# Course Identification

Basic Topics 1

20194151

## Lecturers and Teaching Assistants

Prof. Harry Dym

Heli Ben-Hamu

## Course Schedule and Location

2019

First Semester

Monday, 11:15 - 13:00, Ziskind, Rm 1

Thursday, 10:15 - 12:00, Ziskind, Rm 1

Thursday, 10:15 - 12:00, Ziskind, Rm 1

05/11/2018

## Field of Study, Course Type and Credit Points

Mathematics and Computer Science (Systems Biology / Bioinformatics): Lecture; Elective; 4.00 points

## Comments

## Prerequisites

- Some familiarity with elementary linear algebra would be helpful, though not strictly necessary, since most of the basic concepts will be reviewed (quickly).
- Elementary concepts of calculus (differentiation, integration, continuity) will enter in the second part of the course.

## Restrictions

40

## Language of Instruction

## Attendance and participation

## Grade Type

## Grade Breakdown (in %)

70%

30%

## Evaluation Type

**Examination**

## Scheduled date 1

04/03/2019

Ziskind, Rm 1

1000-1300

N/A

## Scheduled date 2

14/03/2019

Ziskind, Rm 1

1000-1300

N/A

## Estimated Weekly Independent Workload (in hours)

## Syllabus

This course will both review and extend a number of basic mathematical tools which are generally useful in applications and are typically assumed as prerequisites for many of the current courses. The lectures will focus on the following topics:

- Linear Algebra: Jordan forms. Special classes of matrices (unitary, Hermitian, normal, positive definite, stochastic). Singular value decompositions. Pseudoinverses. Linear systems of equations.
- Normed linear spaces: Norms. Basic inequalities. Inner product spaces. Orthogonal systems. Projections, Orthogonal projections, Mean square approximation.
- Differential Equations: Systems of first order differential equations. Elements of stability theory. Difference equations.
- Matrix valued functions: Mean value theorems. Fixed point theorems. The inverse function theorem. The implicit function theorem.
- Optimization: Extremal problems. Lagrange multipliers.
- Matrices with nonnegative entries: Birkhoff-von Neumann theorem. von Neumann's inequality.

## Learning Outcomes

Upon successful completion of this course students should be able to:

- Demonstrate familiarity with the basic tools of linear algebra with special emphasis placed on the ability to compute.
- Calculate Jordan forms.
- Solve systems of linear equations.
- Compute projections (both orthogonal and skew), best mean square approximation and applications of singular value decomposition.
- Apply the acquired knowledge to multivariable calculus (including implicit function theorems and extremal problems with constraints).