Students will soon figure out algorithms are part of the many things they do everyday from planning their day, working on a project to writing code. An algorithm is a detailed step-by-step instruction set or formula for solving a problem or completing a task.
A comprehensive introduction to control system synthesis in which the digital computer plays a major role, reinforced with hands-on laboratory experience. Covers elements of real-time computer architecture; input-output interfaces and data converters; analysis and synthesis of sampled-data control systems using classical and modern (state-space) methods; analysis of trade-offs in control algorithms for computation speed and quantization effects. Laboratory projects emphasize practical digital servo interfacing and implementation problems with timing, noise, nonlinear devices.
Students will take a sequence of events or steps for some process and create an algorithm. This could apply to any content area. They will display the algorithm in flowchart form. This activity can be modified for all grade levels and content areas.
In this guide you will find eleven terms and definitions for Computational Thinking (CT) concepts. These concepts can be incorporated into existing lesson plans, projects, and demonstrations in order to infuse CT into any disciplinary subject.
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Introduction to the theory and application of large-scale dynamic programming. Markov decision processes. Dynamic programming algorithms. Simulation-based algorithms. Theory and algorithms for value function approximation. Policy search methods. Games. Applications in areas such as dynamic resource allocation, finance and queueing networks, among others.
Students explore the concept of optical character recognition (OCR) in a problem-solving environment. They research OCR and OCR techniques and then apply those methods to the design challenge by developing algorithms capable of correctly "reading" a number on a typical high school sports scoreboard. Students use the structure of the engineering design process to guide them to develop successful algorithms. In the associated activity, student groups implement, test and revise their algorithms. This software design lesson/activity set is designed to be part of a Java programming class.
Testing is critical to any design, whether the creation of new software or a bridge across a wide river. Despite risking the quality of the design, the testing stage is often hurried in order to get products to market. In this lesson, students focus on the testing phase of the software/systems design process. They start by exploring existing examples of program testing using the CodingBat website, which contains a series of problems and challenges that students solve using the Java programming language. Working in teams, students practice writing test cases for other groups' code, and then write test cases for a program before writing the program itself.
Student groups use the Java programming language to implement the algorithms for optical character recognition (OCR) that they developed in the associated lesson. They use different Java classes (provided) to test and refine their algorithms. The ultimate goal is to produce computer code that recognizes a digit on a scoreboard. Through this activity, students experience a very small part of what software engineers go through to create robust OCR methods. This software design lesson/activity set is designed to be part of a Java programming class.
This course begins with an introduction to the theory of computability, then proceeds to a detailed study of its most illustrious result: Kurt GĚŚdel's theorem that, for any system of true arithmetical statements we might propose as an axiomatic basis for proving truths of arithmetic, there will be some arithmetical statements that we can recognize as true even though they don't follow from the system of axioms. In my opinion, which is widely shared, this is the most important single result in the entire history of logic, important not only on its own right but for the many applications of the technique by which it's proved. We'll discuss some of these applications, among them: Church's theorem that there is no algorithm for deciding when a formula is valid in the predicate calculus; Tarski's theorem that the set of true sentence of a language isn't definable within that language; and GĚŚdel's second incompleteness theorem, which says that no consistent system of axioms can prove its own consistency.
Students will learn about algorithms and how to create and follow step-by-step instructions when going through the code.org lessons.