http://www.merlot.org:80/merlot/ A search of MERLOT materials Copyright 1997-2013 MERLOT. All rights reserved. Wed, 19 Jun 2013 23:25:13 PDT Wed, 19 Jun 2013 23:25:13 PDT http://www.merlot.org:80/merlot/images/merlot.gif http://www.merlot.org:80/merlot/ 44 34 http://www.merlot.org/merlot/viewMaterial.htm?id=351579 Machine Learning is one of the ten free courses being offered to the public through Stanford Engineering Everywhere. The course belongs to the Artificial Intelligence series and is taught by Andrew Ng, Assistant Professor of Stanford University's Computer Science Department. This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control. The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing. http://www.merlot.org/merlot/viewMaterial.htm?id=288822 USU OCW is a free and open educational resource for faculty, students, and self-learners, throughout Utah and around the world. OCW supports USU's mission to serve the public through learning, discovery, and engagement. There are available courses in the follwing areas: Anthropology, Biological and Irrigation Engineering, Civil and Enviornmental Engineering, Education, Electrical and Computer Engineering, English. Family, Consumer and Human Development, History, Technology, Languages, Philosophy, Speech, Physics and Theatre Arts. The website also includes the following features to help provide more information for the courses available: imgages/graphics, quizzes, other interactivity, learning assignment and teacher's guide. For more information please go to:http://ocw.usu.edu http://www.merlot.org/merlot/viewMaterial.htm?id=591307 The course deals with introduction to design of feedback control systems, properties and advantages of feedback systems, time-domain and frequency-domain performance measures, stability and degree of stability. It also covers root locus method, nyquist criterion, frequency-domain design, and state space methods. http://www.merlot.org/merlot/viewMaterial.htm?id=555670 This is a reading and discussion subject on issues in the engineering of software systems and software development project design. It includes the present state of software engineering, what has been tried in the past, what worked, what did not, and why. Topics may differ in each offering, but will be chosen from: the software process and lifecycle; requirements and specifications; design principles; testing, formal analysis, and reviews; quality management and assessment; product and process metrics; COTS and reuse; evolution and maintenance; team organization and people management; and software engineering aspects of programming languages. http://www.merlot.org/merlot/viewMaterial.htm?id=591645 This course will cover fundamentals of digital communications and networking. We will study the basics of information theory, sampling and quantization, coding, modulation, signal detection and system performance in the presence of noise. The study of data networking will include multiple access, reliable packet transmission, routing and protocols of the internet. The concepts taught in class will be discussed in the context of aerospace communication systems: aircraft communications, satellite communications, and deep space communications. http://www.merlot.org/merlot/viewMaterial.htm?id=591273 Upon successful completion of this course, students will be able to:Create lumped parameter models (expressed as ODEs) of simple dynamic systems in the electrical and mechanical energy domainsMake quantitative estimates of model parameters from experimental measurementsObtain the time-domain response of linear systems to initial conditions and/or common forcing functions (specifically; impulse, step and ramp input) by both analytical and computational methodsObtain the frequency-domain response of linear systems to sinusoidal inputsCompensate the transient response of dynamic systems using feedback techniquesDesign, implement and test an active control system to achieve a desired performance measureMastery of these topics will be assessed via homework, quizzes/exams, and lab assignments. http://www.merlot.org/merlot/viewMaterial.htm?id=591614 This course develops the fundamentals of feedback control using linear transfer function system models. It covers analysis in time and frequency domains; design in the s-plane (root locus) and in the frequency domain (loop shaping); describing functions for stability of certain non-linear systems; extension to state variable systems and multivariable control with observers; discrete and digital hybrid systems and the use of z-plane design. Assignments include extended design case studies and capstone group projects. Graduate students are expected to complete additional assignments. http://www.merlot.org/merlot/viewMaterial.htm?id=591312 This course models multi-domain engineering systems at a level of detail suitable for design and control system implementation. Topics include network representation, state-space models; multi-port energy storage and dissipation, Legendre transforms; nonlinear mechanics, transformation theory, Lagrangian and Hamiltonian forms; and control-relevant properties. Application examples may include electro-mechanical transducers, mechanisms, electronics, fluid and thermal systems, compressible flow, chemical processes, diffusion, and wave transmission. http://www.merlot.org/merlot/viewMaterial.htm?id=591260 This course is a comprehensive introduction to control system synthesis in which the digital computer plays a major role, reinforced with hands-on laboratory experience. The course 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, and nonlinear devices. http://www.merlot.org/merlot/viewMaterial.htm?id=591271 Multi-scale systems (MuSS) consist of components from two or more length scales (nano, micro, meso, or macro-scales). In MuSS, the engineering modeling, design principles, and fabrication processes of the components are fundamentally different. The challenge is to make these components so they are conceptually and model-wise compatible with other-scale components with which they interface. This course covers the fundamental properties of scales, design theories, modeling methods and manufacturing issues which must be addressed in these systems. Examples of MuSS include precision instruments, nanomanipulators, fiber optics, micro/nano-photonics, nanorobotics, MEMS (piezoelectric driven manipulators and optics), X-Ray telescopes and carbon nano-tube assemblies. Students master the materials through problem sets and a project literature critique.