combinatorial_Mathematics_5th_ed_-_R._Grimaldi.pdf Download here];  
 
Rose-Hulman Institute of Technology: Pearson, 2004; [http://ceiucaweb.com.ar/documentos/6-informatica/3er-anio-2do-cuatri/estructura-de-datos/apunte/Discrete_and_Combinatorial_Mathematics_5th_ed_-_R._Grimaldi.pdf Download here];  
 
+
}
|-
+
|12.10.
+
|1. Choose 2 Exercises from the Exercise 2.4 (page 100).
+
| 1 point / exercise
+
|Discrete and combinatorial mathematics: An applied introduction / Ralph P. Grimaldi.
+
Rose-Hulman Institute of Technology: Pearson, 2004; [http://ceiucaweb.com.ar/documentos/6-informatica/3er-anio-2do-cuatri/estructura-de-datos/apunte/Discrete_and_Combinatorial_Mathematics_5th_ed_-_R._Grimaldi.pdf Download here];
+
 
+
|-
+
|19.10
+
| Find/create the open statement which is possible to prove by mathematical induction.
+
Prove the statement and use the proof to explain the principle of mathematical induction.
+
| 3 points
+
 
+
|-
+
|26.10
+
| 1. Take the FEV1 Spirometry graph in time (Morning Lecture, slide 27). Based on that graph write as many information as you can.
+
2. Find the quadratic function characteristics.
+
| 2 - 4 points
+
2 points
+
 
+
|-
+
|02.11
+
| Find derivatives:
+
1. y = (x + 5)*x^2
+
 
+
2. y = log(2)x – 5x + 7x^5
+
 
+
3. y = sin x / cos x
+
 
+
4.  y = (3x + 5^x – 6)/(ln x + e^x)
+
| 4 points
+
 
+
|-
+
|09.11
+
| Find the local and global extremes of a function. Create the graph of that function: y = x2 / (1 – x2)
+
(you can check your answer on a page 115)
+
| 4 points
+
| Calculus / Gilbert Strang. Massachusetts Institute of Technology: Wellesley-Cambridge Press. [https://ocw.mit.edu/ans7870/resources/Strang/Edited/Calculus/Calculus.pdf Download here]; 
+
 
+
|-
+
|30.11
+
|Find non-homogeneous linear system of 5 equations with 5 variables.
+
Use Gaussian Reduction to find the solution of your system.
+
| 4 points
+
| Fundamentals of Linear Algebra / James B. Carrell. Canada: University of British Colombia, 2005. [https://www.math.ubc.ca/~carrell/NB.pdf Download here];
+
 
+
|-
+
|07.12
+
|Try to find (google or book(s)) the explanation of the mathematical term: eigenvalue.
+
Choose any matrix and find its eigenvalues.
+
| 4 points
+
| Fundamentals of Linear Algebra / James B. Carrell. Canada: University of British Colombia, 2005. [https://www.math.ubc.ca/~carrell/NB.pdf Download here];
+
|}
+
  
 
== References ==
 
== References ==

Revision as of 09:51, 27 September 2018

Mathematics for Cognitive Science 2-IKVa-102

The lectures will provide students with basics of propositional and predicate logic, linear algebra, mathematical analysis, and probability that are important for the study of informatics and its role in (computational) cognitive science. At the same time, students will learn about mathematical culture, notation, way of thinking and expressing oneself.

Course schedule

Type Day Time Room Lecturer
Lecture/Exercise Wednesday 08:10 M-VII Martina Babinská
Exercise/Lecture Thursday 13:10 M-VII Martina Babinská

Syllabus

Date Topic References
27.09. The basics of logic and proving methods: propositional logic. Discrete and combinatorial mathematics: An applied introduction / Ralph P. Grimaldi.

Rose-Hulman Institute of Technology: Pearson, 2004; Download here; chap. 2.1, 2.2

03.10. The basics of logic and proving methods: propositional + predicate logic. Discrete and combinatorial mathematics: An applied introduction / Ralph P. Grimaldi.

Rose-Hulman Institute of Technology: Pearson, 2004; Download here; chap. 2.4

04.10. The basics of logic and proving methods: Sets (sets of numbers, set theory, set operations, the laws of set theory) Discrete and combinatorial mathematics: An applied introduction / Ralph P. Grimaldi.

