and process data efficiently using sophisticated data structures and algorithms Design algorithms and analyze their complexity in terms of running time and space usage Create applications that are ...

The student is also exposed to the notion of a faster algorithm and asymptotic complexity through the O, big-Omega and big-Theta notations. In this module, the student will learn about the basics of ...

When I first started working with integral field spectroscopic (IFU) data, I was struck by how much complexity was being ...

The first step in reverse engineering is determining whether the algorithm follows a purely random model (such as RNG) or exhibits deterministic characteristics (such as PRNG). Analyzing sequences ...

data structures and their algorithms. Topics include: data and procedural abstraction, amortized data structures, trees and search trees, hash tables, priority queues, graphs, shortest paths, ...

An algorithm is a list of rules to follow in order to complete a task or solve a problem. The steps in an algorithm need to be in the right order. Think about an algorithm for getting dressed in ...

However, interpreting spectral data can be difficult and time-consuming, especially when differences between samples are subtle. The new algorithm ... details or are too complex to understand ...