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.
As currently taught in the United States, introductory courses in analytical chemistryemphasize quantitative (and sometimes qualitative) methods of analysis along with a heavydose of equilibrium chemistry. Analytical chemistry, however, is much more than a collection ofanalytical methods and an understanding of equilibrium chemistry; it is an approach to solvingchemical problems. Although equilibrium chemistry and analytical methods are important, theircoverage should not come at the expense of other equally important topics.
The introductory course in analytical chemistry is the ideal place in the undergraduate chemistry curriculum forexploring topics such as experimental design, sampling, calibration strategies, standardization,optimization, statistics, and the validation of experimental results. Analytical methods comeand go, but best practices for designing and validating analytical methods are universal. Becausechemistry is an experimental science it is essential that all chemistry students understand theimportance of making good measurements.
My goal in preparing this textbook is to find a more appropriate balance between theoryand practice, between “classical” and “modern” analytical methods, between analyzing samplesand collecting samples and preparing them for analysis, and between analytical methods anddata analysis. There is more material here than anyone can cover in one semester; it is myhope that the diversity of topics will meet the needs of different instructors, while, perhaps,suggesting some new topics to cover.
Apply the sampling distribution of the sample mean as summarized by the Central Limit Theorem (when appropriate). In particular, be able to identify unusual samples from a given population.
" 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."
A series of progressive composition projects, culminating in a large final projecting, using various types of music hardware and software. Instruction in recording, editing, synthesis, sampling, digital sound processing, sequencing, and interactive systems. Close listening to computer and electronic music from various genres including Varese, Cage, Schaeffer, Xenakis, Lansky, Stockhausen, Tcherepnin, Barlow, Gunter, and Eno. Subject focuses on using the computer as a means of musical creativity and intuition.
Learning Objectives: 1).Determine point estimates in simple cases, and make the connection between the sampling distribution of a statistic, and its properties as a point estimator.
2). Explain what a confidence interval represents and determine how changes in sample size and confidence level affect the precision of the confidence interval.
3). Find confidence intervals for the population mean and the population proportion (when certain conditions are met), and perform sample size calculations.
Begins with the premise that the 1960s mark a great dividing point in the history of twentieth-century Western musical culture, and explores the ways in which various social and artistic concerns of composers, performers, and listeners have evolved since that decade. Focuses on works by classical composers from around the world. Topics to be explored include: the impact of rock, as it developed during the 1960s-70s; the concurrent emergence of post-serial, neo-tonal, Minimalist, and New Age styles; the globalization of Western musical traditions; the impact of new technologies; and the significance of music video, video games, and other versions of (digital) multimedia. Interweaves discussion of these topics with close study of seminal musical works, evenly distributed across the four decades since 1960. Works by MIT composers included.
"This course is an investigation into the history and aesthetics of music and technology as deployed in experimental and popular musics from the 19th century to the present. Through original research, creative hands-on projects, readings, and lectures, the following topics will be explored. The history of radio, audio recording, and the recording studio, as well as the development of musique concr?te and early electronic instruments. The creation and extension of musical interfaces by composers such as Harry Partch, John Cage, Conlon Nancarrow, and others. The exploration of electromagnetic technologies in pickups, and the development of dub, hip-hop, and turntablism. The history and application of the analog synthesizer, from the Moog modular to the Roland TR-808. The history of computer music, including music synthesis and representation languages. Contemporary practices in circuit bending, live electronics, and electro-acoustic music, as well as issues in copyright and intellectual property, will also be examined. No prerequisites."
LEARNING OBJECTIVE: Identify and distinguish between a parameter and a statistic.
LEARNING OBJECTIVE: Explain the concepts of sampling variability and sampling distribution.
" The course serves as an introduction to the theory and practice behind many of today's communications systems. 6.450 forms the first of a two-course sequence on digital communication. The second class, 6.451 Principles of Digital Communication II, is offered in the spring. Topics covered include: digital communications at the block diagram level, data compression, Lempel-Ziv algorithm, scalar and vector quantization, sampling and aliasing, the Nyquist criterion, PAM and QAM modulation, signal constellations, finite-energy waveform spaces, detection, and modeling and system design for wireless communication."
This course introduces theoretical and practical principles of design of oceanographic sensor systems. Topics include: transducer characteristics for acoustic, current, temperature, pressure, electric, magnetic, gravity, salinity, velocity, heat flow, and optical devices; limitations on these devices imposed by ocean environments; signal conditioning and recording; noise, sensitivity, and sampling limitations; and standards. Lectures by experts cover the principles of state-of-the-art systems being used in physical oceanography, geophysics, submersibles, acoustics. For lab work, day cruises in local waters allow students to prepare, deploy and analyze observations from standard oceanographic instruments.
This course develops skills in research design for policy analysis and planning. The emphasis is on the logic of the research process and its constituent elements. The course relies on a seminar format so students are expected to read all of the assigned materials and come to class prepared to discuss key themes, ideas, and controversies. Since the materials draw broadly on the social sciences, and since students have diverse interests and methodological preferences, ongoing themes in our discussions will be linking concepts to planning scholarship in general and considering how different epistemological orientations and methodological techniques map on to planning specializations.
1). Identify the sampling method used in a study and discuss its implications and potential limitations.
2). Critically evaluate the reliability and validity of results published in mainstream media.
3). Summarize and describe the distribution of a categorical variable in context.
Subject provides a solid theoretical foundation for the analysis and processing of experimental data, and real-time experimental control methods. Includes spectral analysis, filter design, system identification, simulation in continuous and discrete-time domains. Emphasis on practical problems with laboratory exercises. Subject is designated as a d'Arbeloff Laboratory "gateway" subject.
This course was developed in 1987 by the MIT Center for Advanced Engineering Studies. It was designed as a distance-education course for engineers and scientists in the workplace. Signals and Systems is an introduction to analog and digital signal processing, a topic that forms an integral part of engineering systems in many diverse areas, including seismic data processing, communications, speech processing, image processing, defense electronics, consumer electronics, and consumer products. The course presents and integrates the basic concepts for both continuous-time and discrete-time signals and systems. Signal and system representations are developed for both time and frequency domains. These representations are related through the Fourier transform and its generalizations, which are explored in detail. Filtering and filter design, modulation, and sampling for both analog and digital systems, as well as exposition and demonstration of the basic concepts of feedback systems for both analog and digital systems, are discussed and illustrated.
Introductory statistics course developed through the Ohio Department of Higher Education OER Innovation Grant. The course is part of the Ohio Transfer Module and is also named TMM010. For more information about credit transfer between Ohio colleges and universities please visit: www.ohiohighered.org/transfer.Team LeadKameswarrao Casukhela Ohio State University – LimaContent ContributorsEmily Dennett Central Ohio Technical CollegeSara Rollo North Central State CollegeNicholas Shay Central Ohio Technical CollegeChan Siriphokha Clark State Community CollegeLibrarianJoy Gao Ohio Wesleyan UniversityReview TeamAlice Taylor University of Rio GrandeJim Cottrill Ohio Dominican University
Producing Data – Sampling MethodsIn this module we will explore the different sampling methods to obtain representative samples from a population. We also learn about the relative advantages and disadvantages of each method. Learning Objectives:Reasons for samplingRandom Vs. Non-Random SamplesSampling Bias and VariabilityRandom Sampling Methods – Simple, Stratified, Systematic, Cluster and Multistage random samplesNon-Random Sampling Methods – Voluntary Response and Convenience samplingSample surveys, sampling errorsBest method of random samplingSampling distributions