Rose-Hulman Institute of Technology: Pearson, 2004; Download here; chap. 3.1, 3.2

10.10. The basics of logic and proving methods: Proving methods (constructive, direct, contrapositive, contradiction, biconditional, mathematical induction) Discrete and combinatorial mathematics: An applied introduction / Ralph P. Grimaldi.

Rose-Hulman Institute of Technology: Pearson, 2004; Download here; chap. 2, 3, 4.1

11.10. Counting methods for Rows (sum and multiplying) Discrete and combinatorial mathematics: An applied introduction / Ralph P. Grimaldi.

Rose-Hulman Institute of Technology: Pearson, 2004; Download here;

17.10. The basics of mathematical analysis: mathematical function vs dependency (definition, mathematical functions in the real world )
18.10. The basics of mathematical analysis: mathematical function (graph vs. formula, basic mathematical functions, basic characteristics)
24.10. The basics of mathematical analysis: mathematical function (quadratic function, monotonicity, boundary, extremes)
25.10. The basics of mathematical analysis: mathematical function (continuity, limit)
31.10. The basics of mathematical analysis: calculus (the rate of change, derivative definition, derivative in the real world)
07.11. The basics of mathematical analysis: calculus (derivative counting rules)
08.11. The basics of mathematical analysis: calculus (maximum and minimum problem, convex and concave problem)
14.11. The basics of mathematical analysis: calculus (the chain rule, functions’ characteristics in a view of derivative)
15.11. Repeating and practicing class
21.11. Middle term writing test
22.11. The basics of linear algebra: The basic problem of linear algebra (matrix and vector)
28.11. The basics of linear algebra: The basic problem of linear algebra (vector operations, linear combination)
29.11. The basics of linear algebra: Matrices (basic operations)
05.12. The basics of linear algebra: Matrices (Gaussian Reduction)
06.12. The basics of linear algebra: Matrices (advanced operations)
12.12. The basics of linear algebra: Matrices (eigenvalues, eigenvectors)
13.12. The basics of probability: Introduction (probability in the real world, definition)
13.12. The basics of probability: Introduction (counting basics)
20.12. Repeating and practicing

}


Homework

Date Homework Points References
03.10. 1. Choose 1 Exercise from the Exercise 2.1 (page 54).

2. Is 0/0 = 0 statement or not? Why?

1 point

1 point

Discrete and combinatorial mathematics: An applied introduction / Ralph P. Grimaldi.

Rose-Hulman Institute of Technology: Pearson, 2004; Download here; }

References

  • Discrete and combinatorial mathematics: An applied introduction / Ralph P. Grimaldi.

Rose-Hulman Institute of Technology: Pearson, 2004. Download here;

  • Calculus / Gilbert Strang. Massachusetts Institute of Technology: Wellesley-Cambridge Press. Download here;
  • Fundamentals of Linear Algebra / James B. Carrell. Canada: University of British Colombia, 2005. Download here;
  • Artificial Intelligence: A Modern Approach / Stuart Russell and Peter Norvig. The USA: Pearson, 2010. Download here;

Course grading

To be classified student has to achieve at least 50% of every activity:

PROJECT

  • form: essay, presentation, song or movie
  • topic: What does mathematics mean for me? What am I expecting from this course?
  • term: 27.10.2017
  • goal: self-study motivation
  • weight: 15%

WEEKLY EXAMS

  • form: 10-15 minutes writing tests
  • term: every Thursday at the beginning of the exercise
  • goal: regular preparation
  • weight: 40%
  • note: student can also achieve extra (bonus) points for: weekly homeworks, class work (solving problems and schoolmate’s help) and/or self-activity (lecture preparation… )

MIDDLE TERM EXAM

  • form: 90 minutes writing test (student can choose from the offered task sets)
  • term: 23.11.2017
  • goal: progress definition
  • weight: 15%

FINAL EXAM

  • form: 90 minutes writing test
  • term: January, February 2018
  • goal: course output
  • weight: 30%

OVERALL GRADING: A > 90%, B > 80%, C> 70%, D > 60%, E > 52% points.


Information list

Course information sheet >