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Calendar description

This course description includes:

  • Application of computational methods to engineering problems.
  • Number systems, errors and error propagation.
  • Roots of nonlinear equations.
  • Introduction to numerical linear algebra.
  • Interpolation and numerical integration.
  • Introduction to numerical solutions of ordinary differential equations, optimization.

It also includes a statement that the [e]mphasis will be placed on algorithm development.

This course covers all these topics, but also includes a section on specific partial differential equations of interest to electrical and computer engineering students. Additionally, this course includes topics related to both exact values and when data is gathered in the presence of noise.

This course is essential for computer engineering students because it bridges the gap between theoretical mathematical concepts and their practical applications in engineering. Throughout the course, you’ll learn to apply computational techniques to solve real-world engineering problems, building a strong foundation in number systems, error analysis, and the mathematical principles behind numerical solutions. These skills are invaluable, enabling you to model complex systems and solve equations that standard analytical methods cannot address, making you more adaptable and resourceful as an engineer.

In the digital age, data is often imperfect, whether due to measurement noise or rounding errors in computation. This course will guide you in developing algorithms that can handle such inaccuracies, allowing you to interpret data accurately and make reliable predictions. From finding the roots of nonlinear equations to solving systems of linear equations, integrating functions, and addressing partial differential equations, you’ll build a toolkit of computational methods that will serve you across various fields, including circuit analysis, signal processing, and control systems.

Algorithm development is emphasized throughout, empowering you to create customized solutions for engineering challenges. Whether you’re optimizing systems or working with noisy data in signal processing, these methods are essential for delivering precise, reliable results. Mastery of numerical methods prepares you to handle the unique demands of engineering applications, making this course a key asset in your career as a computer engineer.